Welcome to use FoxRenderFarm SDK!

RenderBus at a glance

Overview

   We provide a simple Python rendering SDK to make use of our cloud rendering service easily;    This official rendering SDK is developed and maintained by RD and TD groups of RENDERBUS;    This rendering SDK has been tested on python2.7 and python3.6;

Why to use the rendering SDK?

   1. Automation. The SDK automates the process of using the cloud rendering service (analysing scens, uploading assets, rendering, downloading, etc). Users can integrate the modules to there own workflow(such as DeadLine, Qube, etc).

   2. Open source. Users can customize the codes or submit development suggestions.

   3. Cross-version. Python2 and python3 are both supported.

   4. Cross-platform. Windows and Linux are both supported(rayvision_sync only supports Windows and Centos7 and above).

   5. Security. Dynamic signature algorithm authentication (HmacSHA256 + Base64 + UTC timestamp time-limited authentication + random number to prevent replay attacks) adopted, more secure.

   6. Provide a variety of invoking ways. Support local and remote analysis.

   7. Independence. Isolate the API functions, easily expanding.

   8. Complete Documentation.

Supported software

  • Maya
  • Houdini
  • Clarisse
  • 3ds Max
  • Katana
  • Arnorld Standalone

Note

If the user analyzes the scene by himself, the theory can also support rendering software such as Blender, c4d, Arnold Standalone, and KeyShot.

Preparation

  1. An account of RENDERBUS
  2. Apply to use the render SDK from RENDERBUS Developer Center and get the AccessID and AccessKey

Installation

Refer to Installation Guide

Get started

Refer to SDK Getting Started Tutorial

Parameter setting

Refer to Detailed parameters configuration

Important

Make sure local Python environment and PIP are available before use.

Installation Guide

Method One (recommended):

Note

Users who have limited access to the Python official address network can download and install from our custom server。

  • Download from Python official pypi (recommended)

    pip install rayvision_maya

    pip install rayvision_clarisse

    pip install rayvision_houdini

  • Install from a custom PIP server

    Before using specific rendering modules, such as Houdini rendering, please refer to the following installation method to install the modules in turn rayvision_log, rayvision_api , rayvision_utils , rayvision_sync,

Method Two:

Download source code directly from GitHub:

git clone https://github.com/foxrenderfarm/rayvision_log.git

git clone https://github.com/foxrenderfarm/rayvision_api.git

git clone https://github.com/foxrenderfarm/rayvision_utils.git

git clone https://github.com/foxrenderfarm/rayvision_sync.git

other modules are installed similarly to the secondary installation method

SDK tutorial

I. Login authentication

render_para = {
    "domain": "jop.foxrenderfarm.com",  # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "2",
    "access_id": "xxxx",
    "access_key": "xxxx",
}

api = RayvisionAPI(
        access_id=render_para['access_id'],
        access_key=render_para['access_key'],
        domain=render_para['domain'],
        platform=render_para['platform']
    )

RayvisionAPI Parameters:

Parameters Type Required Default Description
domain string Y task.renderbus.com China user：task.renderbus.com，Foreign user：jop.foxrenderfarm.com
platform string Y 2 platform ID，example: W2:"2", W6/qingyun:"6", GPU Region 1:"21"
access_id string Y user authorization id
access_key string Y user authorization key

II. Analysis of the scene

Analysis is independent(Maya / Houdini / Clarisse)

Example for Houdini:

from rayvision_houdini.analyze_houdini import AnalyzeHoudini

analyze_info = {
    "cg_file": r"D:\files\CG FILE\flip_test_slice4.hip",
    "workspace": "c:/workspace",
    "software_version": "17.5.293",
    "project_name": "Project1",
    "plugin_config": {
        'renderman': '22.6'
    }
}
analyze_obj = AnalyzeHoudini(**analyze_info)
analyze_obj.analyse()

Instructions：

  • “workspace” is used to control the location of the generated json file. If workspace is not set, the default location is generated:

    windows : os.environ["USERPROFILE"] + "renderfarm_sdk"  
Linux：os.environ["HOME"] + “renderfarm_sdk”

  • Analytically generated task.json is no “task_id”、“user_id”、”project_id” parameters，Users can choose to write the three parameters themselves, or to write the three parameters automatically when check.

AnalyzeHoudini Parameters:

Parameters Type Required Default Description
cg_file string Y Scenario files to analyze
software_version string Y The version of the software
project_name string N The project name
plugin_config dict N The plug-in configuration，example {'renderman': '22.6'}
workspace string N None Analyze the location of the generated json file (avoiding duplication automatically adds a timestamp folder)

III. Add special fields and update the json file interface

Only updates and modifications to the parameters of task.json and upload.json files are supported.

1. Modify the task.json

update_task_info(update_info, task_path)

https://blog-tao625.oss-cn-shenzhen.aliyuncs.com/izone/blog/20200402094336.pngtask_info

from rayvision_api.utils import update_task_info, append_to_task, append_to_upload
update_task = {
    "pre_frames": "100",  # Sets the priority to render the first frame
    "stop_after_test": "1"  # Stop rendering after rendering the priority frame
}
update_task_info(update_task, analyze_obj.task_json)

2. task.json add custom parameters

The added custom parameters will be integrated into dictionary for key is “additional_info”. 【Warning】：Custom parameters will not take effect immediately. If you have this requirement, please contact our customer service。

https://blog-tao625.oss-cn-shenzhen.aliyuncs.com/izone/blog/20200402094058.pngadditional_info

custom_info_to_task = {
    "env": "houdini_env"
}
append_to_task(custom_info_to_task, analyze_obj.task_json)

3. user custom upload.json

Support custom add file path to upload.json, will automatically deduplicate append_to_upload(files_paths, upload_path)

https://blog-tao625.oss-cn-shenzhen.aliyuncs.com/izone/blog/20200402094235.pngupload

custom_info_to_upload = [
    r"D:\houdini\CG file\Cam003\cam.abc",
]
append_to_upload(custom_info_to_upload, analyze_obj.upload_json)

IV. Validate json file

When validating, we check whether there is’ user_id ‘, ‘project_id’, ‘task_id’ in task.json, If not, the interface is called to fetch the relevant parameters from the server and write task.json

check_obj = RayvisionCheck(api, analyze_obj)
task_id = check_obj.execute(analyze_obj.task_json, analyze_obj.upload_json)

V. Upload

Now there are two ways:

1.Upload the json file first and then upload the resource file according to “upload.json”:

Four json files are uploaded, and the transfer engine automatically starts uploading the scene, resource, and other files based on the upload.json file.

upload(self,task_id,task_json_path,tips_json_path,asset_json_path,upload_json_path, max_speed=None)

CONFIG_PATH = [
    r"C:\workspace\work\tips.json",
    r"C:\workspace\work\task.json",
    r"C:\workspace\work\asset.json",
    r"C:\workspace\work\upload.json",
]
upload_obj = RayvisionUpload(api)
upload_obj.upload(str(task_id), *CONFIG_PATH)

2.Uploading json files is completely independent of the user resources:

Uploading resources：upload_asset(self, upload_json_path, max_speed=None, is_db=True)

Upload json file: upload_config(self, task_id, config_file_list, max_speed=None)

CONFIG_PATH = [
    r"C:\workspace\work\tips.json",
    r"C:\workspace\work\task.json",
    r"C:\workspace\work\asset.json",
]
UPLOAD = RayvisionUpload(api)
UPLOAD.upload_asset(r"C:\workspace\work\upload.json", is_db=False)
UPLOAD.upload_config("5165465", CONFIG_PATH)

【Warning】:You need a task ID to upload a json file, but you don’t need a task ID to upload a resource file;The ‘is_db’ parameter in upload_asset is used to control whether or not a local database is needed. By default, a local database is used;

VI. Submit Task

api.submit(int(task_id))

VIII. Download

Download now provides 3 ways:

1. Supports custom downloads of hierarchical directory structures under each rendering task.

download(self, task_id_list=None, max_speed=None, print_log=True, download_filename_format="true",local_path=None, server_path=None)

download = RayvisionDownload(api)
download.download(download_filename_format="true", server_path="18164087_muti_layer_test/l_ayer2")

Warning：This method needs to provide the task ID if the “server_path” is not empty, and the task ID does not take effect if there is a custom “server_path”.

2. Realtime download, that is, the task rendering completed a frame began to download

auto_download(self, task_id_list=None, max_speed=None, print_log=False, sleep_time=10, download_filename_format="true", local_path=None)

download = RayvisionDownload(api)
download.auto_download([18164087], download_filename_format="false")

Warning：The method task ID cannot be empty

3. The task is not downloaded until all frames are rendered

auto_download_after_task_completed(self, task_id_list=None, max_speed=None, print_log=True, sleep_time=10, download_filename_format="true", local_path=None):

download = RayvisionDownload(api)
download.auto_download_after_task_completed([18164087], download_filename_format="false")

Warning: The method task ID cannot be empty

IX. Attachment: transfer configuration file

1. Transport configuration Settings include:

Select database type, database file path Settings, transfer log path Settings

2. The transport configuration file used by default: db_config.ini， The following figure

https://blog-tao625.oss-cn-shenzhen.aliyuncs.com/izone/blog/20200415114705.pngdb_config.ini

db_config.ini:

[TRANSFER_LOG_PATH]
transfer_log_path =

[DATABASE_CONFIG]
on = true
type = sqlite
db_path =D:\test\upload

[REDIS]
host = 127.0.0.1
port = 6379
password =
table_index = 0
timeout = 5000

[SQLITE]
temporary = false

The user can also modify the configuration for the template based on the default configuration and specify the database configuration file location, specifying a custom configuration file as follows.

from rayvision_sync.upload import RayvisionUpload

UPLOAD = RayvisionUpload(api, db_config_path=r"D:\test\upload\db_config.ini")

3. db_config.ini Parameters:

Parameters instructions Default
transfer_log_path Transfer engine log file path
on Whether to use a local database, true / false: Yes / No true
type Select database,currently only supports "redis" and "sqlite" sqlite
db_path The database file saves the path
host redis database host 127.0.0.1
port redis database port 6379
password redis database password
table_index Redis Repositories，cannot be empty
timeout Redis client connection timeout,unit ms 5000
temporary When using sqlite database, if the uploaded record data is deleted after the completion of the upload, the default "false" will not be deleted false

4. transfer_log_path and db_path The priority rule for values is as follows:

  • db_config.ini custom paths are preferred if they are set；

  • No custom path is as follows:

    transfer_log_path

    • Use environment variables first ‘RAYVISION_LOG’

    • Second use:

      window: The environment variable “USERPROFILE”/<renderfarm_sdk>Linux: The environment variable “HOME” /<renderfarm_sdk>

    db_path

    • Use environment variables first ‘RAYVISION_LOG’

    • Second use:

      window: The environment variable “USERPROFILE”/<renderfarm_sdk>Linux：The environment variable “HOME” /<renderfarm_sdk>

Rayvision Api

Note

API entry function module

Note

task is mainly used to verify the analysis results and to configure some initial task information.

Note

Set option for asset and general configuration of the task.

RayvisionTask

Note

operators is mainly used for calling the rendering interface.

Environment setting and calling the rendering platform service interface.

RenderEnv

Set the rendering environment configuration.

class rayvision_api.operators.env.RenderEnvOperator(connect)

Bases: object

The rendering environment configuration.

add_render_env(data)

Adjust user rendering environment configuration.

Parameters:data (dict) –

Rendering environment configuration. e.g.:

{
‘cgId’: “2000”, ‘cgName’: ‘Maya’, ‘cgVersion’: ‘2018’, ‘renderLayerType’: 0, ‘editName’: ‘tests’, ‘renderSystem’: 1, ‘pluginIds’: [2703]

}
Returns:
Render env info.
e.g.:
{
‘editName’: ‘tests’

}
Return type:dict
delete_render_env(edit_name)

Delete user rendering environment configuration.

Parameters:edit_name (str) – Rendering environment custom name.
get_render_env(name=None, cg_names=None, os_name=1)

Get the user rendering environment configuration.

Parameters:
  • name (str, optional) –

    The name of the DCC. e.g.:

    maya, houdini, 3ds Max
  • cg_names (list for str, optional) – Software configuration for queries.
  • os_name (int) – Operating system selection, default is 1, 0: Linux, 1: windows
Returns:

Software info.
e.g.:
[
{

“cgId”: 2000, “editName”: “testRenderEnv332”, “cgName”: “Maya”, “cgVersion”: “2020”, “osName”: 0, “renderLayerType”: 0, “isDefault”: 0, “respUserPluginInfoVos”: [

{

“pluginId”: 1166, “pluginName”: “wobble”, “pluginVersion”: “wobble 0.9.5”

}

]

}, {

”cgId”: 2000, “editName”: “testRenderEnv222”, “cgName”: “Maya”, “cgVersion”: “2020”, “osName”: 0, “renderLayerType”: 0, “isDefault”: 0, “respUserPluginInfoVos”: [

{

“pluginId”: 1166, “pluginName”: “wobble”, “pluginVersion”: “wobble 0.9.5”

}

]
Return type:

list
set_default_render_env(edit_name)

Set the default render environment configuration.

Parameters:edit_name (str) – Rendering environment custom name.
update_render_env(data)

Modify the user rendering environment configuration.

Parameters:data (dict) –

Rendering environment configuration. e.g.:

{
‘cgId’: “2000”, ‘cgName’: ‘Maya’, ‘cgVersion’: ‘2018’, ‘renderLayerType’: 0, ‘editName’: ‘tests’, ‘renderSystem’: 1, ‘pluginIds’: [2703],

}.

Query

API query operation.

class rayvision_api.operators.query.QueryOperator(connect)

Bases: object

API query operation.

all_frame_status()

Get the overview of task rendering frame.

Returns:
Frames status info.
e.g.:
{
“executingFramesTotal”: 1, “doneFramesTotal”: 308, “failedFramesTotal”: 2, “waitingFramesTotal”: 153, “totalFrames”: 577

}
Return type:dict
error_detail(code=None, codes=None, language=0)

Get analysis error code.

Parameters:
  • code (string) –

    Required value, error code. e.g.:

    10010. 15000.
  • codes (list for int) – error codes
  • language (int, optional) – Not required, language, 0: Chinese (default) 1: English.
Returns:

Detailed list of error messages.
e.g.:
[
{

“id”: 5, “code”: “15000”, “type”: 1, “languageFlag”: 0, “desDescriptionCn”: “启动 3ds max 卡住或者失败”, “desSolutionCn”: “1.检查启用对应版本的 3ds max

是否有特殊弹窗，有的话手动关闭；n2.检查操作系 统是否设置了高级别的权限”,

”solutionPath”: “

http://note.youdao.com/noteshare?id=d8f1ea0c46dfb524af798f6b1d31cf6f”,

”isRepair”: 0, “isDelete”: 1, “isOpen”: 1, “lastModifyAdmin”: “”, “updateTime”: 1534387709000

},

]
Return type:

list
get_all_frames(task_id, start_page=1, end_page=2000, page_size=100)

Gets all frame details for the specified task.

Parameters:
  • task_id (int) – small task id
  • start_page (int) – The start page that you want to query.
  • end_page (int) – The end page that you want to query.

Returns (dict): all frames detail info.

get_custome_frames(task_id, restartframes)

Retrieves the frame of the specified task according to the frame。

Parameters:
  • task_id (int) – small task id
  • restartframes (list) –

    The frame number needs to be redrawn. .. rubric:: Examples

    [“2-4[1]”, “10”]
get_frame_thumbnall(frame_id, frame_status=4)

Load thumbnail.

Parameters:
  • frame_id (int) – Frame id.
  • frame_status (int) – State of the frame, only complete with thumbnails.
Returns:

Thumbnail path.
Example:
[

“small_pic100000100001138Render_264_renderbus_0008[-]jpg.jpg”

]
Return type:

list
get_raysync_user_key()

Get the user rendering environment configuration.

Returns:
User login raysync information.
Example:
{
‘raySyncUserKey’: ‘8ccb94d67c1e4c17fd0691c02ab7f753cea64e3d’, ‘userName’: ‘test’, ‘platform’: 2,

}
Return type:dict
get_task_list(page_num=1, page_size=100, status_list=None, search_keyword=None, start_time=None, end_time=None)

Get task list.

An old to the new row, the old one.

Parameters:
  • page_num (int) – Required value, current page.
  • page_size (int) – Required value, numbers displayed per page.
  • status_list (list<int>) – status code list，query the status of the task in the list.
  • search_keyword (string) – Optional, scenario name or job ID.
  • start_time (string) – Optional, search limit for start time.
  • end_time (string) – Optional, search limit for end time.
Returns:

Task info, please see the documentation for details.
e.g.:
{

“pageCount”: 32, “pageNum”: 1, “total”: 32, “size”: 1, “items”: [

{

“sceneName”: “衣帽间.max”, “id”: 18278, “taskAlias”: “P18278”, “taskStatus”: 0, “statusText”: “render_task_status_0”, “preTaskStatus”: 25, “preStatusText”: “render_task_status_25”, “totalFrames”: 0, “abortFrames”: null, “executingFrames”: null,

},

]

}
Return type:

dict
get_task_processing_img(task_id, frame_type=None)

Get the task progress diagram,currently only Max software is supported.

Parameters:
  • task_id (int) – Task id.
  • frame_type (int) – Apply colours to a drawing type, nonessential 2 represents the photon frame, 5 gets the main picture progress, and returns the result dynamically according to the stage of the rendering task
  • Example –
    {
    “taskId”:389406

    }
Returns: Task progress diagram information
dict:
Example:
{

“block”:16, “currentTaskType”:”Render”, “grabInfo”:[

[
{
“couponFee”:”0.00”, “frameIndex”:”0”, “renderInfo”:””, “frameBlock”:”1”, “frameEst”:”0”, “grabUrl”:”/mnt/output/d20/small_pic/10001500/10001834/389406/Render_2018110900083_0_frame_0[_]block_0[_]_STP00000_Renderbus_0000[-]tga.jpg”, “feeAmount”:”0.20”, “frameUsed”:”66”, “frameStatus”:”4”, “framePercent”:”100”, “isMaxPrice”:”0”, “startTime”:”2018-11-09 18:28:26”, “endTime”:”2018-11-09 18:29:32”

}

]

], “height”:1500, “sceneName”:”com_589250.max-Camera007”, “startTime”:”2018-11-09 18:27:40”, “width”:2000

}

get_transfer_server_msg()

Get the user rendering environment configuration.

Returns:
Connect raysync information.
Example:
{
‘raysyncTransfer’: {
‘port’: 2542, ‘proxyIp’: ‘render.raysync.cn’, ‘proxyPort’: 32011, ‘serverIp’: ‘127.0.0.1’, ‘serverPort’: 2121, ‘sslPort’: 2543

}

}
Return type:dict
platforms()

Get platforms.

Returns:
Platforms info.
e.g.:
[
{
“platform”: 2, “name”: “query_platform_w2”

},

]
Return type:list
restart_failed_frames(task_param_list, status=None)

Replay failed frames for large tasks.

Parameters:
  • task_param_list (list of str) – Task ID list.
  • status (list for int) – task status
restart_frame(task_id, select_all=1, ids_list=None, status=None)

Re-submit the specified frame.

Parameters:
  • task_id (int) – Task ID number.
  • ids_list (list, optional) – Frame ID list, valid when select_all is 0.
  • select_all (int, optional) – Whether to re-request all, 1 represents the user select all operation, 0 represents the user is not all selected, taskId is required when filling in 1, or ids is required when filling in 0 or not.
  • status (list for int, optional) – Specifies the state of the reframe.
supported_plugin(name)

Get supported rendering software plugins.

Parameters:name (str) –

The name of the DCC. e.g.:

maya, houdini
Returns:
Plugin info.
e.g.:
{
“cgPlugin”: [
{
“cvId”: 19, “pluginName”: “zblur”, “pluginVersions”: [
{
“pluginId”: 1652, “pluginName”: “zblur”, “pluginVersion”: “zblur 2.02.019”

}

]

},

], “cgVersion”: [

{
“id”: 23, “cgId”: 2005, “cgName”: “CINEMA 4D”, “cgVersion”: “R19”

}

]

}
Return type:dict
supported_software()

Get supported rendering software.

Returns:
Software info.
e.g.:
{
“isAutoCommit”: 2, “renderInfoList”: [
{
“cgId”: 2000, “cgName”: “Maya”, “cgType”: “ma;mb”, “iconPath”: “/img/softimage/maya.png”, “isNeedProjectPath”: 3, “isNeedAnalyse”: 1, “isSupportLinux”: 1

}

], “defaultCgId”: 2001

}
Return type:dict
task_frames(task_id, page_num=1, page_size=100, search_keyword=None)

Get task rendering frame details.

Parameters:
  • task_id (int) – The task ID number, which is the unique identifier of the task, required field.
  • page_num (int) – Current page number.
  • page_size (int) – Displayed data size per page.
  • search_keyword (str, optional) – Is a string, which is queried according to the name of a multi-frame name of a machine rendering, optional.
Returns:

Frames info list, please see the documentation for details.
e.g.:
{

“pageCount”: 9, “pageNum”: 1, “total”: 17, “size”: 2, “items”: [

{

“id”: 1546598, “userId”: null, “framePrice”: null, “feeType”: null, “platform”: null, “frameIndex”: “0-1”, “frameStatus”: 4, “feeAmount”: 0.44, “startTime”: 1535960273000, “endTime”: 1535960762000,

},

],

}
Return type:

dict
task_info(task_ids_list)

Get task details.

Parameters:task_ids_list (list of int) – Shell task ID list.
Returns:
Task details.
e.g.:
{
“pageCount”: 1, “pageNum”: 1, “total”: 1, “size”: 100, “items”: [
{
“sceneName”: “3d66.com_593362_2018.max”, “id”: 19084, “taskAlias”: “P19084”, “taskStatus”: 0, “statusText”: “render_task_status_0”, “preTaskStatus”: 25, “preStatusText”: “render_task_status_25”, “totalFrames”: 0, “abortFrames”: null, “executingFrames”: null, “doneFrames”: null, “failedFrames”: 0, “framesRange”: “0”, “projectName”: “”, “renderConsume”: null, “taskArrears”: 0, “submitDate”: 1535958477000, “startTime”: null, “completedDate”: null, “renderDuration”: null, “userName”: “xiaoguotu_ljian”, “producer”: null, “taskLevel”: 60, “taskUserLevel”: 0, “taskLimit”: null, “taskOverTime”: null, “userId”: 10001520, “outputFileName”: null, “munuTaskId”: “”, “layerParentId”: 0, “cgId”: 2001, “taskKeyValueVo”: {
”tiles”: null, “allCamera”: null, “renderableCamera”: null

}

}

”userAccountConsume”: null

}
Return type:dict

Tag

API operation on tags.

class rayvision_api.operators.tag.TagOperator(connect)

Bases: object

Task tag settings.

add_label(new_name, status=1)

Add a custom label.

