]jmdZddlZddlZddlZddlZddlZddlmZmZddlm Z ddl m Z m Z ddl mZmZmZmZmZddlmZddlmZdd lmZdd lmZmZmZd d lmZd d lmZm Z ejBe"Z#Gdde$Z%Gdde%Z&GddeZ'GddeZ(GddeZ)GddZ*GddeZ+y)z .. include::../docs/project.md N)Enumauto)Path)sampleshuffle)OptionalUnionListDictCallable) parse_config)get_local_path)Response) HTTPError InvalidSchema MissingSchema)Client)r chunkc eZdZy)LabelStudioExceptionN__name__ __module__ __qualname__J/root/env/lib/python3.12/site-packages/label_studio_sdk/_legacy/project.pyrrrrc eZdZy)LabelStudioAttributeErrorNrrrrr!r!rrr!c eZdZdZdZ dZ dZy)ProjectSamplingz9Enumerate the available task sampling modes for labeling.zUniform samplingzSequential samplingzUncertainty samplingN)rrr__doc__RANDOMSEQUENCE UNCERTAINTYrrrr#r#!sC F,$H7(Karr#c2eZdZdZdZ dZ dZ dZ dZ dZ y) ProjectStoragezZEnumerate the available types of external source and target storage for labeling projects.gcss3 azure_blob localfilesrediss3sN) rrrr$GOOGLES3AZURELOCALREDIS S3_SECUREDrrrr)r),s5d F B E( E+ EJDrr)ceZdZeZy)AssignmentSamplingMethodN)rrrrr%rrrr7r7=s VFrr7cBeZdZdZ dZ dZ dZ dZdZdZ dZ d Z y ) ExportSnapshotStatuscreated in_progressfailed completedc||_yN)responseselfr@s r__init__zExportSnapshotStatus.__init__Ks   rcdd|jvsJd|jd|jk(S)zExport snapshot is createdstatusz;"status" field not found in export snapshot status response)r@CREATEDrBs r is_createdzExportSnapshotStatus.is_createdNs:  % I H I %}}X&$,,66rcdd|jvsJd|jd|jk(S)zExport snapshot is in progressrE;"status" field not found in export_snapshot_status response)r@ IN_PROGRESSrGs ris_in_progressz#ExportSnapshotStatus.is_in_progressUs<  % I H I %}}X&$*:*:::rcdd|jvsJd|jd|jk(S)z"Export snapshot failed with errorsrErJ)r@FAILEDrGs r is_failedzExportSnapshotStatus.is_failed\s:  % I H I %}}X&$++55rcdd|jvsJd|jd|jk(S)z1Export snapshot was created and can be downloadedrErJ)r@ COMPLETEDrGs r is_completedz!ExportSnapshotStatus.is_completedcs:  % I H I %}}X&$..88rN) rrrrFrKrNrQrCrHrLrOrRrrrr9r9As;G&K+ F.I=!7;69rr9ceZdZfdZdZedZdZdZdZ dZ dZ d Z d Z d Zd Zd ZdZeddZeddZddefdZ ddedededeeedeedeeej<ff dZdZ de!fdZ"defdZ#d efd!Z$ dd"efd#Z% dd%ed&ed"ed'efd(Z&d)Z'd*Z(d+Z)dd,Z*d-Z+ed.Z,ed/Z-dd0Z.d1Z/dd2Z0d3Z1d4Z2d5Z3 dd6ed7eeee4e4efd8ee5d eefd9Z6d:Z7dd;Z8d6edefd<Z9d6ede4fd=Z:d>ede;fd?ZedefdAZ>dBZ?dCZ@dDZA ddEedFeedGeedHeedIeedJeedKeedLeedMeefdNZB ddEedFeedIeedLeedMeedOef dPZC ddEedFeedGeedHeedJeedKeedLeedMeedQeedReedSeedTeedUeedVeefdWZD ddXedYeedEeedFeedGeedHeedJeedKeedLeedMeedTeedUeedVeedZeefd[ZE ddEedFeedLeedMeedQeedReedSeedTeedUeedOefd\ZF dd]edFeedGeedHeedJeedKeedLeedMeed^eed_eefd`ZG dd]edFeedLeedMeed^eed_eedOefdaZH ddbegdGeedHeedLeedMeef dcZIddZJdeZKdfZLdgZMdeNjdhd$fdieedjePdkedleNdme5dnef doZQdeNjdhd$fdieedkedleNdme5dnef dpZRdeNjdhd$fdieedkedleNdme5dnef dqZSdefdrZT ddLedse;dteduedvedwedxedyedzede;fd{ZU dd|ZVd}edeWfd~ZX dd}edededeeffdZYd}edefdZZdde4defdZ[d6ede\fdZ]dede\fdZ^ddede\fdZ_xZ`S)Projectc:tt| |i|i|_y)zJInitialize project class. Parameters ---------- N)superrTrCparams)rBargskwargs __class__s rrCzProject.__init__ls  gt%t6v6 rc$|j|Sr?) _get_param)rBitems r __getattr__zProject.