mirror of
https://github.com/ynput/ayon-core.git
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removing old collector
This commit is contained in:
Ondrej Samohel
parent
0253722254
commit
85d8af5dec
1 changed files with 0 additions and 512 deletions
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@ -1,512 +0,0 @@
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"""
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Requires:
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environment -> PYPE_PUBLISH_PATHS
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context -> workspaceDir
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Provides:
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context -> user (str)
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instance -> new instance
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"""
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import os
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import re
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import copy
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import json
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import pyblish.api
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from avalon import api
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from pypeapp import PypeLauncher
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def collect(root,
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regex=None,
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exclude_regex=None,
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frame_start=None,
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frame_end=None):
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"""Collect sequence collections in root"""
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from avalon.vendor import clique
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files = list()
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for filename in os.listdir(root):
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# Must have extension
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ext = os.path.splitext(filename)[1]
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if not ext:
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continue
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# Only files
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if not os.path.isfile(os.path.join(root, filename)):
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continue
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# Include and exclude regex
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if regex and not re.search(regex, filename):
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continue
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if exclude_regex and re.search(exclude_regex, filename):
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continue
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files.append(filename)
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# Match collections
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# Support filenames like: projectX_shot01_0010.tiff with this regex
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pattern = r"(?P<index>(?P<padding>0*)\d+)\.\D+\d?$"
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collections, remainder = clique.assemble(files,
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patterns=[pattern],
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minimum_items=1)
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# Exclude any frames outside start and end frame.
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for collection in collections:
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for index in list(collection.indexes):
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if frame_start is not None and index < frame_start:
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collection.indexes.discard(index)
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continue
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if frame_end is not None and index > frame_end:
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collection.indexes.discard(index)
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continue
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# Keep only collections that have at least a single frame
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collections = [c for c in collections if c.indexes]
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return collections, remainder
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class CollectRenderedFrames(pyblish.api.ContextPlugin):
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"""Gather file sequences from working directory
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When "FILESEQUENCE" environment variable is set these paths (folders or
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.json files) are parsed for image sequences. Otherwise the current
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working directory is searched for file sequences.
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The json configuration may have the optional keys:
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asset (str): The asset to publish to. If not provided fall back to
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api.Session["AVALON_ASSET"]
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subset (str): The subset to publish to. If not provided the sequence's
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head (up to frame number) will be used.
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frame_start (int): The start frame for the sequence
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frame_end (int): The end frame for the sequence
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root (str): The path to collect from (can be relative to the .json)
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regex (str): A regex for the sequence filename
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exclude_regex (str): A regex for filename to exclude from collection
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metadata (dict): Custom metadata for instance.data["metadata"]
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"""
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order = pyblish.api.CollectorOrder - 0.0001
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targets = ["filesequence"]
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label = "RenderedFrames"
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active = False
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def process(self, context):
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pixel_aspect = 1
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resolution_width = 1920
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resolution_height = 1080
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lut_path = None
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slate_frame = None
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families_data = None
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baked_mov_path = None
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subset = None
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version = None
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frame_start = 0
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frame_end = 0
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new_instance = None
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if os.environ.get("PYPE_PUBLISH_PATHS"):
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paths = os.environ["PYPE_PUBLISH_PATHS"].split(os.pathsep)
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self.log.info("Collecting paths: {}".format(paths))
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else:
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cwd = context.get("workspaceDir", os.getcwd())
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paths = [cwd]
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for path in paths:
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self.log.info("Loading: {}".format(path))
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if path.endswith(".json"):
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# Search using .json configuration
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with open(path, "r") as f:
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try:
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data = json.load(f)
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except Exception as exc:
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self.log.error(
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"Error loading json: "
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"{} - Exception: {}".format(path, exc)
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)
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raise
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cwd = os.path.dirname(path)
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root_override = data.get("root")
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frame_start = int(data.get("frameStart"))
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frame_end = int(data.get("frameEnd"))
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subset = data.get("subset")
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if root_override:
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if os.path.isabs(root_override):
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root = root_override
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else:
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root = os.path.join(cwd, root_override)
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else:
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root = cwd
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if data.get("ftrack"):
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f = data.get("ftrack")
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os.environ["FTRACK_API_USER"] = f["FTRACK_API_USER"]
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os.environ["FTRACK_API_KEY"] = f["FTRACK_API_KEY"]
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os.environ["FTRACK_SERVER"] = f["FTRACK_SERVER"]
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metadata = data.get("metadata")
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if metadata:
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session = metadata.get("session")
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if session:
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self.log.info("setting session using metadata")
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api.Session.update(session)
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os.environ.update(session)
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instance = metadata.get("instance")
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if instance and isinstance(instance, list):
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instance_family = instance.get("family")
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pixel_aspect = instance.get("pixelAspect", 1)
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resolution_width = instance.get(