Parameters:
  • new_name (str) – Label name.
  • status (int, optional) – Label status,0 or 1,default is 1.
add_task_tag(tag, task_ids)

Add a custom task tag. :param tag: Label name. :type tag: str :param task_ids: task id list. :type task_ids: list[int], optional

delete_label(del_name)

Delete custom label.

Parameters:del_name (str) – The name of the label to be deleted.
delete_task_tag(tag_ids)

del custom task label. :param label_ids: lable id list. :type label_ids: list[int], optional

get_label_list()

Get custom labels.

Returns:
Label list info.
e.g.:
{
“projectNameList”: [
{
“projectId”: 3671, “projectName”: “myLabel”

}

]

}
Return type:dict
get_list(flag=0)

Get the project name based on the flag.

Parameters:flag (int) –
  1. Query items under this account;
  2. Query items under this account and under the master account;
  3. Query all items associated with (all items under the same master account)
get_project_list()

Get custom labels.

Returns:
Label list info.
e.g.:
[
{
“projectId”: 3671, “projectName”: “myLabel”

}

]
Return type:list

Task

Interface to operate on the task.

class rayvision_api.operators.task.TaskOperator(connect)

Bases: object

API task related operations.

TASK_PARAM = 'taskIds'
abort_task(task_param_list)

Give up the task.

Parameters:task_param_list (list) – Task ID list.
create_task(count=1, task_user_level=50, out_user_id=None, labels=None, clone_original_id=None, artist=None)

Create a task ID.

Parameters:
  • count (int, optional) – The quantity of task ID.
  • task_user_level (int) – Set the user’s task level to either 50 or 60, default is 50.
  • out_user_id (int, optional) – Non-required, external user ID, used to distinguish users accessing third parties.
  • labels (list or tuple, optional) – Custom task labels.
  • clone_original_id (int, optional) – Clone the original task ID.
  • artist (str, optional) – producer.
Returns:

The information of the task.
e.g.:
{

“taskIdList”: [1658434], “aliasTaskIdList”: [2W1658434], “userId”: 100093088

}
Return type:

dict
delete_task(task_param_list)

Delete task.

Parameters:task_param_list (list) – Task ID list.
full_speed(task_id_list)

Full to render.

Parameters:
  • task_id_list (list of int) – Task list.
  • Example –
    {
    “taskIds”:[485],

    }
set_task_overtime_top(task_id_list, overtime)

Set the task timeout stop time.

Parameters:
  • task_id_list (list of int) – Task list.
  • overtime (int or float) – Timeout time, unit: second.
  • Example –
    {
    “taskIds”:[485], “overTime”:1800

    }
start_task(task_param_list)

Start task.

Parameters:task_param_list (list) – Task ID list.
stop_task(task_param_list)

Stop the task.

Parameters:task_param_list (list) – Task ID list.
submit_task(task_id, producer=None, only_id=False)

Submit a task to rayvision render farm.

Parameters:
  • task_id (int) – Submit task ID.
  • producer (str, optional) – Producer.
task_id

The ID number of the render task.

Notes

As long as we do not initialize the class again or submit the task successfully, we can always continue to get the task id from the class instance.

Type:int
update_priority(task_id, priority)

Update the render priority for the task by given task id.

Parameters:
  • task_id (int) – The ID number of the render task.
  • priority (int) – The priority for the current render task.

User

Interface to operate the user.

class rayvision_api.operators.user.UserOperator(connect)

Bases: object

API user information operator.

get_transfer_bid()

Get user transfer BID.

Returns:
Transfer bid info.
e.g.:
{
“config_bid”: “30201”, “output_bid”: “20201”, “input_bid”: “10201”

}
Return type:dict
info
query_user_profile()

Get user profile.

Returns:
User profile info.
e.g.:
{
“userId”: 10001136, “userName”: “rayvision”, “platform”: 2, “phone”: “173333333333”, “email”: “”, “company”: “”, “name”: “”, “job”: “”, “communicationNumber”: “”, “softType”: 2000, “softStatus”: 1, “businessType”: 1, “status”: 1, “infoStatus”: 0, “accountType”: 1,

}
Return type:dict
query_user_setting()

Get user setting.

Returns:
The information of the user settings.
e.g.:
{
“infoStatus”: null, “accountType”: null, “shareMainCapital”: 0, “subDeleteTask”: 0, “useMainBalance”: 0, “singleNodeRenderFrames”: “1”, “maxIgnoreMapFlag”: “1”, “autoCommit”: “2”, “separateAccountFlag”: 0, “mifileSwitchFlag”: 0, “assfileSwitchFlag”: 0, “manuallyStartAnalysisFlag”: 0, “downloadDisable”: 0, “taskOverTime”: 12

}
Return type:dict
update_user_settings(task_over_time)

Update user settings.

Parameters:task_over_time (int) – The task timeout is set in seconds.
user_id

RayvisionAPI

Initialize user, task, query, environment, tag interface.

class rayvision_api.core.RayvisionAPI(access_id=None, access_key=None, domain='task.renderbus.com', platform='4', protocol='https', logger=None)

Bases: object

Create the request object.

Including user action, task action, query action, environment operation and tag action.

check_and_add_project_name(project_name)

Get the tag id.

Call the API interface to obtain all the label information of the user, determine whether the label name to be added already exists, and obtain the label id if it exists. If the label does not exist, the API interface is repeatedly requested. The request is up to three times. If the third time does not exist, the empty string is returned.

Parameters:project_name (str) – The name of the tag to be added.
Returns:Tag id.
Return type:int
connect

The current connect instance.

Type:rayvision.api.Connect
get_user_id()

Get user id.

Example

user_profile_info = {
“userId”: 10001136, “userName”: “rayvision”, “platform”: 2, “phone”: “173333333333”, “email”: “”, “company”: “”, “name”: “”, “job”: “”, “communicationNumber”: “”, “softType”: 2000, “softStatus”: 1, “businessType”: 1, “status”: 1, “infoStatus”: 0, “accountType”: 1,

}

Returns:The ID number of the current user.
Return type:int
submit(task_id, producer=None)

Submit a task.

Parameters:
  • task_id (int) – Task id.
  • producer (str, optional) – Producer.
submit_by_data(task_info, file_name='task.json', producer=None)

Submit tasks based on json files.

Parameters:
  • task_info (string) – task.json content.
  • file_name (string, optional) – The name of the json file to be uploaded, only support “”
  • producer (string, optional) – Producer.

Returns:

user_info

Connect

Request, request header and request result processing.

class rayvision_api.connect.Connect(access_id, access_key, protocol, domain, platform, headers=None, session=None)

Bases: object

Connect operation with the server, request.

headers

Get request headers dic.

post(api_url, data=None, validator=True)

Send an post request and return data object if no error occurred.

Request processing through the decorator, if the request fails more than five times, then the exception is ran out.

Parameters:
  • api_url (rayvision_api.api.url.URL or str) –

    The URL address of the corresponding action network Request.

    e.g.:
    /api/render/common/queryPlatforms /api/render/user/queryUserProfile /api/render/user/queryUserSetting
  • data (dict, optional) – Request data.
  • validator (bool, optional) – Validator the data.
Returns:

Response data.
Return type:

dict or List
Raises:

RayVisionAPIError – The request failed, It returns the error ID, the error message, and the request address.

API interfaces use methods

The preparatory work

All interface calls are made through the rayvision_api module, and an API object must be instantiated before use :

user_info = {
    "domain_name": "jop.foxrenderfarm.com",
    "platform": "2",
    "access_id": "xxxxxxxxxxxxxxxxxxxxxx",
    "access_key": "xxxxxxxxxxxxxxxxxxxxx",
}

api = RayvisionAPI(access_id=user_info['access_id'],
                   access_key=user_info['access_key'],
                   domain=user_info['domain_name'],
                   platform=user_info['platform'])

Warning：

  1. the following interface calls will be made directly using the API of the above instance;
  2. In the rayvision_api, the interface actually returns the user only the value of the “data” parameter ;

Obtain the platform list

Interface path： /api/render/common/queryPlatforms

Request parameters： No

Return parameters：

Parameters Type Description Memo
platform Integer Platform number
name String Platform number description

Example of request：

# automatically distinguish domestic and foreign according to the "domain" parameter 
platform = api.query.platforms()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": [
        {
            "platform": 2,
            "name": "query_platform_w2"
        }
    ],
    "serverTime": 1535949047370
}

Obtain the user information

Interface path：/api/render/setUp/queryUserProfile

Request parameter：No

Example of request：

user_profile = api.user.query_user_profile()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "userId": 10001136,
        "userName": "rayvision",
        "platform": 2,
        "phone": "173333333333",
        "email": "",
        "company": "",
        "name": "",
        "job": "",
        "communicationNumber": "",
        "softType": 2000,
        "softStatus": 1,
        "businessType": 1,
        "status": 1,
        "infoStatus": 0,
        "accountType": 1,
        "userType": 1,
        "mainUserId": 0,
        "level": 49,
        "pictureLever": null,
        "zone": 1,
        "rmbbalance": 0,
        "usdbalance": 0,
        "rmbCumulative": 0,
        "usdCumulative": 0,
        "credit": 0,
        "coupon": 49.93,
        "description": "",
        "country": "中国",
        "city": "广东 中山",
        "address": "",
        "cpuPrice": 0.67,
        "gpuPrice": 20,
        "shareMainCapital": 0,
        "subDeleteTask": 0,
        "useMainBalance": 0,
        "hideBalance": 0,
        "hideJobCharge": 0,
        "useLevelDirectory": 1,
        "downloadDisable": 0,
        "displaySubaccount": 1,
        "subaccountLimits": 5,
        "houdiniFlag": 0,
        "c4dFlag": 0,
        "blenderFlag": 0,
        "keyshotFlag": 0,
        "studentEndTime": null
    },
    "serverTime": 1535953580730
}

Obtain user settings

Interface path： /api/render/setUp/queryUserSetting

Request parameter：No

Return parameter：

Parameter Type Description Memo
infoStatus Integer
accountType Integer
shareMainCapital
subDeleteTask
useMainBalance
singleNodeRenderFrames String Multiple frames rendered on one machine
maxIgnoreMapFlag String Can choose to ignore the max map error or not 0：Do not ignore，1：Ignore
autoCommit String Can choose start scene parameter rendering 1：Do not start，2 ：Start
separateAccountFlag Integer Separate the primary and secondary account settings
mifileSwitchFlag Integer Indicate the switch option of mi Document analysis risk
assfileSwitchFlag Integer Do not analyze the ass file switch identifier
manuallyStartAnalysisFlag Integer Manually turn on the analysis switch
downloadDisable Integer Choose to disable downloading or not 1 Disable，0 Do not disable
taskOverTime Integer Timeout - hour

Example of request：

user_setting = api.user.query_user_setting()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "infoStatus": null,
        "accountType": null,
        "shareMainCapital": 0,
        "subDeleteTask": 0,
        "useMainBalance": 0,
        "singleNodeRenderFrames": "1",
        "maxIgnoreMapFlag": "1",
        "autoCommit": "2",
        "separateAccountFlag": 0,
        "mifileSwitchFlag": 0,
        "assfileSwitchFlag": 0,
        "manuallyStartAnalysisFlag": 0,
        "downloadDisable": 0,
		"taskOverTime": 12,
		"taskOverTimeSec": 3600
    },
    "serverTime": 1535954828406
}

Update user settings

Interface path： /api/render/setUp/updateUserSetting

Request parameter：

Parameter Type Necessary Description Memo
task_over_time Integer Y Set up of Task timeout situation, unit: second

Return parameter: default

Example of return：

update_user_setting = api.user.update_user_settings(task_over_time=43200)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Obtain user transfer BID

Interface path：/api/render/transfer/getBid

Request parameter：default

Return parameter：

Parameter Type Description Memo
config_bid String Configuration file transfer ID
output_bid String Download the transfer file ID
input_bid String Asset upload transfer ID
parent_input_bid String Input transfer bid for corresponding main account
sub_user_output_bids Object Subaccount Outputbids: If the accessed user is the main account, there is a subaccount value; otherwise, it is empty
userId String ID of subaccount
output_bid String output_bid for subaccount

Example of request：default

user_transfer_bid = api.user.get_transfer_bid()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "config_bid": "30201",
        "input_bid": "10201",
        "output_bid": "20201",
        "parent_input_bid": "10202",
        "sub_user_output_bids": [{
            userId:"119776",
            outputBid:"10401"
        }]
	},
    "serverTime": 1535957964631
}

Create task ID

Interface path：/api/render/submit/createTask

Request parameter：

parameter Type Necessary Description Memo
count Integer N create the number of task Numbers Not required, Default 1
out_user_id Long N external user ID Not required，used to distinguish third party access users
task_user_level Integer N task user level Not required，optional 50 and 60, default is 50
labels List N custom tag Not required
clone_original_id integer N Clone the original task ID
artist String N Productor

Return parameter：

Parameter Type Description Memo
aliasTaskIdList List\<String> Task ID alias
taskIdList List\<Integer> Task ID

Example of request：

create_task_id = api.task.create_task(count=1, 
                                      task_user_level=50,
                                      labels=["label_test1", "label_test2"])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "aliasTaskIdList": [
            "2W19097"
        ],
        "taskIdList": [
            19097
        ],
        "userId": 10007893
    },
    "serverTime": 1535959487092
}

Submit task

Interface path：/api/render/submit/task

Request parameter：

Parameter Type Necessary Description Memo
task_id Integer Y task id
producer String N producer

Return parameter：default

Example of request：

submit_task = api.task.submit_task(task_id=create_task_id[0])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Warning: Before committing, you need to call the transport interface to upload the relevant analysis configuration file .

Obtain analysis error code

Interface path： /api/render/submit/queryAnalyseErrorDetail

Request parameter：

Parameter Type Necessary Description Memo
code String N error code Codes and codes are either mandatory
codes String N Error code list Codes and codes are either mandatory
language String N language 0：Chinese（default） 1：English

Return parameter：List<CodeInfo>

Parameter Type Description Memo
id
code Integer error code
type Integer Type 0 Warning-can be ignored，1 Error-can not be ignored
languageFlag Integer languageType 0：Chinese，1：English
desDescriptionCn String Chinese description
desSolutionCn String Solution
solutionPath String Connect to solution
isRepair Integer Check if repairable or not 1：Repairable ，0：Non-repairable
isOpen Integer Check if turn on the intercept of the error or not 0：Not turn on the intercept，1：Turn on the intercept
updateTime Date The final update time

Example of request：

error_detail = api.query.error_detail(code="50001")

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": [
        {
            "id": 5,
            "code": "15000",
            "type": 1,
            "languageFlag": 0,
            "desDescriptionCn": "启动3ds max卡住或者失败",
            "desSolutionCn": "1.检查启用对应版本的3ds max是否有特殊弹窗，有的话手动关闭；\n2.检查操作系统是否设置了高级别的权限",
            "solutionPath": "http://note.youdao.com/noteshare?id=d8f1ea0c46dfb524af798f6b1d31cf6f",
            "isRepair": 0,
            "isDelete": 1,
            "isOpen": 1,
            "lastModifyAdmin": "",
            "updateTime": 1534387709000
        }
    ],
    "serverTime": 1535962451356
}

Obtain the task list

Interface path：/api/render/handle/getTaskList

Request parameter：

Parameter Type Necessary Description Memo
page_num Integer N Mandatary，number of current page Default: 1
page_size Integer N Mandatary，quantities of displaying per page Default: 1
status_list List\<Integer> N status code list，query the status of the task in the list Check task status description for details
search_keyword String N Optional, scenario name or job ID Fuzzy search
start_time String N Optional, search limit for start time Example:yyyy-MM-dd HH:mm:ss
end_time String N Optional, search limit for end time Example:yyyy-MM-dd HH:mm:ss

Task status description：

Status Status code Description
WAITING 0 Waiting
RENDERING 5 Rendering
PRE_RENDERING 8 Prepared to be handled
STOP 10 Stop
ARREARAGE_STOP 20 Stop due to arrearage
TIME_OUT_STOP 23 Stop due to timing out
FINISHED 25 Finished
FINISHED_HAS_FAILED 30 Finished with failed frames contained
ABANDON 35 Give up
FINISHED_TEST 40 Test completed
FAILED 45 Failed
ANALYSE 50 Analyzing

Return parameter：list<Task Info>

Parameter Type Description Memo
sceneName String Scene Name
id Integer Task id
taskAlias String Task Name
taskStatus Byte Task status 1/Waiting, 5/Rendering, 10/Stop, 15/User Stop, 20/Stop due to arrearage, 25/Finished, 30/Finished with failed frames contained, 35/Give up, 40/Test completed, 45/Failed
statusText String Status Text
preTaskStatus Byte Preprocessi-ng Task Status
preStatusText String Preprocessi-ng Task Status Text
totalFrames Integer Total frames
abortFrames Integer Abort frames
executingFrames Integer Executing frames
doneFrames Integer Done frames
failedFrames Integer Failed frames
framesRange String Frames range
projectName String Project name
renderConsume BigDecimal Task render consume
taskArrears BigDecimal Task arrears
submitDate Date Submit Date
startTime Date Start Date
completedDate Date Completed Date
renderDuration Long Task render duration
userName String User name
producer String producer
taskLevel Byte Task level
taskUserLevel Integer Task level of user
taskLimit Integer Task node limit
taskOverTime Long Task timeout reminder time
outputFileName String Output file name
munuTaskId String Dispatch id
layerParentId String About maya task，parent id
cgId Integer Task type 2001/maya，2000/max
taskKeyValueVo Object Task keyword
userAccountConsume Bigdecimal User account consume
couponConsume Bigdecimal Coupon consume
isOpen Byte Whether the front-end expansion button is expanded or not
taskType String Task type Preprocessing, RenderPhoton, Render
renderCamera String Render camera
cloneParentId Integer Clone parent id
cloneOriginalId Integer Clone original id
shareMainCapital Byte Whether to Share Main Account Assets 0：no , 1：yes
taskRam Integer Task render memory
respRenderingTaskList List\<TaskInfo> Child tasks of the open task Structure the same of this object
layerName String Layer name
taskTypeText String Task type text photon/picture
isDelete Byte Whether or not to delete 0: deleted, 1: not deleted

taskKeyValueVo：

parameter Type Description Memo
tiles String Tile number
allCamera String All Cameras
RenderableCarema String Render Cameras

Example of request：

task_list = api.query.get_task_list(page_num=1, page_size=1)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "pageCount": 32,
        "pageNum": 1,
        "total": 32,
        "size": 1,
        "items": [
            {
                "sceneName": "衣帽间.max",
                "id": 18278,
                "taskAlias": "P18278",
                "taskStatus": 0,
                "statusText": "render_task_status_0",
                "preTaskStatus": 25,
                "preStatusText": "render_task_status_25",
                "totalFrames": 0,
                "abortFrames": null,
                "executingFrames": null,
                "doneFrames": null,
                "failedFrames": 0,
                "framesRange": "0",
                "projectName": "",
                "renderConsume": null,
                "taskArrears": 0,
                "submitDate": 1535602289000,
                "startTime": null,
                "completedDate": null,
                "renderDuration": null,
                "userName": "xiaoguotu_ljian",
                "producer": null,
                "taskLevel": 79,
                "taskUserLevel": 0,
                "taskLimit": 200,
                "taskOverTime": null,
                "userId": 10001520,
                "outputFileName": null,
                "munuTaskId": "",
                "layerParentId": 0,
                "cgId": 2001,
                "taskKeyValueVo": {
                            "tiles": null,
                            "allCamera": null,
                            "renderableCamera": null
                        },
                "userAccountConsume": null,
                "couponConsume": null,
                "isOpen": 1,
                "taskType": "",
                "renderCamera": "VRayCam003",
                "cloneParentId": null,
                "cloneOriginalId": null,
                "shareMainCapital": 0,
                "taskRam": null,
                "respRenderingTaskList": [
                    {
                        "sceneName": "衣帽间.max",
                        "id": 18280,
                        "taskAlias": "P18280",
                        "taskStatus": 25,
                        "statusText": "render_task_status_25",
                        "preTaskStatus": null,
                        "preStatusText": null,
                        "totalFrames": 1,
                        "abortFrames": 0,
                        "executingFrames": 0,
                        "doneFrames": 1,
                        "failedFrames": 0,
                        "framesRange": "0",
                        "projectName": "",
                        "renderConsume": 1.57,
                        "taskArrears": 0,
                        "submitDate": 1535602289000,
                        "startTime": 1535602601000,
                        "completedDate": 1535603874000,
                        "renderDuration": 1176,
                        "userName": "xiaoguotu_ljian",
                        "producer": null,
                        "taskLevel": 79,
                        "taskUserLevel": 0,
                        "taskLimit": 200,
                        "taskOverTime": 86400000,
                        "userId": 10001520,
                        "outputFileName": "18280_衣帽间",
                        "munuTaskId": "2018083000075",
                        "layerParentId": 18278,
                        "cgId": 2001,
                        "taskKeyValueVo": {
                            "tiles": null,
                            "allCamera": null,
                            "renderableCamera": null
                        },
                        "userAccountConsume": 0,
                        "couponConsume": 1.57,
                        "isOpen": 0,
                        "taskType": "RenderPhoton",
                        "renderCamera": "VRayCam003",
                        "cloneParentId": 0,
                        "cloneOriginalId": 0,
                        "shareMainCapital": 0,
                        "taskRam": null,
                        "respRenderingTaskList": null,
                        "layerName": null,
                        "taskTypeText": "render_photons_task",
                        "isDelete": 1
                    },
                    {
                        "sceneName": "衣帽间.max",
                        "id": 18281,
                        "taskAlias": "P18281",
                        "taskStatus": 25,
                        "statusText": "render_task_status_25",
                        "preTaskStatus": null,
                        "preStatusText": null,
                        "totalFrames": 17,
                        "abortFrames": 0,
                        "executingFrames": 0,
                        "doneFrames": 17,
                        "failedFrames": 0,
                        "framesRange": "0",
                        "projectName": "",
                        "renderConsume": 6.7,
                        "taskArrears": 0,
                        "submitDate": 1535602289000,
                        "startTime": 1535603885000,
                        "completedDate": 1535604765000,
                        "renderDuration": 5028,
                        "userName": "xiaoguotu_ljian",
                        "producer": null,
                        "taskLevel": 79,
                        "taskUserLevel": 0,
                        "taskLimit": 200,
                        "taskOverTime": 86400000,
                        "userId": 10001520,
                        "outputFileName": "18281_衣帽间",
                        "munuTaskId": "2018083000079",
                        "layerParentId": 18278,
                        "cgId": 2001,
                        "taskKeyValueVo": {
                            "tiles": null,
                            "allCamera": null,
                            "renderableCamera": null
                        },
                        "userAccountConsume": 0,
                        "couponConsume": 6.7,
                        "isOpen": 0,
                        "taskType": "Render",
                        "renderCamera": "VRayCam003",
                        "cloneParentId": 0,
                        "cloneOriginalId": 0,
                        "shareMainCapital": 0,
                        "taskRam": null,
                        "respRenderingTaskList": null,
                        "layerName": null,
                        "taskTypeText": "render_major_picture_task",
                        "isDelete": 1
                    }
                ],
                "layerName": null,
                "taskTypeText": null,
                "isDelete": 1
            }
        ]
    },
    "serverTime": 1535964116655
}