__getattr__vst$$rc,t|jS)ayGet the parsed labeling configuration for the project. You can use this to more easily construct annotation or prediction results based on your labeling configuration. Returns ------- dict Object and control tags from the project labeling configuration. Example with structured configuration of the form: ``` { ".name": { "type": "ControlTag", "to_name": [".name", ".name"], "inputs: [ {"type": "ObjectTag1", "value": ".value"}, {"type": "ObjectTag2", "value": ".value"} ], "labels": ["Label1", "Label2", "Label3"] } ``` `"labels"` are taken from "alias" attribute if it exists, else "value" )r label_configrGs rparsed_label_configzProject.parsed_label_configys0D--..rcddlm}|jsJd|jdd|jd}g}|j D]}||d<|j |di| |S) zGet members from this project. Parameters ---------- Returns ------- list of `label_studio_sdk.users.User` r)UserzfProject members are available in the Enterprise edition of Label Studio only. Use get_users() instead.GET/api/projects//membersclientr)usersrc is_enterprise make_requestidjsonappend)rBrcr@rh user_datas r get_memberszProject.get_memberss !!  ' ! $$UnTWWIX,NO! ,I"&Ih  LL* * + , rcd|ji}|jdd|jd|}|jS)zAdd a user to a project. Parameters ---------- user: User Returns ------- dict Dict with created member userPOSTrerfrlrkrjrl)rBrqpayloadr@s r add_memberzProject.add_membersI477#$$ nTWWIX6W% }}rc.ddi}|Dcgc]}|j}}t|dD]c}tjd||d|ddd}|j d d |jd | }|dxx|j dz cc<e|Scc}w) aAssign annotators to tasks Parameters ---------- users: list of user's objects tasks_ids: list of integer task IDs to assign users to Returns ------- dict Dict with counter of created assignments assignmentsrizStarting assignment for: FallincludedANrh selectedItemstyperrre/tasks/assigneesrs)rkrloggerdebugrjrl) rBrh tasks_idsfinal_responserq users_idscrur@s rassign_annotatorszProject.assign_annotatorss(+)./TWW/ /y$' LA LL4YK@ A").A!>G ((. 1AB)H = )X]]_]-K K ) L0sBcrdd|di}|jdd|j|}|jS)zRemove all assigned annotators for tasks Parameters ---------- tasks_ids: list of int Returns ------- dict Dict with counter of deleted annotator assignments r~Fryrrz-/api/dm/actions?id=delete_annotators&project=rsrjrkrlrBrrur@s rdelete_annotators_assignmentz$Project.delete_annotators_assignmentsJ#Ey$IJ$$ ;DGG9 E%  }}rcrdd|di}|jdd|j|}|jS)zClear all assigned reviewers for tasks Parameters ---------- tasks_ids: list of int Returns ------- dict Dict with counter of deleted reviewer assignments r~Fryrrz,/api/dm/actions?id=delete_reviewers&project=rsrrs rdelete_reviewers_assignmentz#Project.delete_reviewers_assignmentsJ#Ey$IJ$$ :477) D%  }}rc|Dcgc]}|jc}d|ddd}|jdd|jd|}|jScc}w) aAssign reviewers to tasks Parameters ---------- users: list of user's objects tasks_ids: list of integer task IDs to assign reviewers to Returns ------- dict Dict with counter of created assignments FryREr}rrrerrsrt)rBrhrrqrur@s rassign_reviewerszProject.assign_reviewerssg+00$dgg0%* B  $$ nTWWI-=>W% }}1sAc||jvr-|j||jvrtd|d|j|S)Nz Project "z" field is not set)rW update_paramsr!)rB param_names rr\zProject._get_paramsQ T[[ (    ,/ |+=>{{:&&rc`|jdd|j}|jS)aQ Get all available project parameters. Returns -------- dict containing all following params: title: str Project name. description: str Project description label_config: str Label config in XML format. expert_instruction: str Labeling instructions in HTML format show_instruction: bool Whether to display instructions to annotators before they start show_skip_button: bool Whether to show a skip button in the Label Studio UI and let annotators skip the task enable_empty_annotation: bool Allow annotators to submit empty annotations show_annotation_history: bool Show annotation history to annotator organization: int Organization ID color: str Color to decorate the project card in the Label Studio UI maximum_annotations: int Maximum number of annotations for one task. If the number of