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"resolutionWidth", 1920)
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resolution_height = instance.get(
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"resolutionHeight", 1080)
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lut_path = instance.get("lutPath", None)
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baked_mov_path = instance.get("bakeRenderPath")
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families_data = instance.get("families")
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slate_frame = instance.get("slateFrame")
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version = instance.get("version")
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else:
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# Search in directory
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data = dict()
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root = path
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self.log.info("Collecting: {}".format(root))
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regex = data.get("regex")
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if baked_mov_path:
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regex = "^{}.*$".format(subset)
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if regex:
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self.log.info("Using regex: {}".format(regex))
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if "slate" in families_data:
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frame_start -= 1
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if regex:
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collections, remainder = collect(
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root=root,
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regex=regex,
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exclude_regex=data.get("exclude_regex"),
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frame_start=frame_start,
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frame_end=frame_end,
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)
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self.log.info("Found collections: {}".format(collections))
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self.log.info("Found remainder: {}".format(remainder))
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fps = data.get("fps", 25)
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# adding publish comment and intent to context
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context.data["comment"] = data.get("comment", "")
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context.data["intent"] = data.get("intent", "")
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if data.get("user"):
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context.data["user"] = data["user"]
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if data.get("version"):
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version = data.get("version")
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# Get family from the data
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families = data.get("families", ["render"])
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if "ftrack" not in families:
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families.append("ftrack")
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if families_data and "render2d" in families_data:
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families.append("render2d")
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if families_data and "slate" in families_data:
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families.append("slate")
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if not isinstance(instance, list):
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instances = [instance]
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# attachTo must be only on single instance
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if instances[0].get("attachTo"):
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# we need to attach found collections to existing
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# subset version as review represenation.
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for attach in instances[0].get("attachTo"):
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self.log.info(
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"Attaching render {}:v{}".format(
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attach["subset"], attach["version"]))
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new_instance = context.create_instance(
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attach["subset"])
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new_instance.data.update(
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{
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"name": attach["subset"],
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"subset": attach["subset"],
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"version": attach["version"],
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"family": 'review',
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"families": ['review', 'ftrack'],
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"asset": data.get(
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"asset", api.Session["AVALON_ASSET"]),
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"stagingDir": root,
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"frameStart": frame_start,
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"frameEnd": frame_end,
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"fps": fps,
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"source": data.get("source", ""),
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"pixelAspect": pixel_aspect,
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"resolutionWidth": resolution_width,
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"resolutionHeight": resolution_height
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})
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if regex:
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if "representations" not in new_instance.data:
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new_instance.data["representations"] = []
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for collection in collections:
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self.log.info(
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" - adding representation: {}".format(
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str(collection))
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)
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ext = collection.tail.lstrip(".")
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representation = {
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"name": ext,
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"ext": "{}".format(ext),
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"files": list(collection),
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"stagingDir": root,
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"anatomy_template": "render",
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"fps": fps,
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"tags": ["review"],
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}
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new_instance.data["representations"].append(
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representation)
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else:
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try:
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representations = data["metadata"]["instance"]["representations"] # noqa: E501
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except KeyError as e:
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assert False, e
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new_instance.data["representations"] = representations
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elif subset:
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# if we have subset - add all collections and known
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# reminder as representations
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# take out review family if mov path
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# this will make imagesequence none review
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if baked_mov_path:
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self.log.info(
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"Baked mov is available {}".format(
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baked_mov_path))
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families.append("review")
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if session['AVALON_APP'] == "maya":
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families.append("review")
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self.log.info(
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"Adding representations to subset {}".format(
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subset))
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new_instance = context.create_instance(subset)
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data = copy.deepcopy(data)
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new_instance.data.update(
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{
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"name": subset,
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"family": families[0],
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"families": list(families),
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"subset": subset,
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"asset": data.get(
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"asset", api.Session["AVALON_ASSET"]),
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"stagingDir": root,
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"frameStart": frame_start,
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"frameEnd": frame_end,
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"fps": fps,
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"source": data.get("source", ""),
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"pixelAspect": pixel_aspect,
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"resolutionWidth": resolution_width,
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"resolutionHeight": resolution_height,
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"slateFrame": slate_frame,
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"version": version
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}
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)
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if "representations" not in instance.data:
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instance.data["representations"] = []
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for collection in collections:
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self.log.info(" - {}".format(str(collection)))
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ext = collection.tail.lstrip(".")