Stop task

Interface path： /api/render/handle/stopTask

Request parameter：

parameter Type Necessary Description Memo
task_param_list List\<Integer> Y Combination of the task ID

Return parameter：default

Example of request：

stop_task = api.task.stop_task(task_param_list=[13798105])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Start task

Interface path：/api/render/handle/startTask

Request parameter：

parameter Type Necessary Description Memo
task_param_list List\<Integer> Y Combination of the task ID

Return parameter：default

Example of request：

start_task = api.task.start_task(task_param_list=[13798105])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Abandon task

Interface path：/api/render/handle/abandonTask

Request parameter：

Parameter Type Necessary Description Memo
task_param_list List\<Integer> Y Combination of the task ID

Return parameter：default

Example of request：

abort_task = api.task.abort_task(task_param_list=[13798105])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Delete task

Interface path：/api/render/handle/deleteTask

Request parameter：

Parameter Type Necessary Description Memo
task_param_list List\<Integer> Y Task ID list

Return parameter：default

Example of request：

delete_task = api.task.delete_task(task_param_list=[13798105])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Obtain the task rendering frame details

Interface path:  /api/render/handle/queryTaskFrames

Request parameter：

Parameter Type Necessary Description Memo
task_id Integer Y Task ID Task ID，Is the unique identifier of the task, mandatary field
search_keyword String N Query based on the name of the multiple frames that rendered on one machine Is a string that be queried based on name of the multiple frames that rendered on one machine, optional field
page_num Integer N Current page number
page_size Integer N Size of the data that displayed per page

Return parameter：List<FrameInfo>

Parameter Type Description Memo
id Integer frame id
userId Long userID
framePrice Double Render pricing
feeType Integer Fee charge type 0 Quantity-based，1 Machine-bashed，2 Project-based
platform Integer Platform
frameIndex String Frame sequence name
frameBlock String Current frame number
frameStatus Integer Current frame status 1/Waiting,2/Processing,3/Stopped,4/Complete,5/Failed,6/Waiting for the pre-handeling,7/Waiting for photonic frame rendering completed,8/Waiting for the priority rendering completed,9/ Wait for the photon job to finish rendering,10/Waiting for the settlement job rendering completed,11/Task timing out
feeAmount Double Balance deduction
couponFee Double Vouchers deduction
startTime Long Start time (ms)
endTime Long End time (ms)
frameExecuteTime Long Rendering frame time
frameStatusText String Frame status description
arrearsFee Double Render frame arrears amount
taskId Long Task ID
frameType Integer Frame Type 1/Pre-rendering (only one frame, even for multi-camera case), 2/photon frame, 3/combine photon frame, 4/priority frame, 5/main render frame, 6 priority /maya/max composite rendering frame, 7/maya/max rendering main picture composite frame, 8/houdini settlement frame, 9/max channel frame
recommitFlag Integer Recount times Indicate the recount time default is 0,increased as the recount time increase
taskOverTime Integer overtime Overtime details
gopName String Houdini Settlement node name
frameRam Integer Memory of the task rendering frame No memory requirement if description does not specified

Example of request:

task_frame = api.query.task_frames(task_id=13790691, page_num=1, page_size=1)

Example of return:

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "pageCount": 9,
        "pageNum": 1,
        "total": 17,
        "size": 2,
        "items": [
            {
                "id": 1546598,
                "userId": null,
                "framePrice": null,
                "feeType": null,
                "platform": null,
                "frameIndex": "0-1",
                "frameStatus": 4,
                "feeAmount": 0.44,
                "startTime": 1535960273000,
                "endTime": 1535960762000,
                "frameExecuteTime": 489,
                "frameStatusText": "task_frame_status_4",
                "arrearsFee": null,
                "munuJobId": "0",
                "taskId": 19088,
                "munuTaskId": "2018090300040",
                "frameType": 5,
                "couponFee": 0,
                "recommitFlag": 0,
                "isCopy": null,
                "frameBlock": "1",
                "taskOverTime": 86400000,
                "gopName": null,
                "frameRam": null
            },
            {
                "id": 1546599,
                "userId": null,
                "framePrice": null,
                "feeType": null,
                "platform": null,
                "frameIndex": "0-2",
                "frameStatus": 4,
                "feeAmount": 0.43,
                "startTime": 1535960856000,
                "endTime": 1535961338000,
                "frameExecuteTime": 482,
                "frameStatusText": "task_frame_status_4",
                "arrearsFee": null,
                "munuJobId": "1",
                "taskId": 19088,
                "munuTaskId": "2018090300040",
                "frameType": 5,
                "couponFee": 0,
                "recommitFlag": 0,
                "isCopy": null,
                "frameBlock": "2",
                "taskOverTime": 86400000,
                "gopName": null,
                "frameRam": null
            }
        ]
    },
    "serverTime": 1535966967143
}

Gets the page frame details for the specified task

[^api]: Add in v2.4.0

Request parameter：

Parameter Type Is necessary Description Memo
task_id Integer Y small task id If the job ID is "2W35736251", task_ID is 35736251
start_page Integer N Query Start Page, default is 1
end_page Integer N Query end page, default is 2000
page_size Integer N Specifies the number of frames to display per page, which defaults to a maximum of 100

Example of request：

all_frames = api.query.get_all_frames(task_id=35736251)

Example of return：

{
    "1": {
        "id": 665078505,
        "userId": null,
        "framePrice": null,
        "feeType": null,
        "platform": null,
        "frameIndex": "1",
        "frameStatus": 1,
        "feeAmount": 0.0,
        "startTime": 0,
        "endTime": 0,
        "frameExecuteTime": 33,
        "currentRenderTime": 0,
        "frameStatusText": "task_frame_status_1",
        "arrearsFee": null,
        "munuJobId": "0",
        "taskId": 37439351,
        "munuTaskId": "2020092801043",
        "frameType": 4,
        "couponFee": 0.037,
        "recommitFlag": 0,
        "isCopy": null,
        "frameBlock": "",
        "taskOverTime": 259200,
        "gopName": null,
        "frameRam": 64,
        "averageCpu": 9,
        "averageMemory": 2240647168,
        "isOverTime": 0,
        "overOneMonth": null,
        "renderRam": null,
        "nodeId": "10.60.3.224",
        "openRenderRam": null
    },
    "2-4[1]": {
        "id": 665078511,
        "userId": null,
        "framePrice": null,
        "feeType": null,
        "platform": null,
        "frameIndex": "2-4[1]",
        "frameStatus": 1,
        "feeAmount": null,
        "startTime": 0,
        "endTime": 0,
        "frameExecuteTime": 0,
        "currentRenderTime": 0,
        "frameStatusText": "task_frame_status_1",
        "arrearsFee": null,
        "munuJobId": "0",
        "taskId": 37439351,
        "munuTaskId": "2020092801165",
        "frameType": 5,
        "couponFee": null,
        "recommitFlag": 0,
        "isCopy": null,
        "frameBlock": "",
        "taskOverTime": 259200,
        "gopName": null,
        "frameRam": 64,
        "averageCpu": 0,
        "averageMemory": 0,
        "isOverTime": 0,
        "overOneMonth": null,
        "renderRam": null,
        "nodeId": "",
        "openRenderRam": null
    }
}

Obtain the overview of task rendering frames

Interface path： /api/render/handle/queryAllFrameStats

Request parameter：No

Return parameter：

parameter Type Description Memo
executingFramesTotal Integer Number of frames in rendering
doneFramesTotal Integer Number of frames completed
failedFramesTotal Integer Number of rendered frames failed
waitingFramesTotal Integer Number of frames in waiting
totalFrames Integer Number of overall rendered frames

Example of request：

all_frame_status = api.query.all_frame_status()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "executingFramesTotal": 1,
        "doneFramesTotal": 308,
        "failedFramesTotal": 2,
        "waitingFramesTotal": 153,
        "abandonFramesTotal": 113,
        "totalFrames": 577
    },
    "serverTime": 1535968038725
}

Re-submit the failed frames

Interface path：  /api/render/handle/recommitTasks

Request parameter：

Parameter Type Necessary Description Memo
task_param_list List\<Integer> Y Task ID list
status List\ N A set of frame task states that are not filled to represent failed frames

Return parameter：default

Example of request：

restart_failed_frames = api.query.restart_failed_frames(task_param_list=[13788981])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Re-submit the specified frames based on the frame number

[^api]: Add in v2.4.0

Request parameter：

Parameter Type Necessary Description Memo
task_id Integer Y small task id If the job ID is "2W35736251", task_ID is 35736251
restartframes List[str] Y List of frame Numbers that need to be replayed example：["6", "7-9[1]"]

Example of request：

restart_frame = api.query.get_custome_frames(task_id=37439351, restartframes=["6", "7-9[1]"])

Example of return：None

Re-submit the specified frames

Interface path： /api/render/handle/recommitTaskFrames

Request parameter：

Parameter Type Necessary Description Memo
task_id Integer N Task ID
ids_list List\<Integer> N Combine the frame ID Effective if 0 displayed when select_all
select_all Integer N Choose if re-submit all 1：All，0：Only the specified frame
status List\ N frame status Only pass taskId will take effect

Return parameter：default

Example of request：

restart_frame = api.query.restart_frame(task_id=14362099, select_all=1)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Obtain the task details

Interface path： /api/render/handle/queryTaskInfo

Request parameter：

Parameter Type Necessary Description Memo
task_ids_list List\<Integer> N Combine the shell task ID

Return parameter：List<TaskInfo>

Parameter Type Description Memo
sceneName String Scene Name
id Integer Task id
taskAlias String Task Name
taskStatus Byte Task status 1/Waiting, 5/Rendering, 10/Stop, 15/User Stop, 20/Stop due to arrearage, 25/Finished, 30/Finished with failed frames contained, 35/Give up, 40/Test completed, 45/Failed
statusText String Status Text
preTaskStatus Byte Preprocessi-ng Task Status
preStatusText String Preprocessi-ng Task Status Text
totalFrames Integer Total frames
abortFrames Integer Abort frames
executingFrames Integer Executing frames
doneFrames Integer Done frames
failedFrames Integer Failed frames
framesRange String Frames range
projectName String Project name
renderConsume BigDecimal Task render consume
taskArrears BigDecimal Task arrears
submitDate Date Submit Date
startTime Date Start Date
completedDate Date Completed Date
renderDuration Long Task render duration
userName String User name
producer String producer
taskLevel Byte Task level
taskUserLevel Integer Task level of user
taskLimit Integer Task node limit
taskOverTime Long Task timeout reminder time
outputFileName String Output file name
munuTaskId String Dispatch id
layerParentId String About maya task，parent id
cgId Integer Task type 2001/maya，2000/max
taskKeyValueVo Object Task keyword
userAccountConsume Bigdecimal User account consume
couponConsume Bigdecimal Coupon consume
isOpen Byte Whether the front-end expansion button is expanded or not
taskType String Task type Preprocessing, Render photon, Render picture
renderCamera String Render camera
cloneParentId Integer Clone parent id
cloneOriginalId Integer Clone original id
shareMainCapital Byte Whether to Share Main Account Assets (0：no 1：yes)
taskRam Integer Task render memory
respRenderingTaskList List\<TaskInfo> Child tasks of the open task Structure the same of this object
layerName String Layer name
taskTypeText String Task type text photon/picture

Example of request：

task_info = api.query.task_info(task_ids_list=[14400249])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "pageCount": 1,
        "pageNum": 1,
        "total": 1,
        "size": 100,
        "items": [
            {
                "sceneName": "test_no_randerman_175.hip",
                "id": 14400249,
                "taskAlias": "2W14400249",
                "taskStatus": 25,
                "statusText": "render_task_status_25",
                "preTaskStatus": null,
                "preStatusText": null,
                "totalFrames": 1,
                "abortFrames": 0,
                "executingFrames": 0,
                "doneFrames": 1,
                "failedFrames": 0,
                "framesRange": "/out/geometry110-200[1]",
                "projectName": "analysis_multi_project_empty_placeholder",
                "renderConsume": 0.0,
                "taskArrears": 0.0,
                "submitDate": 1577765849000,
                "startTime": 1577765851000,
                "completedDate": 1577766104000,
                "renderDuration": 13,
                "userName": "ding625yutao",
                "producer": "丁玉涛",
                "taskLevel": 81,
                "taskUserLevel": 0,
                "taskLimit": 1,
                "taskOverTime": 43200,
                "overTimeStop": 86400,
                "userId": 100150764,
                "outputFileName": "14400249_test_no_randerman_175",
                "munuTaskId": "2019123100841",
                "munuTaskIds": "2019123100841",
                "layerParentId": 0,
                "cgId": 2004,
                "userAccountConsume": 0.0,
                "couponConsume": 0.039,
                "qyCouponConsume": null,
                "isOpen": 0,
                "taskType": "GopRender",
                "renderCamera": "",
                "cloneParentId": 0,
                "cloneOriginalId": 0,
                "shareMainCapital": 0,
                "taskRam": 64,
                "respRenderingTaskList": null,
                "layerName": "",
                "taskTypeText": null,
                "locationOutput": "C:/RenderFarm/Download",
                "isDelete": 1,
                "channel": 1,
                "remark": "",
                "labels": "{}",
                "isOverTime": 0,
                "taskKeyValueVo": {
                    "tiles": null,
                    "allCamera": null,
                    "renderableCamera": null
                },
                "waitingCount": null,
                "stopType": 0
            }
        ]
    },
    "serverTime": 1578046630345,
    "requestId": "py6RCN-VGFzay1TZXJ2aWNlMDc-1578046630330"
}

Add a custom label

Interface path： /api/render/project/add

Request parameter：

Parameter Type Necessary Description Memo
new_name String N Label name
status Integer N Lable status 0: on, 1: off, default is 1

Return parameter：default

Example of request：

task_info = api.tag.add_label(new_name="test_tag4", status=0)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Delete custom label

Interface path： /api/render/project/delete

Request parameter：

Parameter Type Description Memo
del_name String Label name

Return parameter：default

Example of request：

delete_label_name = api.tag.delete_label(del_name="test_tag2")

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1535957894211
}

Get the project name

Interface path： /api/render/project/getList

Request parameter：No

Return parameter：

Parameter Type Description Memo
projectNameList List Project name list
Object.projectName String Project name
Object.projectId Integer Project id

Example of request：

label_list = api.tag.get_label_list()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "projectNameList": [
            {
                "projectId": 3671,
                "projectName": "myLabel"
            }
        ]
    },
    "serverTime": 1546998557770
}

Get the project name(Control by flag)

Interface path:  /api/render/project/list

Request parameter：

Parameter Type Necessary Description Memo
flag int N 0:Check the items under this account;
1:Check the items under this account and the main account;
2:Query associated with all items (all items under the same main account);		 default: 0

Return parameter：

Parameter Type Description Memo
projectNameList List\<Object> project list
Object.projectName String project name
Object.projectId Integer project id

Example of request：

new_projects = api.tag.get_list(flag=0)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "projectNameList": [
            {
                "projectId": 3671,
                "projectName": "myLabel"
            }
        ]
    },
    "serverTime": 1546998557770
}

Add a task label

Interface path: /api/render/handle/addTaskLabel

Request parameter：

Parameter Type Necessary Description Memo
tag string Y task tag
task_ids list[int] Y task id list

Return parameter：No

Example of request：No

tag = api.tag.add_task_tag(tag="test_tag", task_ids=[29445045, 29435295])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 15942751740441
}

Delete task label

Interface path: /api/render/task/deleteTaskLabel

Request parameter：

Parameter Type Description Memo
tag_ids list[int] Delete the task tag ID

Return parameter：No

Example of request：No

del_tag = api.tag.delete_task_tag(tag_ids=[21205])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 15942760110461
}

Obtain the supported rendering software

Interface path：/api/render/plugin/querySoftwareList

Request parameter：No

Return parameter：

Parameter Type Description Memo
isAutoCommit Integer Choose if submit automatically or not
renderInfoList List\<Software> Renderer version list
defaultCgId Integer Default renderer ID

Software

Parameter Type Description Memo
cgId Integer Render software ID
cgName String Render software name
cgType String Render file suffix support
iconPath String Rendering software icon address
isNeedProjectPath Integer
isNeedAnalyse Integer Need to analyze
isSupportLinux Integer Indicates if linux is supported or not

Example of request：

support_software = api.query.supported_software()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "isAutoCommit": 2,
        "renderInfoList": [
            {
                "cgId": 2000,
                "cgName": "Maya",
                "cgType": "ma;mb",
                "iconPath": "/img/softimage/maya.png",
                "isNeedProjectPath": 1,
                "isNeedAnalyse": 1,
                "isSupportLinux": 1
            },
            {
                "cgId": 2001,
                "cgName": "3ds Max",
                "cgType": "max",
                "iconPath": "/img/softimage/max.png",
                "isNeedProjectPath": 1,
                "isNeedAnalyse": 1,
                "isSupportLinux": 0
            },
            {
                "cgId": 2004,
                "cgName": "Houdini",
                "cgType": "hip;hipnc;hiplc",
                "iconPath": "/img/softimage/houdini.png",
                "isNeedProjectPath": 2,
                "isNeedAnalyse": 1,
                "isSupportLinux": 1
            },
            {
                "cgId": 2005,
                "cgName": "Cinema 4D",
                "cgType": "c4d",
                "iconPath": "/img/softimage/cinema-4D.png",
                "isNeedProjectPath": 1,
                "isNeedAnalyse": 1,
                "isSupportLinux": 0
            },
            {
                "cgId": 2007,
                "cgName": "Blender",
                "cgType": "blend",
                "iconPath": "/img/softimage/blender.png",
                "isNeedProjectPath": 1,
                "isNeedAnalyse": 1,
                "isSupportLinux": 0
            },
            {
                "cgId": 2008,
                "cgName": "VR Standalone",
                "cgType": "vrscene",
                "iconPath": "/img/softimage/VR-standalone.png",
                "isNeedProjectPath": 3,
                "isNeedAnalyse": 2,
                "isSupportLinux": 0
            },
            {
                "cgId": 2012,
                "cgName": "KeyShot",
                "cgType": "bip",
                "iconPath": "/img/softimage/keyshot.png",
                "isNeedProjectPath": 2,
                "isNeedAnalyse": 1,
                "isSupportLinux": 0
            },
            {
                "cgId": 2013,
                "cgName": "Clarisse",
                "cgType": "project;render",
                "iconPath": "/img/softimage/clarisse.png",
                "isNeedProjectPath": 3,
                "isNeedAnalyse": 1,
                "isSupportLinux": 1
            }
        ],
        "defaultCgId": 2001
    },
    "serverTime": 1578048938715,
    "requestId": "W12mkM-VGFzay1TZXJ2aWNlMDc-1578048938685"
}

Obtain supported rendering software plugins

Interface path：/api/render/plugin/querySoftwareDetail

Request parameter：

Parameter Type Necessary Description Memo
name String Y Render software ID

Return parameter：

Parameter Type Description Memo
cgPlugin List\<Plugin> Supported plugin list
cgVersion List\<Soft Version> Supported software list

Plugin：

Parameter Type Description Memo
cvId Integer Rendering software version ID (Soft Version.id)
pluginName String Plugin name
pluginVersions List\<Plugin Version> Plugin version list

PluginVersion

Parameter Type Description Memo
pluginId Integer Plugin version ID
pluginName String Plugin name
pluginVersion String Plugin version

SoftVersion：

Parameter Type Description Memo
id Integer Render software version ID
cgId Integer Render software ID
cgName String Render software name
cgVersion String Render software version

Example of request：

support_software_plugin = api.query.supported_plugin(name='maya')

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "isAutoCommit": 2,
        "renderInfoList": [
            {
                "cgId": 2000,
                "cgName": "Maya",
                "cgType": "ma;mb",
                "iconPath": "/img/softimage/maya.png",
                "isNeedProjectPath": 3,
                "isNeedAnalyse": 1,
                "isSupportLinux": 1
            }
        ],
        "defaultCgId": 2001
    },
    "serverTime": 1535973558961
}

New user rendering environment configuration

Interface path：/api/render/plugin/addUserPluginConfig

Request parameter：

Parameter Type Necessary Description Memo
render_env Dict Y Render environment configuration Detailed parameters refer to

render_env：

Parameter Type Necessary Description Memo
cgId Integer Y Render software ID Soft Version.cgId
cgName String Y Render software name Soft Version.cgName
cgVersion String Y Render software version Soft Version.cgVersion
renderLayerType Integer N Maya render Type
editName String Y render environment custom name
renderSystem Integer Y Render system 0 linux, 1 windows
pluginIds List\<Integer> Y render plugin list Plugin Version.plugin Id
projectPath String N Engineering path

Return parameter：

Parameter Type Description Memo
editName String render environment custom name

Example of request：

env = {
    "cgId": 2000,
    "cgName": "Maya",
    "cgVersion": "2020",
    "renderLayerType": 0,
    "editName": "testRenderEnv",
    "renderSystem": "0",
    "pluginIds": [1166]
}
add_user_env = api.env.add_render_env(render_env=env)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
		"editName": "testRenderEnv"
	},
    "serverTime": 1535957894211
}

Adjust user render environment configuration

Interface path：/api/render/plugin/editUserPluginConfig

Request parameter：

Parameter Type Description Memo
render_env Dict Y Render environment configuration Detailed parameters refer to

render_env：

Parameter Type Necessary Description Memo
cgId Integer Y Render software ID Soft Version.cgId
cgName String Y Render software name Soft Version.cgName
cgVersion String Y Render software version Soft Version.cgVersion
renderLayerType Integer N Maya render Type
editName String Y render environment custom name
renderSystem Integer Y Render system 0 linux, 1 windows
pluginIds List Y render plugin list Plugin Version.plugin Id
projectPath String N Engineering path

Return parameter：default

Example of request：

update_env = {
    "cgId": 2000,
    "cgName": "Maya",
    "cgVersion": "2020",
    "renderLayerType": 0,
    "editName": "testRenderEnv",
    "renderSystem": "0",
    "pluginIds": []
}
update_user_env = api.env.update_render_env(render_env=update_env)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1536027063801
}

Delete user render environment configuration

Interface path: /api/render/plugin/deleteUserPluginConfig

Request parameter：

parameter Type Necessary Description Memo
edit_name String Y render environment custom name

Return parameter：default

Example of request：

delete_user_env = api.env.delete_render_env(edit_name="testRenderEnv")

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1536027063801
}

Set up default render environment configuration

Interface path：/api/render/plugin/setDefaultUserPluginConfig

Request parameter：

parameter Type Necessary Description Memo
edit_name String Y render environment custom name

Return parameter：default

Example of request：

set_default_user_env = api.env.set_default_render_env(edit_name="testRenderEnv")

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1536027063801
}

Obtain user render environment configuration

Interface path：/api/render/plugin/getUserPluginConfig

Request parameter：

Parameter Type Description Memo
name String N Rendering software name cg_names and name must fill in one
cg_names List\ N 渲染软件名列表 cg_names and name must fill in one
os_name Integer N 选择操作系统 0:Linux，1:windows,默认1

Return parameter: List<RenderEnv>

Parameter Type Description Memo
cgId Integer Render software ID
editName String render environment custom name
cgName String Render software name
cgVersion String Render software version
osName Integer render environment system 0：Linux，1：windows
renderLayerType Integer
isDefault Integer Check if it is the default configuration 0 Not default configuration 1 Is default configuration
respUserPluginInfoVos List\<Plugin Version> render environment plugin list

Example of request：

user_render_config = api.env.get_render_env(name='houdini')

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": [
        {
            "cgId": 2004,
            "editName": "175",
            "cgName": "Houdini",
            "cgVersion": "17.5",
            "osName": 1,
            "renderLayerType": 0,
            "isDefault": 0,
            "projectPath": "",
            "isMainUserId": 1,
            "respUserPluginInfoVos": [
                {
                    "pluginId": 5304,
                    "pluginName": "renderman",
                    "pluginVersion": "renderman 22.6"
                }
            ]
        },
        {
            "cgId": 2004,
            "editName": "pianwan",
            "cgName": "Houdini",
            "cgVersion": "17.5",
            "osName": 1,
            "renderLayerType": 0,
            "isDefault": 0,
            "projectPath": "",
            "isMainUserId": 1,
            "respUserPluginInfoVos": []
        },
        {
            "cgId": 2004,
            "editName": "houdini_test",
            "cgName": "Houdini",
            "cgVersion": "17.5",
            "osName": 0,
            "renderLayerType": 0,
            "isDefault": 0,
            "projectPath": "",
            "isMainUserId": 1,
            "respUserPluginInfoVos": []
        },
        {
            "cgId": 2004,
            "editName": "16.5",
            "cgName": "Houdini",
            "cgVersion": "16.5",
            "osName": 1,
            "renderLayerType": 0,
            "isDefault": 0,
            "projectPath": "",
            "isMainUserId": 1,
            "respUserPluginInfoVos": []
        }
    ],
    "serverTime": 1578282315348,
    "requestId": "23IhQf-VGFzay1TZXJ2aWNlMDQ-1578282315343"
}

Task Progress (Only support Max )

Interface path：/api/render/handle/loadTaskProcessImg

Request parameter：

Parameter Type Necessary Description Memo
task_id Integer Y Task ID required
frame_type Integer N Frame type 2：photon，5：picture Without transmission, the background will dynamically return the results according to the stage of the rendering task

Return parameter：

Parameter Type Description Memo
width Integer Image resolution width
height Integer Image resolution height
block Integer Block number
isRenderPhoton Boolean Is render photon True:task is render photon
currentTaskType String Task render stage Render: render picture RenderPhoton: render photon
sceneName String Scene name+camera name
startTime String Task start time
endTime String Task end time
grabInfo List\<List\<dict>> Block frame info

Block frame info：grabInfo

Parameter Type Description Memo
startTime String Start time
endTime String End time
frameStatus String Frame status
isMaxPrice String Is max picture
feeAmount String Fee amount
couponFee String Coupon fee
frameIndex String Frame number
frameBlock String Block number
framePercent String Frame render percent
frameUsed String Frame render time consumed
frameEst String Predicted Remaining Time for Frame Rendering
renderInfo String Frame Rendering Progress Information
grabUrl String Frame Rendering Schedule Connection Address

Example of request：

task_processing_img = api.query.get_task_processing_img(task_id=14470635, frame_type=2)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "isRenderPhoton": true,
        "completedTime": "2020-01-03 10:02:55",
        "currentTaskType": "RenderPhoton",
        "sceneName": "翻新就沙发.max-Camera001",
        "grabInfo": [
            [
                {
                    "couponFee": "1.04",
                    "frameIndex": "0",
                    "renderInfo": "",
                    "frameBlock": null,
                    "frameEst": "0",
                    "grabUrl": "/mnt/output/d2_1/small_pic/100033000/100033433/14470635/RenderPhoton_2020010200306_0_rayvision0000[-]tga.jpg",
                    "feeAmount": "0.00",
                    "frameUsed": "174",
                    "frameStatus": "4",
                    "framePercent": "100",
                    "isMaxPrice": "0",
                    "startTime": "2020-01-03 09:57:18",
                    "endTime": "2020-01-03 10:00:12"
                }
            ]
        ],
        "width": 700,
        "block": 1,
        "startTime": "2020-01-02 09:35:51",
        "height": 518
    },
    "serverTime": 1578299393862,
    "requestId": "qELLr0-VGFzay1TZXJ2aWNlMDc-1578299393837"
}

Task Setting Of Over Time Stop

Interface path： /api/render/handle/setTaskOverTimeStop

Request parameter：

Parameter Type Necessary Description Memo
task_id_list List\<Integer> Y Task ID required
overtime Long Y Time of Task stop Required,unit:second

Example of request：

set_task_overtime = api.task.set_task_overtime_top(task_id_list=[14684405], overtime=60)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": "SUCCESS",
    "serverTime": 1578308287155,
    "requestId": "8VNTma-VGFzay1TZXJ2aWNlMDc-1578308286842"
}

Task thumbnail

Interface path：/api/render/handle/loadingFrameThumbnail

Request parameter：

Parameter Type Necessary Description Memo
frame_id Integer Y Frame ID This can be obtained through the "Obtain the task rendering frame details" interface
frame_status Integer N Frame status A value of 4 means complete, only thumbnails are available when completed

Example of request：

frame_thumbnall = api.query.get_frame_thumbnall(frame_id=230772361)

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": "SUCCESS",
    "serverTime": 1578308287155,
    "requestId": "8VNTma-VGFzay1TZXJ2aWNlMDc-1578308286842"
}

Get Raysync transmission message

Interface path： /api/render/transfer/getServerInfo

Request parameter：No

Example of request：

transfer_server_msg = api.query.get_transfer_server_msg()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "clientVersion": "3.2.8.2",
        "protocolVersion": "3.2.8.2",
        "raysyncTransfer": {
            "serverIp": "127.0.0.1",
            "serverPort": 2121,
            "proxyIp": "42.123.110.38",
            "proxyPort": 32001,
            "sslPort": 2443,
            "port": 2442
        }
    },
    "serverTime": 1565678980735,
    "requestId": "YenJW9-1565678980088"
}

Get Raysync authentication key

Interface path：/api/render/user/getRaySyncUserKey

Request parameter：No

Example of request：

raysync_user_key = api.query.get_raysync_user_key()

Example of return：

{
	"version": "1.0.0",
	"result": true,
	"message": "success",
	"code": 200,
	"data": {
		"channel": 2,
		"platform": 2,
		"signature": "rayvision2017",
		"version": "1.0.0",
		"userKey": "5394a44e890557d8d937b92086482dab",
		"id": 1868599,
		"userName": "wsh_12345",
		"zone": 1,
		"phone": "183160224171",
		"email": "testwangshunhui@rayvision",
		"loginTime": 1565682011157,
		"infoStatus": 0,
		"accountType": 2,
		"shareMainCapital": 0,
		"subDeleteTask": 0,
		"subDeleteCapital": 1,
		"useMainBalance": 0,
		"downloadDisable": 0,
		"raySyncUserKey": "40d59041f72809ffaa16146a36780595666c681e"
	},
	"serverTime": 1565682019430,
	"requestId": "4lkn0I-1565682010026"
}

Full Speed Render

Interface path： /api/render/handle/fullSpeedRendering

Request parameter：

Parameter Type Necessary Description Memo
task_id_list List\<Integer> Y Yes Task id

Example of request：

full_speed_render = api.task.full_speed(task_id_list=[13652193])

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": "成功",
    "serverTime": 1578311448826,
    "requestId": "X81MN5-VGFzay1TZXJ2aWNlMDQ-1578311448620"
}

Get transport configuration

Interface path： /api/render/transfer/getConfig

Request parameter：No

Return parameter：

Parameter Type Description Memo
inputBid String Input bid
outputBid String output bid
configBid String config bid
parentInputBid String Input Bid corresponds to the main account
resqEngines Object[] Engine configuration
engineName String Engine name
checkServer String Check server
checkPort String Check port
checkEnable String Check for availability
checkExcludType String Detect exception file type, separate
automaticCheck number Automatic detection and switching of line 1 is 0: No
isDefault number 1: Yes; 0: No, default 1
resqEngineAccounts Object[] aspera account
bid String aspera input bid
name String aspera username
password String aspera password
respTaskEngineLines Object[] Engine list
name String Line name
server String Line server IP
port String Line server port
isDefault Number 1: Yes; 0: No, default 1
lineId Number ID of line tables
type Number Line type 1. Special line 0. General line
subUserOutputBids Object[] Collection outputbid subaccount
userId String ID of subaccount
outputBid String outputBid

Example of request：

transfer_config = api.transmit.get_transfer_config()

Example of return：

{
    "version": "1.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": {
        "inputBid": "10202",
        "outputBid": "20202",
        "configBid": "30201",
        "parentInputBid": null,
        "resqEngines": [
            {
                "resqEngineAccounts": [
                    {
                        "bid": "20202",
                        "name": "20202",
                        "password": "xB9CWAML1qd+k1X9prYHheQUAtZ0hcpmJHxe7mfVw9Q="
                    }
                ],
                "respTaskEngineLines": [
                    {
                        "name": "Aspera_main",
                        "server": "10.60.197.79",
                        "port": "10221",
                        "isDefault": 1,
                        "lineId": 123,
                        "type":1
                    }
                ],
                "engineName": "trtt",
                "automaticCheck": 1,
                "checkServer": "677",
                "checkPort": "8888",
                "checkEnable": "1",
                "checkExcludType": "88",
                "isDefault": 0
            },
            {
                "resqEngineAccounts": null,
                "respTaskEngineLines": [
                    {
                        "name": "raysync_main",
                        "server": "10.60.197.79",
                        "port": "10200",
                        "isDefault": 1,
                        "lineId": 121
                    }
                ],
                "engineName": "RaySync",
                "automaticCheck": 0,
                "checkServer": "10.60.196.151",
                "checkPort": "10100",
                "checkEnable": "0",
                "checkExcludType": "tx",
                "isDefault": 1
            },
            {
                "resqEngineAccounts": [
                    {
                        "bid": "30201",
                        "name": "30201",
                        "password": "ACz/0lNMCgyq/7WjR0QGpaXmR0/Xb0//6UaMn/s8QN4="
                    }
                ],
                "respTaskEngineLines": [
                    {
                        "name": "Aspera_main",
                        "server": "10.60.197.79",
                        "port": "10221",
                        "isDefault": 1,
                        "lineId": 123
                    }
                ],
                "engineName": "Aspera",
                "automaticCheck": 0,
                "checkServer": "test2.raysync.cn",
                "checkPort": "8888",
                "checkEnable": "0",
                "checkExcludType": "tx",
                "isDefault": 0
            }
        ],
        "subUserOutputBids": [
            {
                "userId": "119784",
                "outputBid": "10202"
            }
        ]
    },
    "serverTime": 1587380763325,
    "requestId": "K7wW6L-QmV5b25kTGVlZGVNYWNCb29rLVByby5sb2NhbA-1587380762156"
}

Upload the task profile

Interface path： /api/render/submit/taskJsonFile

Request parameter：

Parameter Type Necessary Description Memo
task_id Integer Y task id
content String Y File values in jsonformat
file_name String N file name default“task.json”

Return parameter：No

Example of request：

start_task = api.task.start_task(task_param_list=[13798105])

Example of return：

{
    "version": "2.0.0",
    "result": true,
    "message": "success",
    "code": 200,
    "data": null,
    "serverTime": 1589532607599,
    "requestId": null
}

Log Management

Warning

Make sure local Python environment and PIP are available before use.

Demo

rayvision_log An example is given as follows: demo

import logging
from rayvision_log import init_logger

package_name = 'mylog'
init_logger(package_name)
logging.info('test')

Set the log path

  1. Default path

Mac OS X:

~/Library/Logs/<AppName>/Logs/<username>/<hostname>.log

Unix:

~/.cache/<AppName>/log/Logs/<username>/<hostname>.log

Window:

C:Users<username>AppDataLocal<AppAuthor><AppName>Logs<username><hostname>.log
  1. Customized path
  • Define parameter： RAYVISION_LOG_ROOT = "xxxx"
  • Set RAYVISION_LOG_ROOT as environment variable
  • The log files will be saved in RAYVISION_LOG_ROOT

Log interface

Basic logging setup.

rayvision_log.core.get_default_log_config()

Get the default logging configuration.

Returns:The default logging configuration.
Return type:dict
rayvision_log.core.init_logger(app_name)

Initialize logging with our default configuration.

An easier interface for artists to use to create loggers in their packages and applications. Any application that uses this will use the default logging configuration.

Examples

>>> import logging
>>> from rayvision_log import init_logger
>>> app_name = "rayvision_api"
>>> init_logger(app_name)
>>> LOG = logging.getLogger(app_name)
Parameters:app_name (str) – The application or package name for which to create a logger.
rayvision_log.core.set_up_logger(app_name, log_config, use_orginal=False)

Set up loggers based on given name and configuration.

Example

>>> app_name = "rayvision_api"
>>> log_config = {
                    formatters: {
                        file: {
                            format: '%(asctime)s [%(levelname)s] %(name)s: %(message)s'
                        }
                    },
                    handlers: {
                        file: {
                            class: concurrent_log_handler.ConcurrentRotatingFileHandler
                        }
                    }
                }
Parameters:
  • app_name (str) – Name of the application.
  • log_config (dict) – The configuration of the logger.

References

https://pypi.org/project/ConcurrentLogHandler/

rayvision_log.core.update_config(config)

Some python2 versions use native logging

Parameters:config (dict) – logging config
Returns:logging config.
Return type:dict

Note

Mainly to verify the analysis results

Task Information Verification

Mainly to check task information (task_info) and uploading (upload) asset information. Whether it is automated analysis using the SDK or user-defined local analysis, the result must be verified in this step.

Check the analysis results.

Check the analysis of the task information and upload asset information.

class rayvision_api.task.check.RayvisionCheck(api, analyze=None, workspace=None)

Bases: object

Check the analysis results.

check_analyze(analyze, workspace, is_cover=True)

Initializes the configuration file information.

check_error_warn_info(language='0')

Check the error in the analysis scenario.

According to the status code of the analyzed error information, the API interface is called to obtain detailed error information and solutions, and the warning information is printed out, and the number of error information is recorded.

Parameters:
  • language (str) – The language that identifies the details of the
  • obtained, 0 (error) – Chinese (default) 1: English.
Returns:

List of detailed descriptions of errors.
Return type:

list
static check_path(tmp_path)

Check if the path exists.

check_task_info(task_info)

Check and add the required parameter information.

check_workspace(workspace)

Check the working environment.

Parameters:workspace (str) – Workspace path.
Returns:Workspace path.
Return type:str
execute(task_json, upload_json='', asset_json='', is_cover=True, only_id=True)

Check asset configuration information.

Check the scene for problems and filter unwanted configuration information. :param is_cover: Whether the updated json file overwrites the file under the original path,

by default ‘True’.
get_json_info(data)
is_scene_have_error()

Check the scene.

Determine whether the scene has an error based on the number of serious errors.

Raises:RayvisionError – There is a problem with the scene.
write(only_id=True)

Check and write to a json file.

Upload

1. Upload file cutting

Some upload.json files may have up to hundreds of thousands of resources, at this time you may need to cut the upload file。
def cutting_upload(upload_path, max_resources_number=None, after_cutting_position=None):
    """Cut upload.json according to the number of custom files.

    Args:
        upload_path (str): upload.json absolute path.
        max_resources_number (int): Maximum number of resources in each upload file.
        after_cutting_position (str): save location of upload file generated after cutting.

    Returns:
        list: Absolute path of all upload files generated after cutting, excluding original upload files.
            e.g.:
                ['D:\\test\\test_upload\\1586250829\\upload_1.json',
                'D:\\test\\test_upload\\1586250829\\upload_2.json']

    """
Use example:
from rayvision_sync.utils import cutting_upload
upload_pool = cutting_upload(r"D:\test\test_upload\1586250829\upload.json", max_resources_number=800)

2. Multi-thread upload

Multiple uploads can use multi-threaded concurrent upload
def multi_thread_upload(self, upload_pool, thread_num=10):
    """muti thread upload resource.

    Args:
        upload_pool (list or tuple): Store a list or ancestor of uploaded files.
        thread_num (int): Number of threads, 10 threads are enabled by default.
    """
Use example：
from rayvision_api import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload

api = RayvisionAPI(access_id="xxxxx",
                   access_key="xxxxx",
                   domain="task.renderbus.com",
                   platform="2")

UPLOAD = RayvisionUpload(api)
UPLOAD.multi_thread_upload(upload_pool, thread_num=20)

3. Use thread pool to control upload

Thread pool can also be used for concurrent uploads
def thread_pool_upload(self, upload_pool, pool_size=10):
    """Thread pool upload.

    Args:
        upload_pool (list or tuple): store a list or ancestor of uploaded files.
        pool_size (int): thread pool size, default is 10 threads.

    """
    pool = ThreadPoolExecutor(pool_size)
    for i in range(len(upload_pool)):
        pool.submit(self.upload_asset, upload_pool[i])
    pool.shutdown(wait=True)
Use example：
from rayvision_api import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload

api = RayvisionAPI(access_id="xxxxx",
                   access_key="xxxxx",
                   domain="task.renderbus.com",
                   platform="2")

UPLOAD = RayvisionUpload(api)
UPLOAD.thread_pool_upload(upload_pool, pool_size=20)

4. Only upload resources in upload

Users who upload upload resources only need to log in
def upload_asset(self, upload_json_path, max_speed=None, is_db=True):
    """Run the cmd command to upload asset files.

    Args:
        upload_json_path (str): Path to the upload.json file.
        max_speed (str): Maximum transmission speed, default value
            is 1048576 KB/S.
        is_db (bool): Whether to produce local database record upload file.

    Returns:
        bool: True is success, False is failure.

    """
Use example：
from rayvision_api import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload

api = RayvisionAPI(access_id="xxxxx",
                   access_key="xxxxx",
                   domain="task.renderbus.com",
                   platform="2")
                   
UPLOAD = RayvisionUpload(api)
UPLOAD.upload_asset(r"D:\test\test_upload\1586250829\upload.json")

5. Only upload the json configuration file generated by analysis

def upload_config(self, task_id, config_file_list, max_speed=None):
    """Run the cmd command to upload configuration profiles.

    Args:
        task_id (str): Task id.
        config_file_list (list): Configuration file path list.
        max_speed (str): Maximum transmission speed, default value
            is 1048576 KB/S.

    Returns:
        bool: True is success, False is failure.

    """
Use example:
from rayvision_api import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload

api = RayvisionAPI(access_id="xxxxx",
                   access_key="xxxxx",
                   domain="task.renderbus.com",
                   platform="2")

CONFIG_PATH = [
    r"C:\workspace\work\tips.json",
    r"C:\workspace\work\task.json",
    r"C:\workspace\work\asset.json",
    r"C:\workspace\work\upload.json",
]

UPLOAD = RayvisionUpload(api)
UPLOAD.upload_config("5165465", CONFIG_PATH)

6. Upload the configuration file first and then automatically upload the resource according to the upload file (task id must be)

def upload(self, task_id, task_json_path, tips_json_path, asset_json_path,
           upload_json_path, max_speed=None):
    """Run the cmd command to upload the configuration file.

    Args:
        task_id (str, optional): Task id.
        task_json_path (str, optional): task.json file absolute path.
        tips_json_path (str, optional): tips.json file absolute path.
        asset_json_path (str, optional): asset.json file absolute path.
        upload_json_path (str, optional): upload.json file absolute path.
        max_speed (str): Maximum transmission speed, default value
            is 1048576 KB/S.

    Returns:
        bool: True is success, False is failure.

    """
Use example:
from rayvision_api import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload

api = RayvisionAPI(access_id="xxxxx",
                   access_key="xxxxx",
                   domain="task.renderbus.com",
                   platform="2")

CONFIG_PATH = [
    r"C:\workspace\work\tips.json",
    r"C:\workspace\work\task.json",
    r"C:\workspace\work\asset.json",
    r"C:\workspace\work\upload.json",
]

upload_obj = RayvisionUpload(api)
upload_obj.upload("5165465", **CONFIG_PATH)

7. append_to_upload: Custom upload.json file

from rayvision_api import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload
from rayvision_api.utils import append_to_upload

api = RayvisionAPI(access_id="xxxxx",
                   access_key="xxxxx",
                   domain="jop.foxrenderfarm.com",
                   platform="2")
UPLOAD = RayvisionUpload(api)

# 1. Can accept the list, the list can be passed in the folder path or file path
custom_info_to_upload = [
    r"E:\fang\ass_test\static_ass.ass",
    r"E:\fang",
    r"D:\houdini\CG file\F"
]
# 2.You can also receive a single string
# custom_info_to_upload = r"D:\houdini\CG file\katana_file"

# Need to specify an existing upload.json path
append_to_upload(custom_info_to_upload, r"D:\test\upload.json")
UPLOAD.upload_asset(r"D:\test\upload.json")

8. Customize upload service address and transport engine selection

Upload service address generally does not need to be modified, if the line is not good also support custom modification.