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if "slate" in instance.data["families"]:
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frame_start += 1
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representation = {
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"name": ext,
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"ext": "{}".format(ext),
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"files": list(collection),
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"frameStart": frame_start,
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"frameEnd": frame_end,
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"stagingDir": root,
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"anatomy_template": "render",
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"fps": fps,
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"tags": ["review"] if not baked_mov_path else ["thumb-nuke"],
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}
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instance.data["representations"].append(
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representation)
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if regex:
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for collection in collections:
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self.log.info(" - {}".format(str(collection)))
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ext = collection.tail.lstrip(".")
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if "slate" in new_instance.data["families"]:
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frame_start += 1
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representation = {
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"name": ext,
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"ext": "{}".format(ext),
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"files": list(collection),
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"frameStart": frame_start,
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"frameEnd": frame_end,
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"stagingDir": root,
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"anatomy_template": "render",
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"fps": fps,
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"tags": ["review"] if not baked_mov_path else [],
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}
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new_instance.data["representations"].append(
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representation)
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# filter out only relevant mov in case baked available
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self.log.debug("__ remainder {}".format(remainder))
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if baked_mov_path:
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remainder = [r for r in remainder
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if r in baked_mov_path]
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self.log.debug("__ remainder {}".format(remainder))
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# process reminders
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for rem in remainder:
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# add only known types to representation
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if rem.split(".")[-1] in ['mov', 'jpg', 'mp4']:
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self.log.info(" . {}".format(rem))
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if "slate" in instance.data["families"]:
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frame_start += 1
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tags = ["preview"]
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if baked_mov_path:
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tags.append("delete")
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representation = {
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"name": rem.split(".")[-1],
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"ext": "{}".format(rem.split(".")[-1]),
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"files": rem,
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"stagingDir": root,
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"frameStart": frame_start,
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"anatomy_template": "render",
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"fps": fps,
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"tags": tags
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}
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new_instance.data["representations"].append(
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representation)
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else:
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try:
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representations = data["metadata"]["instance"]["representations"] # noqa: E501
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except KeyError as e:
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assert False, e
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new_instance.data["representations"] = representations
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else:
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# we have no subset so we take every collection and create one
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# from it
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# Ensure each instance gets a unique reference to the data
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data = copy.deepcopy(data)
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# If no subset provided, get it from collection's head
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subset = data.get("subset", collection.head.rstrip("_. "))
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# If no start or end frame provided, get it from collection
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indices = list(collection.indexes)
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start = int(data.get("frameStart", indices[0]))
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end = int(data.get("frameEnd", indices[-1]))
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new_instance.append(collection)
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new_instance.context.data["fps"] = fps
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if "representations" not in new_instance.data:
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new_instance.data["representations"] = []
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representation = {
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"name": ext,
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"ext": "{}".format(ext),
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"files": list(collection),
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"frameStart": start,
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"frameEnd": end,
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"stagingDir": root,
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"anatomy_template": "render",
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"fps": fps,
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"tags": ["review"],
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}
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new_instance.data["representations"].append(
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representation)
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# temporary ... allow only beauty on ftrack
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if session['AVALON_APP'] == "maya":
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AOV_filter = ['beauty']
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for aov in AOV_filter:
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if aov not in new_instance.data['subset']:
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new_instance.data['families'].remove(
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'review')
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new_instance.data['families'].remove(
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'ftrack')
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representation["tags"].remove('review')
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else:
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data = copy.deepcopy(data)
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if not isinstance(data["metadata"]["instance"], list):
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instances = [data["metadata"]["instance"]]
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for instance in instances:
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subset = instance["subset"]
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task = data["metadata"]["session"]["AVALON_TASK"]
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new_subset_name = 'render{}{}{}{}'.format(
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task[0].upper(), task[1:],
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subset[0].upper(), subset[1:])
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self.log.info(
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"Creating new subset: {}".format(new_subset_name))
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new_instance = context.create_instance(new_subset_name)
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new_instance.data.update(
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{
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"name": new_subset_name,
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"family": 'render',
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"families": data["metadata"]["families"],
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"subset": new_subset_name,
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"asset": data.get(
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"asset", api.Session["AVALON_ASSET"]),
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"stagingDir": root,
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"frameStart": frame_start,
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"frameEnd": frame_end,
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"fps": fps,
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"source": data.get("source", ""),
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"pixelAspect": pixel_aspect,
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"resolutionWidth": resolution_width,
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"resolutionHeight": resolution_height,
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"slateFrame": slate_frame
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}
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)
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new_instance.data["representations"] = instance["representations"] # noqa: E501
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if new_instance is not None:
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self.log.info("remapping paths ...")
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new_instance.data["representations"] = [PypeLauncher().path_remapper(data=r) for r in new_instance.data["representations"]] # noqa: E501
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self.log.debug(
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"__ representations {}".format(
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new_instance.data["representations"]))
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self.log.debug(
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"__ instance.data {}".format(new_instance.data))
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else:
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self.log.error("nothing collected")
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