1. The following upload interface supports custom server addresses and transport engine Settings

Transport engine support: “aspera” and “raysync”

  • upload_asset

    UPLOAD.upload_asset(r"D:\test\upload.json", engine_type='aspera', server_ip="45.251.92.16", server_port="12121")

  • upload_config

    CONFIG_PATH = [
    r"C:\workspace\work\tips.json",
    r"C:\workspace\work\task.json",
    r"C:\workspace\work\asset.json",
    r"C:\workspace\work\upload.json",
]
UPLOAD.upload_config(task_id="5165465",
                     config_file_list=config_list,
                     server_ip="45.251.92.16",
                     server_port="12121")

  • upload

    UPLOAD.upload(task_id="41235091",
                  engine_type='aspera',
                  server_ip="45.251.92.16",
                  server_port="12121",
                  task_json_path=r"C:\workspace\work\task.json",
                  tips_json_path=r"C:\workspace\work\tips.json",
                  asset_json_path=r"C:\workspace\work\asset.json",
                  upload_json_path=r"C:\workspace\work\upload.json")

9. Upload file type (transmit_type)

The upload file is controlled by the parameter “transmit_type”, and the supported transmission file formats are: “upload_list” and “upload_json”.
    1. upload_list

    The content of the “upload_json_path” file specified by this upload mode (support txt and json files) can be a file absolute path or folder absolute path for each line. If it is a folder, all files in the folder will be uploaded.

    For Example:

    https://blog-tao625.oss-cn-shenzhen.aliyuncs.com/izone/blog/20201116160335.png

    1. upload_json

    The content of the “upload_json_path” file (json file) specified by this upload mode must follow a fixed format, and only files can be uploaded.

    例如:

    // upload.json
{
  "asset": [
    {
      "local": "D:/houdini/CG file/local/clarisse_test1.project", 
      "server": "/D/houdini/CG file/local/clarisse_test1.project"
    }
  ]
}

Download

1. The automatic download is completed with a single frame as the granularity rendering (task id must be)

    def auto_download(self, task_id_list=None, max_speed=None,
                      print_log=False, sleep_time=10,
                      download_filename_format="true",
                      local_path=None,
                      engine_type="aspera", server_ip=None, server_port=None):
        """Automatic download (complete one frame download).

        Wait for all downloads to update undownloaded records.

        Args:
            task_id_list (list of int): List of tasks ids that need to be
                downloaded.
            max_speed (str, optional): Download speed limit,
                The unit of 'max_speed' is KB/S,default value is 1048576 KB/S,
                means 1 GB/S.
            print_log (bool, optional): Print log, True: print, False: not
                print.
            sleep_time (int, optional): Sleep time between download,
                unit is second.
            download_filename_format: File download local save style,
                "true": tape task ID and scene name,
                "false" : download directly without doing processing.
            local_path (str): Download file locally save path,
                default Window system is "USERPROFILE" environment variable address splicing "renderfarm_sdk",
                Linux system is "HOME" environment variable address splicing "renderfarm_sdk".
            engine_type (str, optional): set engine type, support "aspera" and "raysync", Default "aspera".
            server_ip (str, optional): transmit server host,
                if not set, it is obtained from the default transport profile.
            server_port (str, optional): transmit server port,
                if not set, it is obtained from the default transport profile.

        Returns:
            bool: True is success.

        """
Use example
from rayvision_api import RayvisionAPI
from rayvision_sync.download import RayvisionDownload

api = RayvisionAPI(access_id="xxx",
                   access_key="xxx",
                   domain="task.renderbus.com",
                   platform="2")

download = RayvisionDownload(api)
download.auto_download([18164087], download_filename_format="false")

2. Taking task as the granularity, downloading starts when all frames in the task are rendered (task id must be)

    def auto_download_after_task_completed(self, task_id_list=None,
                                           max_speed=None, print_log=True,
                                           sleep_time=10,
                                           download_filename_format="true",
                                           local_path=None,
                                           engine_type="aspera", server_ip=None, server_port=None):
        """Auto download after the tasks render completed.

        Args:
            task_id_list(list of int): List of tasks ids that need to be
                downloaded.
            max_speed(str, optional): Download speed limit,
                The unit of 'max_speed' is KB/S,default value is 1048576 KB/S,
                means 1 GB/S.
            print_log(bool, optional): Print log, True: print, False: not
                print.
            sleep_time(int, optional): Sleep time between download,
                unit is second.
            download_filename_format: File download local save style,
                "true": tape task ID and scene name,
                "false" : download directly without doing processing.
            local_path (str): Download file locally save path,
                default Window system is "USERPROFILE" environment variable address splicing "renderfarm_sdk",
                Linux system is "HOME" environment variable address splicing "renderfarm_sdk".
            engine_type (str, optional): set engine type, support "aspera" and "raysync", Default "aspera".
            server_ip (str, optional): transmit server host,
                if not set, it is obtained from the default transport profile.
            server_port (str, optional): transmit server port,
                if not set, it is obtained from the default transport profile.

        Returns:
            bool: True is success.

        """
Use example
from rayvision_api import RayvisionAPI
from rayvision_sync.download import RayvisionDownload

api = RayvisionAPI(access_id="xxx",
                   access_key="xxx",
                   domain="task.renderbus.com",
                   platform="2")

download = RayvisionDownload(api)
download.auto_download_after_task_completed([18164087], download_filename_format="false")

3. User-defined download server directory structure download (task id is not required)

    def download(self, task_id_list=None,
                 max_speed=None, print_log=True,
                 download_filename_format="true",
                 local_path=None, server_path=None,
                 engine_type="aspera", server_ip=None, server_port=None):
        """Download and update the undownloaded record.

        Args:
            task_id_list (list of int): List of tasks ids that need to be
                downloaded.
            max_speed (str, optional): Download speed limit,
                The unit of ``max_speed`` is KB/S,default value is 1048576
                KB/S, means 1 GB/S.
            print_log (bool, optional): Print log, True: print, False: not
                print.
            download_filename_format: File download local save style,
                "true": tape task ID and scene name,
                "false" : download directly without doing processing.
            local_path (str): Download file locally save path,
                default Window system is "USERPROFILE" environment variable address splicing "renderfarm_sdk",
                Linux system is "HOME" environment variable address splicing "renderfarm_sdk",
            server_path (str or list): The user customizes the file structure to be downloaded from
                the output server, and all file structures are downloaded by default,
                example: "18164087_test/l_layer".
            engine_type (str, optional): set engine type, support "aspera" and "raysync", Default "aspera".
            server_ip (str, optional): transmit server host,
                if not set, it is obtained from the default transport profile.
            server_port (str, optional): transmit server port,
                if not set, it is obtained from the default transport profile.

        Returns:
            bool: True is success.

        """
Use example:
from rayvision_api import RayvisionAPI
from rayvision_sync.download import RayvisionDownload

api = RayvisionAPI(access_id="xxx",
                   access_key="xxx",
                   domain="task.renderbus.com",
                   platform="2")

download = RayvisionDownload(api)
download.download(download_filename_format="true", server_path="18164087_muti_layer_test/l_ayer2")

Maya

Analyse assets, save the result as a local json file. Before analysis, verify initial configuration info.

Clarisse

Analyse assets, save the result as a local json file. Before analysis, verify initial configuration info.

A interface for clarisse.

class rayvision_clarisse.analyse_clarisse.AnalyzeClarisse(cg_file, software_version, project_name=None, plugin_config=None, render_software='Clarisse', local_os=None, workspace=None, custom_exe_path=None, platform='2')

Bases: object

add_tip(code, info)

Add error message.

Parameters:
  • code (str) – error code.
  • info (str or list) – Error message description.
analyse(no_upload=False)

Analytical master method for clarrise.

analyse_cg_file()

Start analyse cg file.

Examples cmd command:

“D:/myproject/internal_news/rayvision_clarisse/rayvision_clarisse /tool/Analyze.exe” -cf “E:/copy/DHGB_sc05_zhuta_610-1570_v0102.project” -tj

“c:/workspace/work/10398483/task.json”
static check_local_os(local_os)

Check the system name.

Parameters:local_os (str) – System name.
Returns:str
static check_path(tmp_path)

Check if the path exists.

check_result()

Check that the analysis results file exists.

check_workspace(workspace)

Check the working environment.

Parameters:workspace (str) – Workspace path.
Returns:Workspace path.
Return type:str
gather_upload_dict()

Gather upload info.

Examples

{
“asset”: [
{
“local”: “E:/copy/muti_layer_test.ma”, “server”: “/E/copy/muti_layer_test.ma”

}

]

}

get_file_md5(file_path)

Generate the md5 values for the scenario.

print_info(info)

Print info by logger.

Parameters:info (str) – Output information.
print_info_error(info)

Print error info by logger.

Parameters:info (str) – Output information.
save_tips()

Write the error message to tips.json.

write_task_json()

The initialization task.json.

write_tips_info()

Write tips info.

writing_error_abort(error_code, info=None)

Collect error abort to tips_info.

Parameters:
  • error_code (str) – Error code.
  • info (None, str) – Default is None.

Houdini

Analyse assets, save the result as a local json file. Before analysis, verify initial configuration info.

RayvisionAnalyse

The core class for CG analysis, providing software verification. Automatically call corrsponding module to analyze cg scenes as per cg software.

JsonHandle

Functionality of reading/writing of json file and verification of part of data.

Exception management

Customized exception handling

Error message.

CG errors.

exception rayvision_utils.exception.exception.AnalyseFailError

Bases: rayvision_utils.exception.exception.AnalyzeError

Analyse Fail Error.

exception rayvision_utils.exception.exception.AnalyzeError

Bases: Exception

Analyze has a damage error.

exception rayvision_utils.exception.exception.CGExeNotExistError

Bases: rayvision_utils.exception.exception.AnalyzeError

No errors in CG boot.

exception rayvision_utils.exception.exception.CGFileNameIllegalError

Bases: rayvision_utils.exception.exception.AnalyzeError

CG File Name Illegal Error.

exception rayvision_utils.exception.exception.CGFileNotExistsError

Bases: rayvision_utils.exception.exception.AnalyzeError

CG file does not exist error.

exception rayvision_utils.exception.exception.CGFileZipFailError

Bases: rayvision_utils.exception.exception.AnalyzeError

CG file compression failed error.

exception rayvision_utils.exception.exception.CompressionFailedError

Bases: Exception

Compression failed error.

exception rayvision_utils.exception.exception.DecompressionFailedError

Bases: Exception

Unzip failed error.

exception rayvision_utils.exception.exception.FileNameContainsChineseError

Bases: rayvision_utils.exception.exception.AnalyzeError

File Name Contains Chinese Error.

exception rayvision_utils.exception.exception.GetCGLocationError

Bases: rayvision_utils.exception.exception.AnalyzeError

Error getting CG local path.

exception rayvision_utils.exception.exception.GetCGVersionError

Bases: rayvision_utils.exception.exception.AnalyzeError

Error getting CG version.

exception rayvision_utils.exception.exception.GetRendererError

Bases: rayvision_utils.exception.exception.AnalyzeError

Get renderer error.

exception rayvision_utils.exception.exception.MaxDamageError

Bases: rayvision_utils.exception.exception.AnalyzeError

Max has a damage error.

exception rayvision_utils.exception.exception.MaxExeNotExistError

Bases: rayvision_utils.exception.exception.AnalyzeError

There are no errors in the Max startup file.

exception rayvision_utils.exception.exception.MultiScatterAndVrayConfilictError

Bases: rayvision_utils.exception.exception.AnalyzeError

Multi scatter and vray Confilict error.

exception rayvision_utils.exception.exception.ProjectMaxVersionError

Bases: rayvision_utils.exception.exception.AnalyzeError

Project Max version error.

exception rayvision_utils.exception.exception.RayvisionAPIError(error_code, error, request)

Bases: rayvision_utils.exception.exception.RayvisionError

Raise RayVisionAPIError.

exception rayvision_utils.exception.exception.RayvisionError(error_code, error, *args, **kwargs)

Bases: Exception

Raise RayvisionError if something wrong.

class rayvision_utils.exception.exception.RayvisionHTTPErrorProcessor

Bases: urllib.request.HTTPErrorProcessor

Process HTTP error responses.

Inherit HTTPErrorProcessor in urllib2.

http_response(request, response)

Override the http_response method of HTTPErrorProcessor.

Process the response,when it is a bad Request,the corresponding exception is reported.

Parameters:
  • request (urllib2.Request) – Request object.
  • response (opener.open) – Response object.
Returns:

Abnormal response.
Return type:

Exception
exception rayvision_utils.exception.exception.RayvisonTaskIdError(error)

Bases: rayvision_utils.exception.exception.RayvisionError

Raise RayVisonTaskIdError.

exception rayvision_utils.exception.exception.VersionNotMatchError

Bases: rayvision_utils.exception.exception.AnalyzeError

Version not match error.

Handle tips messages and write them to tips.json.

class rayvision_utils.exception.tips.TipsInfo(save_path=None)

Bases: object

Handling errors encountered in the analysis.

add(key, *values)

Add tips message.

Parameters:
  • key (str) – TipsInfo code.
  • values (tuple) –

    TipsInfo message. e.g.:

    (‘Scene file no exists’, ‘Missing renderer’)
save_and_exit(path, exit_code=-1)

Save the prompt to the tips.json file and exit.

Parameters:
  • path (str) – The configuration information path path.
  • exit_code (int) – Exit code, default is -1.
save_tips(path=None)

Save the prompt to the tips.json file.

Parameters:path (str, optional) – The configuration information path path.
set_tips(key, value)

Set tips message.

Parameters:
  • key (str) – TipsInfo code.
  • value (str) – TipsInfo message.

Detailed parameter configuration

Clarisse Configuration

Analyze clarisse scene and save the output as task.json, asset.json, upload.json and tips.json.

1.task.json

File to save the analysis result of the scene, including scene name, cg software version, render settings, etc.

task.json example

{
    "scene_info_render": {
        "image_node": [
            {
                "frames": "0-50[1]",
                "renderable": "0",
                "output": "D:\\temp\\cam02",
                "format": "exr16",
                "LUT": "linear",
                "save_to_disk": "1",
                "name": "project://scene/cam02",
                "layers": [
                    {
                        "frames": "0-50[1]",
                        "renderable": "1",
                        "output": "D:\\temp\\cam02_layer02",
                        "format": "exr16",
                        "enable_deep_output": "1",
                        "save_to_disk": "1",
                        "enable_deep_output_path": "D:\\temp\\cam02_layer02_deep",
                        "name": "project://scene/cam02.cam02_layer02"
                    }
                ]
            }
        ]
    },
    "software_config":{
        "plugins":{},
        "cg_version":"clarisse_ifx_4.0_sp3",
        "cg_name":"Clarisse"
    },
    "task_info":{
        "task_stop_time":"259200",
        "frames_per_task":"1",
        "channel":"4",
        "task_id":"11022523",
        "project_name":"Project1",
        "platform":"2",
        "tiles":"1",
        "is_picture":"0",
        "project_id":"200953",
        "job_stop_time":"86400",
        "distribute_render_node":"3",
        "stop_after_test":"2",
        "clone_original_id":"",
        "ram":"64",
        "render_layer_type":"0",
        "test_frames":"000",
        "graphics_cards_num":"2",
        "edit_name":"",
        "pre_frames":"000",
        "input_project_path":"",
        "enable_layered":"1",
        "is_distribute_render":"0",
        "time_out":"43200",
        "tiles_type":"block",
        "user_id":"100150764",
        "cg_id":"2013",
        "input_cg_file":"E:/copy/DHGB_sc05_zhuta_610-1570_v0102.project",
        "os_name":"1",
    },
    "scene_info":{
        "image_node": [
            {
                "frames": "0-50[1]",
                "renderable": "0",
                "output": "D:\\temp\\cam02",
                "format": "exr16",
                "LUT": "linear",
                "save_to_disk": "1",
                "name": "project://scene/cam02",
                "layers": [
                    {
                        "frames": "0-50[1]",
                        "renderable": "1",
                        "output": "D:\\temp\\cam02_layer02",
                        "format": "exr16",
                        "enable_deep_output": "1",
                        "save_to_disk": "1",
                        "enable_deep_output_path": "D:\\temp\\cam02_layer02_deep",
                        "name": "project://scene/cam02.cam02_layer02"
                    }
                ]
            }
        ]
    }
}

task.json Parametric Interpretation

parameter type description example
software_config object environment(cg software, version and plugins, etc.) refer to software_config
task_info object render settings(priority frames, render range, etc.) refer to task_info
scene_info_render object analysis result(render node, output, etc.) refer to scene_info_render

software_config

parameter type description example
cg_name string software "Clarisse"
cg_version string software version "clarisse_ifx_4.0_sp3"
plugins object plugin{name, version} {}

task_info

parameter type Is it necessary description default example
graphics_cards_num string Y 1: open single card rendering 2: open dual card rendering "2" "2"
enable_layered string Y render layer mode,"0":off, "1":on "0" "1"
cg_id string Y software id."2013": Clarisse "2013"
ram string Y ram: 64 / 128 "64" "64"
os_name string Y Rendering machine operating system: "0":Linux; "1": Windows "1" "1"
render_layer_type string N render layer mode(only support maya): "0"：renderlayer方式 "1"：rendersetup方式 "0" "0"
is_distribute_render string N distributed render mode,"0":off, "1":on "0" "0"
input_cg_file string Y input file path "E:/copy/DHGB_sc05_zhuta_610-1570_v0102.project"
input_project_path string Y project path, could be empty " "
job_stop_time string Y Set the frame timeout time, will only affect the current frame, unit seconds "259200" "28800"
user_id string Y user id
pre_frames string Y Priority rendering (priority frames are not recommended to customize multiple individual frames) "000" "000: 1,3-4 [1]" means: Priority rendering first frame: No Priority rendering middle frame: No Priority rendering last frame: No Priority rendering custom frame: 1,3-4 [1]
platform string Y submit platform : "2": "www2", "3": "www3", "6": "www4", "21": "gpu", "2"
is_picture string Y "0: Effect Chart "1": Animation Chart "0" "0"
project_id string Y project id " " "200953"
project_name string Y project name " 0" "Project1"
channel string Y 1:Web local analysis (animation deduction); 2:web cloud analysis; 3:Rendering plugin submission； 4：API/SDK submission; 8：Animation plugin submission "4" "4"
tiles_type string Y "block, strip" "block" "block"
tiles string Y tile number, 1 for single node, greater than 1 for tiles rendering(multi-nodes) "1" "1"
distribute_render_node string N nodes number for distributed rendering "3" "3"
frames_per_task string Y frames per task "1" "1"
stop_after_test string Y "1":pause after priority render, "2":continue after priority render (default "2") "2" "2"
task_id string Y task id
task_stop_time string Y Large task timeout stops in unit seconds, "0" means unlimited "0" "86400"
time_out string Y Overtime reminder time, unit: sec "43200" "43200"
Note: Clarisse temporarily does not support distributed rendering (is_distribute_render) and tiled rendering (tiles)

scene_info_render

parameter type description example
image_node object Clarisse IFX includes all images in the scene and 3dlayer under the image, and clarisse BUiLDER includes all VariableRange in the scene and ImageNodeWrite under VariableRange. refer to scene_info_render.image_node

scene_info_render.image_node

parameter type description example
renderable string "0": do not open rendering,
“1”: open rendering (this is not the value in the scene,the platform is not open by default, the platform is notrecommended to directly render image and VariableRange)		 "0"
output string The output path of the current image in clarisse IFX, no output in clarisse BUiLDER The output path of the current image in clarisse IFX, no in clarisse BUiLDER "D:\temp\cam02"
format string The output format of the current image in clarisse IFX, optional value, none under clarisse BUiLDER "exr16"
LUT string The stringIFX manages the output color of the current image. Non-essential values, none under clarisse BUiLDER "linear"
save_to_disk string Whether to save the output of the current image in clarisse IFX, no under clarisse BUiLDER "1"
name string The name of the current image in clarisse IFX, the name of the current VariableRange in clarisse BUiLDER, and the path of the two in the scene "project://scene/cam02"
layers string IFX is the 3dlayer in the current image, the value is list, the value of list is dict, there are several layers of dict in the current image, there are several layers of dict, clarisse BUiLDER is the ImageNodeWrite in the current VariableRange, the value is list, The value of list is dict. How many ImageNodeWrites are in the current VariableRange, there are several dicts of ImageNodeWrites. See scene_info_render.image_node.layers object analysis scene_info_render.image_node.layers
frames string clarisse IFX is the frame range of the current image, clarisse BUiLDER is the value of the F or Frame variable of the current VariableRange "0-50[1]"

scene_info_render.image_node.layers

parameter type description example
frames string clarisse IFX is the current 3dlayer start frame and end frame, and clarisse BUiLDER is the coverage value of the ImageNodeWrite under the current VariableRange "0-50[1]"
renderable string "0": do not open rendering
“1”: open rendering		 "1"
output string The output path of the current layer in clarisse IFX, not under clarisse BUiLDER "D:\temp\cam02_layer02"
format string The output format of the current layer or ImageNodeWrite "exr16"
enable_deep_output string Whether to enable deep save output for the current layer in clarisse IFX, no under clarisse BUiLDER "1"
save_to_disk string Whether to save the output of the current layer in clarisse IFX, no under clarisse BUiLDER "1"
enable_deep_output_path string clarisse IFX is the deep output path of the current layer, there is no under clarisse BUiLDER "D:\temp\cam02_layer02_deep"
name string 1: The current layer name in clarisse IFX is also the path in the scene;
2: The name of the current ImageNodeWrite in clarisse BUiLDER, the value is the path in the scene of the current VariableRange and the current imageNodeWrite in the scene Path to === link		 1："project://scene/cam02.cam02_layer02"
2：“build://yt_0080===build://cloudShadow”

2.upload.json

File to save assets info

upload.json example

{
    "scene": [
        {
            "local": "E:\\work\\Trex\\ep\\ani_fly\\clarisse\\trex_fly_env_songshu.project",
            "server": "/E/work/Trex/ep/ani_fly/clarisse/trex_fly_env_songshu.project"
        }
    ],
    "asset": [
        {
            "local": "E:\\work\\Trex\\ep\\ani_fly\\clarisse\\assets\\speedtree\\guanmu01\\LeafHD2.png",
            "server": "/E/work/Trex/ep/ani_fly/clarisse/assets/speedtree/guanmu01/LeafHD2.png"
        },
        {
            "local": "E:\\work\\Trex\\ep\\ani_fly\\clarisse\\assets\\speedtree\\tree_far\\tree_far08\\HuangshanPineBark_Normal.png",
            "server": "/E/work/Trex/ep/ani_fly/clarisse/assets/speedtree/tree_far/tree_far08/HuangshanPineBark_Normal.png"
        }
    ]
}

upload.json

parameter type description example
asset object Asset path information to be uploaded refer to asset
scene object Scene file information refer to scene

asset

parameter type description example
local string local path of asset "E:\work\Trex\ep\ani_fly\clarisse\assets\speedtree\guanmu01\LeafHD2.png"
server string Relative path on the server side, generally consistent with local "/E/work/Trex/ep/ani_fly/clarisse/assets/speedtree/guanmu01/LeafHD2.png"

scene

parameter type description example
local string local path of project "E:\work\Trex\ep\ani_fly\clarisse\trex_fly_env_songshu.project"
server string Relative path on the server side, generally consistent with local "/E/work/Trex/ep/ani_fly/clarisse/trex_fly_env_songshu.project"

3.tips.json

File to save errors, warnings
{
    "50001":[
        "Nodes: /obj/flattank_fluid/compressed_cache/file_mode  File name: $HIP/geo/$HIPNAME.$OS.$F.bgeo.sc  miss file: /geo/flip_test_slice4.compressed_cache.1.bgeo.sc ",
    ]
}

Houdini Configuration

Analyze houdini scene and save the output as task.json, asset.json,upload.json and tips.json.

1.task.json

File to save the analysis result of the scene, including scene name, cg software version, render settings, etc.

task.json

{
    "scene_info_render": {
        "rop_node": [
            {
                "node": "/out/mantra1", 
                "frames": "1-10[1]", 
                "option": "-1", 
                "render": "1",
                "height": "720",
				"width": "1280"
            }
        ], 
        "geo_node": [],
        "distributedsim_node": [
			{
				"node": "/out/distributedsim",
				"output_driver": "/obj/distribute_flattank/save_slices",
				"render": "0",
				"simControlName": "/obj/flattank_sim/DISTRIBUTE_flattank_CONTROLS",
				"output_file": "/geo/flip_test_slice4.flattank.0.1.bgeo.sc",
				"num_slices": "4",
				"option": "1",
				"frames": "1-240[1]",
				"sliceType": "particle"
			}
        ]
    }, 
    "task_info": {
        "enable_layered":"1", 
        "cg_id": "2004", 
        "ram": "64", 
        "os_name": "1", 
        "render_layer_type": "0", 
        "is_distribute_render": "1", 
        "input_cg_file": "D:/gitlab/renderSDK/scenes/houdini_test/sphere.hip", 
        "job_stop_time": "28800", 
        "user_id": "10000031", 
        "pre_frames": "000", 
        "platform": "2", 
        "is_picture": "0", 
        "project_id": "3316", 
        "channel": "4", 
        "tiles_type": "block", 
        "tiles": "1", 
        "project_name": "dasdd", 
        "distribute_render_node": "3", 
        "frames_per_task": "1", 
        "stop_after_test": "2", 
        "input_project_path": "", 
        "task_id": "440149", 
        "task_stop_time": "86400", 
        "time_out": "12",
        "graphics_cards_num": "2"
    },  
    "software_config": {
        "cg_version": "16.5.268", 
        "cg_name": "Houdini", 
        "plugins": {}
    }
}

task.json Parametric Interpretation

parameter type description example
software_config object Y environment(cg software, version and plugins, etc.) refer to software_config
task_info object Y render settings(priority frames, render range, etc.) refer to task_info
scene_info_render object Y analysis result(render node, output, etc.) refer to scene_info_render

software_config

parameter type description example
cg_name string software "Houdini"
cg_version string software version "16.5.268"
plugins object plugin{name, version} {}

task_info

parameter type Is it necessary description default example
graphics_cards_num string Y 1： open single card rendering 2: open dual card rendering "2" "2"
enable_layered string Y render layer mode,"0":off, "1":on "0" "1"
cg_id string Y software id."2004": Houdini "2013"
ram string Y ram: 64 / 128 "64" "64"
os_name string Y Rendering machine operating system: "0":Linux; "1": Windows "1" "1"
render_layer_type string N render layer mode(only support maya): "0"：renderlayer方式 "1"：rendersetup方式 "0" "0"
is_distribute_render string N distributed render mode,"0":off, "1":on "0" "0"
input_cg_file string Y input file path "E:/copy/DHGB_sc05_zhuta_610-1570_v0102.project"
input_project_path string Y project path, could be empty " "
job_stop_time string Y Set the frame timeout time, will only affect the current frame, unit seconds "259200" "28800"
user_id string Y user id
pre_frames string Y Priority rendering (priority frames are not recommended to customize multiple individual frames) "000" "000: 1,3-4 [1]" means: Priority rendering first frame: No Priority rendering middle frame: No Priority rendering last frame: No Priority rendering custom frame: 1,3-4 [1]
platform string Y submit platform : "2": "www2", "3": "www3", "6": "www4", "21": "gpu", "2"
is_picture string Y "0: Effect Chart "1": Animation Chart "0" "0"
project_id string Y project id " " "200953"
project_name string Y project name " 0" "Project1"
channel string Y 1:Web local analysis (animation deduction); 2:web cloud analysis; 3:Rendering plugin submission； 4：API/SDK submission; 8：Animation plugin submission "4" "4"
tiles_type string Y "block, strip" "block" "block"
tiles string Y tile number, 1 for single node, greater than 1 for tiles rendering(multi-nodes) "1" "1"
distribute_render_node string N nodes number for distributed rendering "3" "3"
frames_per_task string Y frames per task "1" "1"
stop_after_test string Y "1":pause after priority render, "2":continue after priority render (default "2") "2" "2"
task_id string Y task id
task_stop_time string Y Large task timeout stops in unit seconds, "0" means unlimited "0" "86400"
time_out string Y Overtime reminder time, unit: sec "43200" "43200"
Note：The distributed rendering machine (distribute_render_node) will only take effect if the distributed storage parameter (distribute_render_node) is set to on.

scene_info_render

parameter type description example
rop_node object Render node
geo_node object Solve node
distributedsim_node object Distributed node

scene_info_render.rop_node和geo_node

parameter type Is it necessary description example
node string Y Node full path name "/out/mantra1"
frames string Y Frame number range "1-10[1]"
option string Y Task type:
-1: rendering;
0: general solution;
1: distributed solution;		 "-1"
render string Y Whether to activate rendering:
1: Render (solve) the node;
0: The node does not participate in rendering (solve)		 "1"
height string N Camera height “720”
width string N Camera width “1280”

scene_info_render.distributedsim_node对象解析

parameter type Is it necessary description example
node string Y Node full path name "/out/distributedsim"
output_driver string N Solve node path "/obj/distribute_flattank/save_slices"
render string Y Whether to activate rendering:
1: Render (solve) the node;
0: The node does not participate in rendering (solve)		 "0"
simControlName string N Solve node name "/obj/flattank_sim/DISTRIBUTE_flattank_CONTROLS"
output_file string N Output file "/geo/flip_test_slice4.flattank.0.1.bgeo.sc"
num_slices string N Block calculation of the total number of blocks (the total cannot exceed 16) "4"
option string Y Task type:
-1: rendering;
0: general solution;
1: distributed solution;		 "1"
frames string Y Solve Frame Range "1-240[1]"
sliceType string N Slice type "particle"

2.upload.json

File to save asset info

upload.json example

{
  "asset": [
    {
      "local": "D:/gitlab/renderSDK/scenes/houdini_test/sphere.hip", 
      "server": "/D/gitlab/renderSDK/scenes/houdini_test/sphere.hip"
    }
  ]
}

upload.json

parameter type description example
asset object Asset path information to be uploaded refer to asset

asset

parameter type description example
local string local path of asset "D:/gitlab/renderSDK/scenes/houdini_test/sphere.hip"
server string Relative path on the server side, generally consistent with local "/D/gitlab/renderSDK/scenes/houdini_test/sphere.hip"

3.tips.json

File to save errors, warnings
{
    "50001":[
        "Nodes: /obj/flattank_fluid/compressed_cache/file_mode  File name: $HIP/geo/$HIPNAME.$OS.$F.bgeo.sc  miss file: /geo/flip_test_slice4.compressed_cache.1.bgeo.sc "
    ]
}

Maya Configuration

Analyze clarisse scene and save the output as task.json, asset.json, upload.json and tips.json.

1.task.json

File to save the analysis result of the scene, including scene name, cg software version, render settings, etc.

task.json

{
    "scene_info_render": {
        "defaultRenderLayer": {
            "renderable": "1", 
            "env": {}, 
            "is_default_camera": "1", 
            "option": "", 
            "common": {
                "image_format": "exr", 
                "end": "10", 
                "width": "960", 
                "image_file_prefix": "", 
                "all_camera": [
                    "stereoCameraRightShape", 
                    "stereoCameraLeftShape", 
                    "stereoCameraCenterCamShape", 
                    "perspShape", 
                    "cameraShape2", 
                    "cameraShape1"
                ], 
                "render_camera": [
                    "cameraShape1"
                ], 
                "start": "1", 
                "animation": "False", 
                "renderer": "mentalRay", 
                "frames": "1-10[1]", 
                "height": "540", 
                "renumber_frames": "False", 
                "by_frame": "1"
            }
        }, 
        "mut": {
            "renderable": "1", 
            "is_default_camera": "1", 
            "option": "", 
            "common": {
                "image_format": "exr", 
                "end": "10", 
                "width": "960", 
                "image_file_prefix": "", 
                "all_camera": [
                    "stereoCameraRightShape", 
                    "stereoCameraLeftShape", 
                    "stereoCameraCenterCamShape", 
                    "perspShape", 
                    "cameraShape2", 
                    "cameraShape1"
                ], 
                "render_camera": [
                    "cameraShape1", 
                    "stereoCameraLeftShape"
                ], 
                "start": "1", 
                "animation": "False", 
                "renderer": "mentalRay", 
                "frames": "1-10[1]", 
                "height": "540", 
                "renumber_frames": "False", 
                "by_frame": "1"
            }
        }
    }, 
    "task_info": {
        "enable_layered": "1", 
        "cg_id": "2000", 
        "ram": "64", 
        "os_name": "1", 
        "render_layer_type": "0", 
        "is_distribute_render": "0", 
        "input_cg_file": "D:/chensr/scene/maya2016_multi_layers_cameras.ma", 
        "job_stop_time": "28800", 
        "user_id": "10000031", 
        "pre_frames": "000", 
        "platform": "2", 
        "is_picture": "0", 
        "project_id": "3316", 
        "channel": "4", 
        "tiles_type": "block", 
        "tiles": "1", 
        "project_name": "dasdd", 
        "distribute_render_node": "3", 
        "frames_per_task": "1", 
        "stop_after_test": "2", 
        "input_project_path": "", 
        "task_id": "439800", 
        "task_stop_time": "86400", 
        "time_out": "12",
        "graphics_cards_num": "2"
    }, 
    "software_config": {
        "cg_version": "2016", 
        "cg_name": "Maya", 
        "plugins": {}
    }
}

task.json

parameter type description example
software_config object environment(cg software, version and plugins, etc.) refer to software_config
task_info object render settings(priority frames, render range, etc.) refer to task_info
scene_info_render object analysis result(render node, output, etc.) refer to scene_info_render

software_config

parameter type Is it necessary description example
cg_name string Y software "Maya"
cg_version string Y software version "2016"
plugins object Y plugin{name, version} {}

task_info

parameter type Is it necessary description default example
graphics_cards_num string Y 1： open single card rendering 2: open dual card rendering "2"
enable_layered string Y render layer mode,"0":off, "1":on "0" "1"
cg_id string Y software id."2000": Maya "2013"
ram string Y ram: 64 / 128 "64" "64"
os_name string Y Rendering machine operating system: "0":Linux; "1": Windows "1" "1"
render_layer_type string N render layer mode: "0"：renderlayer "1"：rendersetup "0" "0"
is_distribute_render string N distributed render mode,"0":off, "1":on "0" "0"
input_cg_file string Y input file path "E:/copy/DHGB_sc05_zhuta_610-1570_v0102.project"
input_project_path string Y project path, could be empty " "
job_stop_time string Y Set the frame timeout time, will only affect the current frame, unit seconds "259200" "28800"
user_id string Y user id
pre_frames string Y Priority rendering (priority frames are not recommended to customize multiple individual frames) "000" "000: 1,3-4 [1]" means: Priority rendering first frame: No Priority rendering middle frame: No Priority rendering last frame: No Priority rendering custom frame: 1,3-4 [1]
platform string Y submit platform : "2": "www2", "3": "www3", "6": "www4", "21": "gpu", "2"
is_picture string Y "0: Effect Chart "1": Animation Chart "0" "0"
project_id string Y project id " " "200953"
project_name string Y project name " 0" "Project1"
channel string Y 1:Web local analysis (animation deduction); 2:web cloud analysis; 3:Rendering plugin submission； 4：API/SDK submission; 8：Animation plugin submission "4" "4"
tiles_type string Y "block, strip" "block" "block"
tiles string Y tile number, 1 for single node, greater than 1 for tiles rendering(multi-nodes) "1" "1"
distribute_render_node string N nodes number for distributed rendering "3" "3"
frames_per_task string Y frames per task "1" "1"
stop_after_test string Y "1":pause after priority render, "2":continue after priority render (default "2") "2" "2"
task_id string Y task id
task_stop_time string Y Large task timeout stops in unit seconds, "0" means unlimited "0" "86400"
time_out string Y Overtime reminder time, unit: sec "43200" "43200"

Note:

  • Only when layering is enabled (enable_layered) can you use tiled rendering. Tiled rendering mode (tiles_type) and one machine multi-frame rendering mode (frames_per_task) are mutually exclusive. Only one mode can be used at the same time
  • Maya currently does not support distributed rendering (is_distribute_render).

scene_info_render

parameter type Is it necessary description example
layer object Y layer info refer to scene_info_render.layer

scene_info_render.layer

parameter type description example
renderable string Y Render layer switch "1"
env object N Environmental information {}
is_default_camera string N Whether to use the default camera, the default value is ‘1’ (use the default camera) "1"
option string N Renderer corresponding information ""
common object Y Scene general information refer to scene_info_render.layer.common

scene_info_render.layer.common

parameter type Is it necessary description example
image_format string Y Render element output file type "jpg"
end string Y end frame "100"
width string Y Width-resolution "1920"
image_file_prefix string Y Output file name setting，"/" ""
all_camera array Y List of all cameras ["stereoCameraRightShape", "cameraShape1"]
render_camera array Y List of cameras to be rendered ["stereoCameraRightShape"]
start string Y Start frame "1"
animation string N Animation switch "False"
renderer string Y Renderer name “arnold“
frames string Y Render frame "1-10[1]"
height string Y High-resolution "1080"
renumber_frames string N Frame overlay "False"
by_frame string Y Frame interval "1"

2.upload.json

File to save assets info

upload.json example

{
  "asset": [
    {
      "local": "D:/chensr/scene/maya2016_multi_layers_cameras.ma", 
      "server": "/D/chensr/scene/maya2016_multi_layers_cameras.ma"
    }
  ]
}

upload.json

parameter type description example
asset object Asset path information to be uploaded refer to asset

asset Parametric Interpretation

parameter type description example
local string local path of asset "D:/chensr/scene/maya2016_multi_layers_cameras.ma"
server string Relative path on the server side, generally consistent with local "/D/chensr/scene/maya2016_multi_layers_cameras.ma"

3.tips.json

File to save errors, warnings
{
    "50001":[
        "Nodes: /obj/flattank_fluid/compressed_cache/file_mode  File name: $HIP/geo/$HIPNAME.$OS.$F.bgeo.sc  miss file: /geo/flip_test_slice4.compressed_cache.1.bgeo.sc ",
    ]
}

Max Profile document

Analysis: We analyze and save the information needed in the scene to task.json, asset.json, upload.json, tips.json for further analysis and processing

1.task.json

Description: Store scene analysis results, rendering settings and other information

task.json

{
    "scene_info": {
        "common": {
            "CurrentProjectFolder": "C:/Users/dingyutao/Documents/3dsMax",
            "Faces": "3784",
            "Peak_Memory": "702.758",
            "Vertices": "1914",
            "all_camera": [
                "Camera001",
                "Camera002",
                "Camera003",
                "Camera004",
                "Camera005"
            ],
            "all_element_type": [
                ".tga",
                ".tif",
                ".jpg",
                ".png",
                ".exr",
                ".rla",
                ".rpf"
            ],
            "all_output_file_type": [
                ".tga",
                ".tif",
                ".jpg",
                ".png",
                ".exr",
                ".rla",
                ".rpf"
            ],
            "animation_range": "0-100",
            "cgv": "2018",
            "element_active": "1",
            "element_list": [
				"MultiMatteElement",
				"VRayAlpha",
				"VRayAtmosphere",
				"VRayBackground",
				"MultiMatteElement",
				"VRayAlpha",
				"VRayAtmosphere"
			],
			"element_path_list": [
				"jh_out_MultiMatteElement.rla",
				"jh_out_VRayAlpha.rla",
				"jh_out_VRayAtmosphere.rla",
				"jh_out_VRayBackground.rla",
				"jh_out_MultiMatteElement1.rla",
				"jh_out_VRayAlpha2.rla",
				"jh_out_VRayAtmosphere.rla"
			],
            "element_type": ".rla",
            "frames": "0",
            "gamma": "1",
            "gamma_val": "2.2",
            "global_proxy": "false",
            "height": "480",
            "in_gamma": "2.2",
            "is_picture": "0",
            "net_render": "0",
            "out_gamma": "2.2",
            "output_file": "E:/3D_Scene/Max/jh/output/1/jh_out.rla",
            "output_file_basename": "jh_out",
            "output_file_type": ".rla",
            "rend_save_file": "true",
            "rend_timeType": "1",
            "renderable_camera": [],
            "taskdurationlimit": "86400",
            "width": "640"
        },
        "renderer": {
            "name": "scanline",
            "renderer": "scanline",
            "renderer_orign": "Default_Scanline_Renderer"
        }
    },
    "scene_info_render": {
        "common": {
            "CurrentProjectFolder": "C:/Users/dingyutao/Documents/3dsMax",
            "Faces": "3784",
            "Peak_Memory": "702.758",
            "Vertices": "1914",
            "all_camera": [
                "Camera001",
                "Camera002",
                "Camera003",
                "Camera004",
                "Camera005"
            ],
            "all_element_type": [
                ".tga",
                ".tif",
                ".jpg",
                ".png",
                ".exr",
                ".rla",
                ".rpf"
            ],
            "all_output_file_type": [
                ".tga",
                ".tif",
                ".jpg",
                ".png",
                ".exr",
                ".rla",
                ".rpf"
            ],
            "animation_range": "0-100",
            "cgv": "2018",
            "element_active": "1",
            "element_list": [
                "Missing_Render_Element_Plug_in",
                "Missing_Render_Element_Plug_in",
                "Missing_Render_Element_Plug_in",
                "Missing_Render_Element_Plug_in",
                "Missing_Render_Element_Plug_in",
                "Missing_Render_Element_Plug_in",
                "Missing_Render_Element_Plug_in"
            ],
            "element_path_list": [],
            "element_type": ".rla",
            "frames": "0",
            "gamma": "1",
            "gamma_val": "2.2",
            "global_proxy": "false",
            "height": "480",
            "in_gamma": "2.2",
            "is_picture": "0",
            "net_render": "0",
            "out_gamma": "2.2",
            "output_file": "E:/3D_Scene/Max/jh/output/1/jh_out.rla",
            "output_file_basename": "jh_out",
            "output_file_type": ".rla",
            "rend_save_file": "true",
            "rend_timeType": "1",
            "renderable_camera": [
                "Camera001"
            ],
            "width": "640"
        },
        "renderer": {
            "name": "scanline",
            "renderer": "scanline",
            "renderer_orign": "Default_Scanline_Renderer"
        }
    },
    "software_config": {
        "cg_name": "3ds Max",
        "cg_version": "2018",
        "plugins": {}
    },
    "task_info": {
        "cg_id": "2001",
        "channel": "4",
        "distribute_render_node": "3",
        "enable_layered": "0",
        "frames_per_task": "1",
        "input_cg_file": "D:/houdini/CG file/jh/jh.max",
        "input_project_path": "",
        "is_distribute_render": "0",
        "is_layer_rendering": "1",
        "is_picture": "0",
        "job_stop_time": "259200",
        "os_name": "1",
        "platform": "2",
        "pre_frames": "100",
        "project_id": "200953",
        "project_name": "Project1",
        "ram": "64",
        "render_layer_type": "0",
        "stop_after_test": "1",
        "task_id": 28474141,
        "task_stop_time": "0",
        "tiles": "1",
        "tiles_type": "block",
        "time_out": "43200",
        "user_id": 100150764
    },
    "additional_info": {}
}

task.json

parameter type Is it necessary description example
software_config dict Y environment(cg software, version and plugins, etc.) refer to software_config
task_info dict Y render settings(priority frames, render range, etc.) refer to task_info
scene_info_render dict Y analysis result(render node, output, etc.) refer to scene_info_render
scene_info dict N same as scene_info_render
additional_info dict N Location of user-defined parameters (need to use custom parameters, need to confirm with the company business personnel)

software_config

parameter type Is it necessary description example
cg_name string Y software name "3ds Max"
cg_version string Y software version "2001"
plugins object Y rendering plugin {}

task_info

parameter type Is it necessary description default example
graphics_cards_num string Y 1： open single card rendering 2: open dual card rendering "2"
enable_layered string Y render layer mode,"0":off, "1":on "0" "1"
cg_id string Y software id."2001": Max "2001"
ram string Y ram: 64 / 128 "64" "64"
os_name string Y Rendering machine operating system: "0":Linux; "1": Windows "1" "1"
render_layer_type string N render layer mode: "0"：renderlayer "1"：rendersetup "0" "0"
is_distribute_render string N distributed render mode,"0":off, "1":on "0" "0"
input_cg_file string Y input file path "E:/copy/DHGB_sc05_zhuta_610-1570_v0102.project"
input_project_path string Y project path, could be empty " "
job_stop_time string Y Set the frame timeout time, will only affect the current frame, unit seconds "259200" "28800"
user_id string Y user id
pre_frames string Y Priority rendering (priority frames are not recommended to customize multiple individual frames) "000" "000: 1,3-4 [1]" means: Priority rendering first frame: No Priority rendering middle frame: No Priority rendering last frame: No Priority rendering custom frame: 1,3-4 [1]
platform string Y submit platform : "2": "www2", "3": "www3", "6": "www4", "21": "gpu", "2"
is_picture string Y "0: Effect Chart "1": Animation Chart "0" "0"
project_id string Y project id " " "200953"
project_name string Y project name " 0" "Project1"
channel string Y 1:Web local analysis (animation deduction); 2:web cloud analysis; 3:Rendering plugin submission； 4：API/SDK submission; 8：Animation plugin submission "4" "4"
tiles_type string Y "block, strip" "block" "block"
tiles string Y tile number, 1 for single node, greater than 1 for tiles rendering(multi-nodes) "1" "1"
distribute_render_node string N nodes number for distributed rendering "3" "3"
frames_per_task string Y frames per task "1" "1"
stop_after_test string Y "1":pause after priority render, "2":continue after priority render (default "2") "2" "2"
task_id string Y task id
task_stop_time string Y Large task timeout stops in unit seconds, "0" means unlimited "0" "86400"
time_out string Y Overtime reminder time, unit: sec "43200" "43200"

Note:

  • Only when the GI setting is enabled can you use block rendering. The tile rendering mode (tiles_type) and the multi-frame rendering mode (frames_per_task) are mutually exclusive. Only one mode can be used at the same time.
  • Max temporarily does not support distributed rendering (is_distribute_render).
  • Max no layered rendering (enable_layered).

scene_info_render

parameter type Is it necessary description example
renderer dict Y Renderer refer to scene_info_render.renderer
common dict Y Scene general information refer to scene_info_render.common

scene_info_render.common

parameter type Is it necessary description example
CurrentProjectFolder string Y The project path of the scene "C:/Users/dingyutao/Documents/3dsMax"
Faces string N Number of faces in the scene "3784"
Peak_Memory string Y Peak memory "702.758"
Vertices string Y vertex "1914"
all_camera list Y List of all cameras ["Camera001", "Camera002"，“Camera003”]
all_element_type list Y All supported rendering element types [
".tga",
".tif",
".jpg",
".png",
".exr",
".rla",
".rpf"
]
all_output_file_type list Y All supported output file types [
".tga",
".tif",
".jpg",
".png",
".exr",
".rla",
".rpf"
]
animation_range string N Animation frame range "0-100"
cgv string Y Max software version “2018“
element_active string Y Whether to output rendering elements
"1": output; "0": no output		 "1"
element_list list Y Render element list [
"MultiMatteElement",
"VRayAlpha",
"VRayAtmosphere",
"VRayBackground",
"MultiMatteElement",
"VRayAlpha",
"VRayAtmosphere"
]
element_path_list list N List of element paths [
"jh_out_MultiMatteElement.rla", "jh_out_VRayAlpha.rla",
"jh_out_VRayAtmosphere.rla",
"jh_out_VRayBackground.rla",
"jh_out_MultiMatteElement1.rla",
"jh_out_VRayAlpha2.rla",
"jh_out_VRayAtmosphere.rla"
]
element_type string Y Output element type ".rla"
frames string Y Current rendered frame “0”
gamma string Y Whether gamma is enabled in the scene
"1": enabled;
"0": not enabled		 “1”
gamma_val string Y Gamma “2.2”
global_proxy string Y Whether to open the global agent “false”
height string Y Resolution, high "480"
width string Y Resolution, width "640"
in_gamma string Y fileingamma "2.2"
is_picture string Y "0: Effect Chart "1": Animation Chart "0"
net_render string N Whether network rendering
"1": on;
"0": not on		 "0"
out_gamma string Y fileoutgamma "2.2"
output_file string Y The main image output path in the scene "E:/3D_Scene/Max/jh/output/1/jh_out.rla"
rend_save_file string N Whether to save the output file “true”
rend_timeType string N rendTimeType “1”
renderable_camera list N Need to submit the rendered camera ["Camera001"]

scene_info_render.renderer

parameter type Is it necessary description example
name string Y renderers.production "scanline"
renderer string Y classof renderers.production "scanline"
renderer_orign string Y renderer orign "Default_Scanline_Renderer"

2.upload.json

Description: Store asset path information to be uploaded

upload.json

{
    "asset": [
        {
            "server": "/C/3D_Scene/Max/jh/3d66Model-545019-files-1.JPG",
            "local": "D:/houdini/CG file/jh/3d66Model-545019-files-1.JPG"
        },
        {
            "server": "/C/3D_Scene/Max/jh/3d66Model-545019-files-3.jpg",
            "local": "D:/houdini/CG file/jh/3d66Model-545019-files-3.jpg"
        },
        {
            "server": "/C/3D_Scene/Max/jh/3d66Model-545019-files-4.jpg",
            "local": "D:/houdini/CG file/jh/3d66Model-545019-files-4.jpg"
        },
        {
            "server": "/C/3D_Scene/Max/jh/3d66Model-545019-files-6.JPG",
            "local": "D:/houdini/CG file/jh/3d66Model-545019-files-6.JPG"
        },
        {
            "server": "/C/3D_Scene/Max/jh/3d66Model-545019-files-8.jpg",
            "local": "D:/houdini/CG file/jh/3d66Model-545019-files-8.jpg"
        },
        {
            "server": "/C/Program Files/Autodesk/3ds Max 2018/maps/uvwunwrap/UV_Checker.png",
            "local": "C:/Program Files/Autodesk/3ds Max 2018/maps/uvwunwrap/UV_Checker.png"
        },
        {
            "server": "/D/houdini/CG file/jh/jh.max.7z",
            "local": "C:/workspace/max/1593418445/jh.max.7z"
        }
    ],
    "scene": {
        "hash": "8a0d163994a2361808b6f5390967a614",
        "server": "/D/houdini/CG file/jh/jh.max.7z",
        "local": "C:/workspace/max/1593418445/jh.max.7z"
    },
    "vrlmap": [],
    "vrmap": []
}

upload.json

parameter type description description example
asset list Y Asset path information to be uploaded refer to asset
scene dict Y Information of scene compressed files to be uploaded
vrlmap list N Light cache information to be uploaded
vrmap list N The cache information of the luminous texture to be uploaded

asset

parameter type description example
local string Asset local path "D:/chensr/scene/maya2016_multi_layers_cameras.ma"
server string Server-side relative paths are generally consistent with local. "/D/chensr/scene/maya2016_multi_layers_cameras.ma"

3.tips.json

Description: Storage of analytical errors, warnings
{
    "10035": [
        "not activation camera"
    ],
    "15031": [
        "Missing_Render_Element_Plug_in",
        "Missing_Render_Element_Plug_in",
        "Missing_Render_Element_Plug_in",
        "Missing_Render_Element_Plug_in",
        "Missing_Render_Element_Plug_in",
        "Missing_Render_Element_Plug_in",
        "Missing_Render_Element_Plug_in"
    ]
}

Katana Configuration

Analyze katana scene and save the output as task.json, asset.json, tips.json.

1.task.json

File to save the analysis result of the scene, including scene name, cg software version, render settings, etc.

task.json

{
  "scene_info_render": {
    "rendernodes": {
      "Render": {
        "renderable": "1",
        "denoise": "0",
        "frames": "1-1[1]",
        "aov": {
          "aaa": "F:/cache/test.exr"
        }
      }
    }
  },
  "additional_info": {},
  "task_info": {
    "enable_layered": "0",
    "task_stop_time": "0",
    "concurrent_tasks": "1",
    "channel": "4",
    "frames_per_task": "1",
    "task_id": 34399251,
    "project_name": "Project1",
    "platform": "2",
    "tiles": "1",
    "is_picture": "0",
    "project_id": "200953",
    "job_stop_time": "259200",
    "distribute_render_node": "3",
    "stop_after_test": "1",
    "clone_original_id": "",
    "ram": "64",
    "render_layer_type": "0",
    "test_frames": "100",
    "graphics_cards_num": "2",
    "edit_name": "",
    "pre_frames": "100",
    "input_project_path": "",
    "is_layer_rendering": "1",
    "is_distribute_render": "0",
    "tiles_type": "block",
    "time_out": "43200",
    "cg_id": "2016",
    "user_id": 100150764,
    "input_cg_file": "F:/cache/arnold_test.katana",
    "os_name": "1"
  },
  "software_config": {
    "plugins": {
      "KtoA": "2.4.0.3"
    },
    "cg_version": "3.2v1",
    "cg_name": "Katana"
  },
  "scene_info": {
    "rendernodes": {
      "Render": {
        "renderable": "1",
        "denoise": "0",
        "frames": "1-1[1]",
        "aov": {
          "aaa": "F:/cache/test.exr"
        }
      }
    }
  }
}

task.json

parameter type description example
software_config object environment(cg software, version and plugins, etc.) refer to software_config
task_info object render settings(priority frames, render range, etc.) refer to task_info
scene_info_render object analysis result(render node, output, etc.) refer to scene_info_render

software_config

parameter type Is it necessary description example
cg_name string Y software "Katana"
cg_version string Y software version "3.2v1"
plugins object Y plugin{name, version} {"KtoA": "2.4.0.3"}

task_info

parameter type Is it necessary description default example
graphics_cards_num string Y 1： open single card rendering 2: open dual card rendering "2"
enable_layered string Y render layer mode,"0":off, "1":on "0" "1"
cg_id string Y software id."2016": Katana "2016"
ram string Y ram: 64 / 128 "64" "64"
os_name string Y Rendering machine operating system: "0":Linux; "1": Windows "1" "1"
render_layer_type string N render layer mode: "0"：renderlayer "1"：rendersetup "0" "0"
is_distribute_render string N distributed render mode,"0":off, "1":on "0" "0"
input_cg_file string Y input file path "F:/cache/arnold_test.katana"
input_project_path string Y project path, could be empty " "
job_stop_time string Y Set the frame timeout time, will only affect the current frame, unit seconds "259200" "28800"
user_id string Y user id
pre_frames string Y Priority rendering (priority frames are not recommended to customize multiple individual frames) "000" "000: 1,3-4 [1]" means: Priority rendering first frame: No Priority rendering middle frame: No Priority rendering last frame: No Priority rendering custom frame: 1,3-4 [1]
platform string Y submit platform : "2": "www2", "3": "www3", "6": "www4", "21": "gpu", "2"
is_picture string Y "0: Effect Chart "1": Animation Chart "0" "0"
project_id string Y project id " " "200953"
project_name string Y project name "0" "Project1"
channel string Y 1:Web local analysis (animation deduction); 2:web cloud analysis; 3:Rendering plugin submission； 4：API/SDK submission; 8：Animation plugin submission "4" "4"
tiles_type string Y "block, strip" "block" "block"
tiles string Y tile number, 1 for single node, greater than 1 for tiles rendering(multi-nodes) "1" "1"
distribute_render_node string N nodes number for distributed rendering "3" "3"
frames_per_task string Y frames per task "1" "1"
stop_after_test string Y "1":pause after priority render, "2":continue after priority render (default "2") "2" "2"
task_id string Y task id
task_stop_time string Y Large task timeout stops in unit seconds, "0" means unlimited "0" "86400"
time_out string Y Overtime reminder time, unit: sec "43200" "43200"

Note:

  • Katana do not support distributed rendering (is_distribute_render) and block rendering (tiles)

scene_info_render

parameter type Is it necessary description example
rendernodes dict Y Render output nodes refer to scene_info_render.rendernodes

scene_info_render.rendernodes

parameter type description example
Render dict Node names, which may have multiple different node names depending on the scenario scene_info_render.rendernodes.Render

scene_info_render.rendernodes.Render

parameter type Is it necessary description example
renderable string Y Whether the node is active, "1" : active, "0" : inactive
denoise string N Noise reduction (effective only on GPU platform), "0" : not on, "1" : on "denoise": "0"
frames string Y Frame range of current node "frames": "1-1[1]"
aov dict Y AOV must be the path in the scene, key: AOV name, value: output address

2.upload.json

Katana does not analyze asset files, but has an Upload.json file that contains only scenario files

upload.json example

{
  "scene": [
    {
      "local": "F:/cache/arnold_test.katana",
      "server": "/F/cache/arnold_test.katana",
      "hash": "41985d615b8e6d44ce7e7881c46971de"
    }
  ],
  "asset": [
    {
      "local": "F:/cache/arnold_test.katana",
      "server": "/F/cache/arnold_test.katana"
    },
  ]
}

upload.json

parameter type description example
asset object Asset path information to be uploaded refer to asset
scene object Scene file information refer to scene

asset Parametric Interpretation

parameter type description example
local string local path of asset "F:/cache/arnold_test.katana
server string Relative path on the server side, generally consistent with local "/F/cache/arnold_test.katana"
hash string hash value "41985d615b8e6d44ce7e7881c46971de"

3.tips.json

File to save errors, warnings
{
    "50001":[
        "Nodes: /obj/flattank_fluid/compressed_cache/file_mode  File name: $HIP/geo/$HIPNAME.$OS.$F.bgeo.sc  miss file: /geo/flip_test_slice4.compressed_cache.1.bgeo.sc ",
    ]
}

Arnold Standalone Configuration

1.task.json

File to save the analysis result of the scene, including scene name, cg software version, render settings, etc.

task.json

{
    "software_config": {
        "plugins": {},
        "cg_version": "6.0.3.0",
        "cg_name": "Arnold Standalone"
    },
    "task_info": {
        "tiles": "1",
        "graphics_cards_num": "2",
        "edit_name": "arnord1111",
        "job_stop_time": "86400",
        "stop_after_test": "1",
        "frames_per_task": "1",
        "ram": "64",
        "time_out": "43600",
        "pre_frames": "100",
        "task_id": "38226011",
        "user_id": "100150764",
        "project_name": "ff",
        "project_id": "426731",
        "input_cg_file": "E:/fang/ass_test/static_ass.ass",
        "task_stop_time": "86400",
        "cg_id": 2003
    },
    "additional_info": {},
    "scene_info_render": {
        "common": {
            "frames": "1-10[1]"
        }
    }
}

task.json

parameter type Is it necessary description example
software_config dict Y environment(cg software, version and plugins, etc.) refer to software_config
task_info dict Y render settings(priority frames, render range, etc.) refer to task_info
scene_info_render dict Y analysis result(render node, output, etc.) refer to scene_info_render

software_config

parameter type Is it necessary description example
cg_name string Y software "Arnold Standalone"
cg_version string Y software version "6.0.3.0"
plugins dict N The SDK or kernel version of Arnold {}

task_info

parameter type Is it necessary description default example
graphics_cards_num string Y 1： open single card rendering 2: open dual card rendering "2" "2"
ram string Y ram: 64 / 128 "64" "64"
input_cg_file string Y Input file path,you have to use backslashes "E:/fang/ass_test/static_ass.ass"，or Serialized rendering: "E:/fang/ass_test/animation_ass.####.ass"
job_stop_time string Y Set the frame timeout time, will only affect the current frame, unit seconds "259200" "28800"
user_id string N user id,not necessary, can be automatically obtained from the server "100150764"
pre_frames string Y Priority rendering (priority frames are not recommended to customize multiple individual frames) "000" "000: 1,3-4 [1]" means: Priority rendering first frame: No Priority rendering middle frame: No Priority rendering last frame: No Priority rendering custom frame: 1,3-4 [1]
project_id string N project id "0" "426731"
project_name string N project name "ff"
tiles string N tile number, 1 for single node, greater than 1 for tiles rendering(multi-nodes) "1" "1"
stop_after_test string Y "1":pause after priority render, "2":continue after priority render (default "2") "2" "2"
task_id string N task id,Not necessary, can be automatically obtained from the server "38226011"
task_stop_time string N Large task timeout stops in unit seconds, "0" means unlimited "0" "86400"
time_out string Y Overtime reminder time, unit: sec "43200" "43200"
cg_id int Y Arnold rendering cgid can only be 2003 2003

scene_info_render

parameter type Is it necessary description example
common string Y Public parameters for rendering
frames string Y Frame range for rendering "1-10[1]"

2.upload.json

File to save assets info

Warning:

  • Please only use English letter, Number, and Underline in the file name and file path;
  • Fox does not support A,B,C,D drives, we do not support shared shared directory (\share\project) and IP path like “\192.168.0.22”;
  • Please make sure the folder structure at Fox is the same as your local;
  • Root directories can’t exceed 22 folders;

upload.json example

{
  "asset": [
    {
      "local": "E:/chensr/scene/maya2016_multi_layers_cameras.ma", 
      "server": "/E/chensr/scene/maya2016_multi_layers_cameras.ma"
    }
  ]
}

upload.json

parameter type description example
asset object Asset path information to be uploaded refer to asset

asset Parametric Interpretation

parameter type description example
local string local path of asset "E:/chensr/scene/maya2016_multi_layers_cameras.ma"
server string Relative path on the server side, generally consistent with local "/E/chensr/scene/maya2016_multi_layers_cameras.ma"

Architecture overview

This document gives a brief introduction to the RenderBusSDK components.

Component

  1. rayvision_log and rayvision_api are root modules, to be invoked by other modules;
  2. rayvision_utils is a general module integrating functions to preprocessing CG configuration information calling rayvision_api when used;
  3. rayvision_sync provides transport-related functions, relys on rayvision_log and rayvision_api;
  4. rayvision_maya, rayvision_houdini, and rayvision_clarisse rely on rayvision_utils;
  • rayvison_api

Core module, provides a lot of interfaces to be called.

  • rayvison_utils

Provides some common functions required by other modules, integrating necessary rendering data preprocessing and customized exception management functions.

  • rayvison_sync

Provides transporting functions, like uploading of CG configuration files and resource files, downloading of rendering result.

  • rayvison_maya

Provides analysis functionality for Maya resource files

  • rayvison_houdini

Provides analysis functionality for houdini resource files

  • rayvison_clarisse

Provides analysis functionality for clarisse resource files

flow chart

_images/SDK基本使用流程.png

General Parameter

PACKAGE_NAME

Set the log name and package name to deploy automatically with gitlab， for example:

​ PACKAGE_NAME = “rayvision_clarisse”

ID mapping of DCC software

DCC_ID_MAPPINGS = {
        'maya': 2000,
        '3ds Max': 2001,
        'lightwave': 2002,
        'arnold': 2003,
        'houdini': 2004,
        'cinema4d': 2005,
        'softimage': 2006,
        'blender': 2007,
        'vr_standalone': 2008,
        'mr_standalone': 2009,
        'sketchup': 2010,
        'vue': 2011,
        'keyshot': 2012,
        'clarisse': 2013,
        'octane_render': 2014,
        'katana': 2016,
    }

HEADERS

HEADERS = {
        'accessId': '',
        'channel': '4',
        'platform': '',
        'UTCTimestamp': '',
        'nonce': '',
        'signature': '',
        'version': '1.0.0',
        'Content-Type': 'application/json'
    }

task_info default parameters

TASK_INFO = {
        'task_info': {
            'input_cg_file': '',
            'is_picture': '0',
            'task_id': '',
            'frames_per_task': '1',
            'pre_frames': '000',
            'job_stop_time': '86400',
            'task_stop_time': '259200',
            'time_out': '43200',
            'stop_after_test': '2',
            'project_name': '',
            'project_id': '',
            'channel': '4',
            'cg_id': '',
            'platform': '',
            'tiles_type': 'block',
            'tiles': '1',
            'is_layer_rendering': '1',
            'is_distribute_render': '0',
            'distribute_render_node': '3',
            'input_project_path': '',
            'render_layer_type': '0',
            'user_id': '',
            'os_name': '1',
            'ram': '64'
        },
        'software_config': {},
        'scene_info': {},
        'scene_info_render': {}
    }

TASK END STATUS CODE LIST

TASK_END_STATUS_CODE_LIST = ['10', '20', '23', '25', '30', '35', '45']

TASK STATUS CODE

Code Description Memo
0 waiting WAITING
5 rendering RENDERING
8 for preprocessing tasks, start preprocessing, state in preprocessing PRE_RENDERING
10 stop STOP
20 stop (arrears) ARREARAGE_STOP
23 timeout to stop TIME_OUT_STOP
25 finished FINISHED
30 completed but failed frames FINISHED_HAS_FAILED
35 abandon ABANDON
40 test completion FINISHED_TEST
45 ailed FAILED
50 analyzing ANALYSE
100 Status update UPDATING

Frame State Code

Code Description Memo
1 Waiting for execution WAITING
2 Being executed STARTED
3 stop ABORTED
4 carry out DONE
5 Error (failure) ERROR
6 Wait for preprocessing to complete PREDONEWAITING
7 Wait for the photon frame rendering to complete PHOTONDONEWAITING
9 Wait for the photon job to finish rendering PREDONEJOBWAITING
10 Wait for the settlement job rendering to complete GOPJOBWAITING
11 Task timeout TIMEOUT

Demo

Demo for maya, houdini and clarisse

### houdini, clarisse, maya Demo

Maya demo

from rayvision_api.core import RayvisionAPI
from rayvision_maya.analyze_maya import AnalyzeMaya
from rayvision_sync.upload import RayvisionUpload
from rayvision_sync.download import RayvisionDownload
from rayvision_api.task.check import RayvisionCheck
from rayvision_api.utils import update_task_info, append_to_task, append_to_upload

# API Parameter
render_para = {
    "domain": "jop.foxrenderfarm.com", # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "2",
    "access_id": "xxxx",
    "access_key": "xxxx",
}

api = RayvisionAPI(access_id=render_para['access_id'],
                   access_key=render_para['access_key'],
                   domain=render_para['domain'],
                   platform=render_para['platform'])

# Step1:Analyze CG File
analyze_info = {
    "cg_file": r"D:\files\CG FILE\muti_layer_test.ma",
    "workspace": "c:/workspace",
    "software_version": "2019",
    "project_name": "Project1",
    "plugin_config": {
        "mtoa": "3.2.1.1"
    }
}
analyze_obj = AnalyzeMaya(**analyze_info)
analyze_obj.analyse()


# step2: Add some custom parameters, or update the original parameter value
update_task = {
    "pre_frames": "100",
    "stop_after_test": "1"
}
update_task_info(update_task, analyze_obj.task_json)

custom_info_to_task = {}
append_to_task(custom_info_to_task, analyze_obj.task_json)

custom_info_to_upload = []
append_to_upload(custom_info_to_upload, analyze_obj.upload_json)


# step3:Check json files
check_obj = RayvisionCheck(api, analyze_obj)
task_id = check_obj.execute(analyze_obj.task_json, analyze_obj.upload_json)


# Step4: Transmission
"""
There are two ways to upload the transmission:
Upload_method: 1: upload four json files and upload the resource file according to upload.json;
               2: json files and resources are uploaded separately;
"""
CONFIG_PATH = {
    "tips_json_path": analyze_obj.tips_json,
    "task_json_path": analyze_obj.task_json,
    "asset_json_path": analyze_obj.asset_json,
    "upload_json_path": analyze_obj.upload_json,
}
upload_obj = RayvisionUpload(api)
"""
The default of the test demo is to upload json and resource files at the same time,
and users can choose their own upload method according to the actual situation.
"""
upload_method = 1
if upload_method == 1:
    # step4.1:Json files are uploaded in conjunction with CG resources
    upload_obj.upload(str(task_id), **CONFIG_PATH)
elif upload_method == 2:
    # step4.2:CG resource files and json are uploaded separately
    upload_obj.upload_asset(upload_json_path=CONFIG_PATH["upload_json_path"])
    upload_obj.upload_config(str(task_id), list(CONFIG_PATH.values()))


# Step5:Submit Task
api.submit(int(task_id))


# Step6:Download
download = RayvisionDownload(api)
# All complete before the automatic start of uniform download.
# download.auto_download_after_task_completed([task_id])
# Poll download (automatic download for each completed frame)
download.auto_download([int(task_id)])

Houdini demo

from rayvision_api.core import RayvisionAPI
from rayvision_houdini.analyze_houdini import AnalyzeHoudini
from rayvision_sync.upload import RayvisionUpload
from rayvision_sync.download import RayvisionDownload
from rayvision_api.task.check import RayvisionCheck
from rayvision_api.utils import update_task_info, append_to_task, append_to_upload

# API Parameter
render_para = {
    "domain": "jop.foxrenderfarm.com",  # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "2",
    "access_id": "xxxx",
    "access_key": "xxxx",
}

api = RayvisionAPI(access_id=render_para['access_id'],
                   access_key=render_para['access_key'],
                   domain=render_para['domain'],
                   platform=render_para['platform'])

# Step1:Analyze CG File
analyze_info = {
    "cg_file": r"D:\houdini\CG file\flip_test_slice4.hip",
    "workspace": "c:/workspace",
    "software_version": "17.5.293",
    "project_name": "Project1",
    "plugin_config": {
        'renderman': '22.6'
    }
}
analyze_obj = AnalyzeHoudini(**analyze_info)
analyze_obj.analyse()


# step2: Add some custom parameters, or update the original parameter value
update_task = {
    "pre_frames": "100",
    "stop_after_test": "1"
}
update_task_info(update_task, analyze_obj.task_json)

custom_info_to_task = {}
append_to_task(custom_info_to_task, analyze_obj.task_json)

custom_info_to_upload = []
append_to_upload(custom_info_to_upload, analyze_obj.upload_json)


# step3:Check json files
check_obj = RayvisionCheck(api, analyze_obj)
task_id = check_obj.execute(analyze_obj.task_json, analyze_obj.upload_json)


# Step4: Transmission
"""
There are two ways to upload the transmission:
Upload_method: 1: upload four json files and upload the resource file according to upload.json;
               2: json files and resources are uploaded separately;
"""
CONFIG_PATH = {
    "tips_json_path": analyze_obj.tips_json,
    "task_json_path": analyze_obj.task_json,
    "asset_json_path": analyze_obj.asset_json,
    "upload_json_path": analyze_obj.upload_json,
}
upload_obj = RayvisionUpload(api)
"""
The default of the test demo is to upload json and resource files at the same time,
and users can choose their own upload method according to the actual situation.
"""
upload_method = 1
if upload_method == 1:
    # step3.1:Json files are uploaded in conjunction with CG resources
    upload_obj.upload(str(task_id), **CONFIG_PATH)
elif upload_method == 2:
    # step3.2:CG resource files and json are uploaded separately
    upload_obj.upload_asset(upload_json_path=CONFIG_PATH["upload_json_path"])
    upload_obj.upload_config(str(task_id), list(CONFIG_PATH.values()))


# Step5:Submit Task
api.submit(int(task_id))


# Step6:Download
download = RayvisionDownload(api)
# All complete before the automatic start of uniform download.
# download.auto_download_after_task_completed([task_id])
# Poll download (automatic download for each completed frame)
download.auto_download([int(task_id)])

Clarisse demo

from rayvision_api.core import RayvisionAPI
from rayvision_clarisse.analyse_clarisse import AnalyzeClarisse
from rayvision_sync.upload import RayvisionUpload
from rayvision_sync.download import RayvisionDownload
from rayvision_api.task.check import RayvisionCheck
from rayvision_api.utils import update_task_info, append_to_task, append_to_upload

# API Parameter
render_para = {
    "domain": "jop.foxrenderfarm.com",  # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "2",
    "access_id": "xxxx",
    "access_key": "xxxx",
}

api = RayvisionAPI(access_id=render_para['access_id'],
                   access_key=render_para['access_key'],
                   domain=render_para['domain'],
                   platform=render_para['platform'])

# Step1:Analyze CG File
analyze_info = {
    "cg_file": r"D:\files\CG FILE\clarisse_test1.project",
    "workspace": "c:/workspace",
    "software_version": "clarisse_ifx_4.0_sp3",
    "project_name": "Project1",
    "plugin_config": {}
}
analyze_obj = AnalyzeClarisse(**analyze_info)
analyze_obj.analyse()


# step2:Add some custom parameters, or update the original parameter value
update_task = {
    "pre_frames": "100",
    "stop_after_test": "1"
}
update_task_info(update_task, analyze_obj.task_json)

custom_info_to_task = {}
append_to_task(custom_info_to_task, analyze_obj.task_json)

custom_info_to_upload = []
append_to_upload(custom_info_to_upload, analyze_obj.upload_json)

# step3:Check json files
check_obj = RayvisionCheck(api, analyze_obj)
task_id = check_obj.execute(analyze_obj.task_json, analyze_obj.upload_json)


# Step4:Transmission
"""
There are two ways to upload the transmission:
Upload_method: 1:upload four json files and upload the resource file according to upload.json;
               2:json files and resources are uploaded separately;
"""
CONFIG_PATH = {
    "tips_json_path": analyze_obj.tips_json,
    "task_json_path": analyze_obj.task_json,
    "asset_json_path": analyze_obj.asset_json,
    "upload_json_path": analyze_obj.upload_json,
}
upload_obj = RayvisionUpload(api)
"""
The default of the test demo is to upload json and resource files at the same time,
and users can choose their own upload method according to the actual situation.
"""
upload_method = 1
if upload_method == 1:
    # step4.1:Json files are uploaded in conjunction with CG resources
    upload_obj.upload(str(task_id), **CONFIG_PATH)
elif upload_method == 2:
    # step4.2:CG resource files and json are uploaded separately
    upload_obj.upload_asset(upload_json_path=CONFIG_PATH["upload_json_path"])
    upload_obj.upload_config(str(task_id), list(CONFIG_PATH.values()))


# Step5:Submit Task
api.submit(int(task_id))


# Step6:Download
download = RayvisionDownload(api)
# All complete before the automatic start of uniform download.
# download.auto_download_after_task_completed([task_id])
# Poll download (automatic download for each completed frame)
download.auto_download([int(task_id)])

3ds Max demo

from rayvision_max.analyse_max import AnalyseMax
from rayvision_api.core import RayvisionAPI
from rayvision_api.task.check import RayvisionCheck
from rayvision_api.utils import update_task_info, append_to_upload, append_to_task
from rayvision_sync.download import RayvisionDownload
from rayvision_sync.upload import RayvisionUpload

# API Parameter
render_para = {
    "domain": "jop.foxrenderfarm.com",  # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "2",
    "access_id": "xxxx",
    "access_key": "xxxx",
}

api = RayvisionAPI(access_id=render_para['access_id'],
                   access_key=render_para['access_key'],
                   domain=render_para['domain'],
                   platform=render_para['platform'])

analyze_info = {
    "cg_file": r'D:\houdini\CG file\jh\jh.max',
    "software_version": "2018",
    "project_name": "Project1",
    "workspace": r"C:\workspace\max",
    "plugin_config": {},
    "renderable_camera": ["Camera001"],  #  Render all cameras by default without specifying the required cameras
}
analyze_obj = AnalyseMax(**analyze_info)
analyze_obj.analyse()

# step2: Add some custom parameters, or update the original parameter value
update_task = {
    "pre_frames": "100",
    "stop_after_test": "1"
}
update_task_info(update_task, analyze_obj.task_json)

custom_info_to_task = {}
append_to_task(custom_info_to_task, analyze_obj.task_json)

custom_info_to_upload = []
append_to_upload(custom_info_to_upload, analyze_obj.upload_json)

# step3:Check json files
check_obj = RayvisionCheck(api, analyze_obj)
task_id = check_obj.execute(analyze_obj.task_json, analyze_obj.upload_json)

# Step4: Transmission
"""
There are two ways to upload the transmission:
Upload_method: 1: upload four json files and upload the resource file according to upload.json;
               2: json files and resources are uploaded separately;
"""
CONFIG_PATH = {
    "tips_json_path": analyze_obj.tips_json,
    "task_json_path": analyze_obj.task_json,
    "asset_json_path": analyze_obj.asset_json,
    "upload_json_path": analyze_obj.upload_json,
}
upload_obj = RayvisionUpload(api)
"""
The default of the test demo is to upload json and resource files at the same time,
and users can choose their own upload method according to the actual situation.
"""
upload_method = 1
if upload_method == 1:
    # step4.1:Json files are uploaded in conjunction with CG resources
    upload_obj.upload(str(task_id), **CONFIG_PATH)
elif upload_method == 2:
    # step4.2:CG resource files and json are uploaded separately
    upload_obj.upload_asset(upload_json_path=CONFIG_PATH["upload_json_path"])
    upload_obj.upload_config(str(task_id), list(CONFIG_PATH.values()))

# Step5:Submit Task
api.submit(int(task_id))

# Step6:Download
download = RayvisionDownload(api)
# All complete before the automatic start of uniform download.
# download.auto_download_after_task_completed([task_id])
# Poll download (automatic download for each completed frame)
download.auto_download([int(task_id)])

Katana demo

from rayvision_api.core import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload
from rayvision_katana.analyse_katana import AnalyzeKatana
from rayvision_sync.download import RayvisionDownload
from rayvision_api.task.check import RayvisionCheck
from rayvision_api.utils import update_task_info, append_to_task, append_to_upload

# API Parameter
render_para = {
    "domain": "jop.foxrenderfarm.com",  # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "2",
    "access_id": "xxxxxxxxxxx",
    "access_key": "xxxxxxxxxxxxx",
}

api = RayvisionAPI(access_id=render_para['access_id'],
                   access_key=render_para['access_key'],
                   domain=render_para['domain'],
                   platform=render_para['platform'])

# Step1:Analyze CG File
analyze_info = {
    "cg_file": r"F:\cache\arnold_test.katana",
    "workspace": "c:/workspace",
    "software_version": "3.2v1",
    "project_name": "Project1",
    "plugin_config": {
        "KtoA": "2.4.0.3"
    }
}

analyze_obj = AnalyzeKatana(**analyze_info)
analyze_obj.analyse()


# step2: Add some custom parameters, or update the original parameter value
update_task = {
    "pre_frames": "100",
    "stop_after_test": "1"
}
update_task_info(update_task, analyze_obj.task_json)

custom_info_to_task = {}
append_to_task(custom_info_to_task, analyze_obj.task_json)

custom_info_to_upload = [
    r"F:\cache\add.png",
    r"F:\cache\ass.jpg",
    r"F:\cache\back3.jpg",
    r"F:\cache\back10.jpg",
    r"F:\cache\cizhuan.jpg",
    r"F:\cache\plane.abc",
    r"F:\cache\plane.abc",
]
append_to_upload(custom_info_to_upload, analyze_obj.upload_json)


# step3:Check json files
check_obj = RayvisionCheck(api, analyze_obj)
task_id = check_obj.execute(analyze_obj.task_json, analyze_obj.upload_json)


# Step4: Transmission
"""
There are two ways to upload the transmission:
Upload_method: 1: upload four json files and upload the resource file according to upload.json;
               2: json files and resources are uploaded separately;
"""
CONFIG_PATH = {
    "tips_json_path": analyze_obj.tips_json,
    "task_json_path": analyze_obj.task_json,
    "asset_json_path": analyze_obj.asset_json,
    "upload_json_path": analyze_obj.upload_json,
}
upload_obj = RayvisionUpload(api)
"""
The default of the test demo is to upload json and resource files at the same time,
and users can choose their own upload method according to the actual situation.
"""
upload_method = 2
if upload_method == 1:
    # step3.1:Json files are uploaded in conjunction with CG resources
    upload_obj.upload(str(task_id), **CONFIG_PATH)
elif upload_method == 2:
    # step3.2:CG resource files and json are uploaded separately
    upload_obj.upload_asset(upload_json_path=CONFIG_PATH["upload_json_path"])
    upload_obj.upload_config(str(task_id), list(CONFIG_PATH.values()))


# Step5:Submit Task
api.submit(int(task_id))


# Step6:Download
download = RayvisionDownload(api)
# All complete before the automatic start of uniform download.
# download.auto_download_after_task_completed([task_id])
# Poll download (automatic download for each completed frame)
download.auto_download([int(task_id)])

Arnorld Standalone demo

Warning

Arnorld Standalone does not have an automatic asset analysis function and requires customers to analyze asset files themselves

from rayvision_api.core import RayvisionAPI
from rayvision_sync.upload import RayvisionUpload
from rayvision_sync.download import RayvisionDownload
from rayvision_api.task.check import RayvisionCheck
from rayvision_api.utils import update_task_info, append_to_task, append_to_upload

# API Parameter
render_para = {
    "domain": "jop.foxrenderfarm.com",  # If it doesn't work, you can use "task.foxrenderfarm.com"
    "platform": "6",
    "access_id": "xxxxx",
    "access_key": "xxxxx",
}

CONFIG_PATH = {
    "task_json_path": r"D:\test\task.json",
    "upload_json_path": r"D:\test\upload.json"
}

api = RayvisionAPI(access_id=render_para['access_id'],
                   access_key=render_para['access_key'],
                   domain=render_para['domain'],
                   platform=render_para['platform'])


# step1: Add some custom parameters, or update the original parameter value
# Step1 can also be set without setting
update_task = {
    "pre_frames": "000:2,4,6-10[1]",
    "stop_after_test": "1"
}
update_task_info(update_task, CONFIG_PATH['task_json_path'])

custom_info_to_task = {}
append_to_task(custom_info_to_task, CONFIG_PATH['task_json_path'])

custom_info_to_upload = [
    r"E:\fang\ass_test\static_ass.ass",
    r"E:\fang\ass_test\animation_ass.0060.ass"
]
append_to_upload(custom_info_to_upload, CONFIG_PATH['upload_json_path'])


# step2:Check json files
check_obj = RayvisionCheck(api)
task_id = check_obj.execute(CONFIG_PATH['task_json_path'])


# Step3: Transmission
"""
task.json files and resources are uploaded separately
"""
upload_obj = RayvisionUpload(api)

# step3.1: Upload resource file(upload.json)
upload_obj.upload_asset(upload_json_path=CONFIG_PATH["upload_json_path"])
# step3.2: Upload task.json
upload_obj.upload_config(str(task_id), list(CONFIG_PATH.values()))


# Step4:Submit Task
api.submit(int(task_id))

# Step5:Download
download = RayvisionDownload(api)
# All complete before the automatic start of uniform download.
download.auto_download_after_task_completed([task_id])
# Poll download (automatic download for each completed frame)
download.auto_download([int(1484947)], local_path=r"E:\test", download_filename_format="false")

FAQ

1. What versions of Python does the RenderBus SDK support?

RenderBus SDK currently supports Python 2.7 and Python 3.6

2. How to download the SDK package with pycharm?

Please refer to Installation Guide

3. To download only the first frame, how to set?

from rayvision_api.utils import update_task_info
update_task = {
     "pre_frames": "100",
 }
 update_task_info(update_task, task_path=r"C:\workspace\1586932339\task.json")

4. After the priority frame rendered, how to set to automatically render at full speed?

from rayvision_api.utils import update_task_info
update_task = {
     "stop_after_test": "1"
 }
update_task_info(update_task, task_path=r"C:\workspace\1586932339\task.json")

For details, please refer to Detailed Parameter Configuration

5. How to set to download the rendering result immediately after current rendered frame rendered?

We provide 2 downloading methods:

  • Download after all frames finish rendering
  • Download after current frame finishes rendering

For details, please refer to SDK Usage

6. What is the easiest way to use?

If you want to use it directly without customization, you can download the corresponding rendering package directly, then select the corresponding [common full process sample] to experience the full process rendering. For details, please refer to the SDK Getting Started Tutorial

Exception code

code symbol description
100 FAIL failed
200 SUCCESS returns successfully
301 NEED_REDIRECT need to redirect to other addresses
400 APIError error request
403 FORBIDDEN no permission
404 RESOURCE_NOT_FOUND resource does not exist
500 INTERNAL_ERROR server processing failed
513 USER_CACHE_NOTFOUNT user_message_find_fail
600 PARAMETER_INVALID illegal parameter
601 PARAMETER_CANT_BE_EMPTY missing required parameters
602 NEED_USER_LOGIN requires user login
603 ILLEGAL_PROTOCOL illegal request
604 VALIDATE_CODE_ERROR mobile verification code error
605 VINSUFFICIENT_PERMISSIONS insufficient permissions
606 VALIDATE_COMMOM_CODE_ERROR verification code error
607 VALIDATE_SEND_CODE_ERROR verification code failed to send
608 USER_AREA_ERROR customer’s domestic and foreign regions do not match
610 SIGNATURE_EXPIRED signature expired
611 SIGNATURE_INVALID invalid signature
700 DO_NOT_HAVE_ANY_MORE_RECORD no more records
800 ACCOUNT_BINDING_USER_NULL account does not exist
801 ACCOUNT_NOT_BINDING device not bound
802 ACCOUNT_BINDING_FAIL device binding failed
804 ACCOUNT_LOCKED account disabled
805 ACCOUNT_USERNAME_PASSWORD_FAIL username/password invalid
806 ACCOUNT_UNIONID_FAIL account is not bound to a third-party user
807 ACCOUNT_PHONE_FAIL phone number is not bound to a third-party user
808 ACCOUNT_UNIONID_PHONE phone number is already bound to other user
809 ACCOUNT_WEIXIN_FAIL Wechat login failed
810 ACCOUNT_WEIBO_FAIL Weibo login failed
811 ACCOUNT_LOGOUT_FAIL logout failed
812 ACCOUNT_LOGIN_IPLIMITFAIL IP address is prohibited
813 ACCOUNT_QQ_FAIL QQ login failed
814 NOREPEAT_SELECT_SOFTWARE unable to select common software repeatedly
815 ACCOUNT_UNIONID_EXISTS UNIONID already exists
900 VALIDATE_PHONE_FAIL phone number already exists
901 VALIDATE_EMAIL_FAIL mailbox already exists
902 VALIDATE_USERNAME_FAIL username already exists
903 ACCOUNT_EMAIL_FAIL mailbox is not bound to an account
904 CURRENCY_NOT_SUPPORT unsupported currency
905 AGENT_NOT_SUPPORT unsupport agent
906 AMOUNT_NOT_SUPPORT please enter a reasonable recharge value
908 COUPONNO_NOT_SUPPORT coupon code is not supported
909 PAYMETHOD_NOT_SUPPORT unsupported payment method
910 NO_INVOICE_ORDER invoice order unavailable
911 NO_INVOICE_ADDRESS invoice order address unavailable
912 SUBUSER_EXISTS_TASKS unable to delete a sub-user with executing tasks
913 SUBUSER_ARREARAGE sub-user is overdue
914 DELSUBUSER_EXISTS_BALANCE there is balance for the sub-user to be deleting
915 NO_INVOICE_TEMPLATE invoice information unavailable
916 RECEIPT_TYPE_ERROR invoice type not match
920 NO_LATEST_VERSION no latest client version
1000 REDIS_CACHE_FAIL redis cache exception
20004 JSON_FILE_UPLOAD_FAILED Uploading json file has failed many times, please check the network environment
200024 ARGUMENT_FORMAT_INVALID The transfer parameter name is set incorrectly. Please check the transfer CMD command
200025 NON-UPLOADABLE FILES Unable to upload the file, check if the file exists or if the file is damaged
1000000 RayvisionError python exception

Release notes

0.1.0 (2019-11-10):

  • First edition

1.1.0 (2020-04-06):

Major update:
  • rayvision_api: Partially passed parameters were updated to check for functional refactoring
  • rayvision_clarisse: Added independent native analysis. Clarissa analysis supports python2
  • rayvision_maya: Added independent local analysis capability
  • rayvision_houdini: Added independent local analysis capability
  • rayvision_sync: Support to upload json configuration and resource files, download support to customize the server file path, support whether to use local comparison function

1.2 (2020-05-21):

  • The fix section describes the error.
  • Add the upload json file interface and instructions on how to use it.

1.3 (2020-09-10):

  • The fix section describes the error.
  • Update the API interface to API2.0.
  • Add katana-related documentation.

1.4 (2020-11-12):

rayvision_log(tag 1.1.2):
  • Compatibility Problem python2 Version Log Module in Fix Part.

1.5 (2020-11-24):

rayvision_sync(tag 2.0):
  • Update Transmission aspera Engine.
  • Support raysync engine transmission.

1.6 (2020-12-16):

rayvision_api(tag 2.4.5):
  • Add new interface;
  • Fixes an insanity in the name of the main sub-account query item;

Contribute to the RenderBusSDK

Important

Please check carefully, you are https://renderbus.readthedocs.io/en/latest/index.html on reading the latest version of this document.

There are many ways to contribute to the RenderBusSDK, and here are some of them:

  • Report errors and requests in the problem tracker, and try to follow the guidelines detailed in reporting errors below.

Report error

  • Please check the FAQ first in case that your issue is resolved already.
  • Check unresolved issues to see if the problem’s been reported. If yes, review comments to get more info.
  • Submit complete reports including platform, software_version, error log, etc. Try to provide a small test scene with which our engineers could position your problem.

Indices and tables