annotations per task is equal or greater to this value, the task is finished and is_labeled=True is set. (Enterprise only) is_published: bool Whether or not the project is published to annotators (Enterprise only) model_version: str Machine learning model version for predictions or pre-annotations is_draft: bool Whether or not the project is in the middle of being created (Enterprise only) created_by: object Details about the user that created the project min_annotations_to_start_training: int Minimum number of completed tasks after which model training is started show_collab_predictions: bool Whether to show model predictions to the annotator, allowing them to collaborate with the ML model sampling: str Type of sampling to use for task labeling. Uncertainty sampling is Enterprise only. Enum: "Sequential sampling" "Uniform sampling" "Uncertainty sampling" show_ground_truth_first: bool Whether to show tasks with ground truth annotations first (Enterprise only) show_overlap_first: bool Whether to show tasks with overlap first (Enterprise only) overlap_cohort_percentage: int Percentage of tasks that must be annotated multiple times. (Enterprise only) task_data_login: str User credentials for accessing task data. (Enterprise only) task_data_password: str Password credentials for accessing task data. (Enterprise only) control_weights: object Weights for control tags used when calculating agreement metrics. (Enterprise only) evaluate_predictions_automatically: bool Retrieve and display predictions when loading a task rdrerrAs r get_paramszProject.get_params(s.|$$UnTWWI,FG}}rcb|jdd|jd}|jS)zGet the list of available ML model versions from pre-annotations or connected ML backends. Returns ------- list of strings Model versions rdrez/model-versionsrrAs rget_model_versionszProject.get_model_versionsis/$$UnTWWI_,UV}}rc.|j|_y)zdGet [all available project parameters](#label_studio_sdk.project.Project.get_params) and cache them.N)rrWrGs rrzProject.update_paramsusoo' rc |jdd|}|jdk(r|j|_yt d)a\ Create a new labeling project in Label Studio. Parameters ---------- title: str Project name. description: str Project description label_config: str Label config in XML format. expert_instruction: str Labeling instructions in HTML format show_instruction: bool Whether to display instructions to annotators before they start show_skip_button: bool Whether to show a skip button in the Label Studio UI and let annotators skip the task enable_empty_annotation: bool Allow annotators to submit empty annotations show_annotation_history: bool Show annotation history to annotator organization: int Organization ID color: str Color to decorate the project card in the Label Studio UI maximum_annotations: int Maximum number of annotations for one task. If the number of annotations per task is equal or greater to this value, the task is finished and is_labeled=True is set. (Enterprise only) is_published: bool Whether or not the project is published to annotators (Enterprise only) model_version: str Machine learning model version for predictions or pre-annotations is_draft: bool Whether or not the project is in the middle of being created (Enterprise only) created_by: object Details about the user that created the project min_annotations_to_start_training: int Minimum number of completed tasks after which model training is started show_collab_predictions: bool Whether to show model predictions to the annotator, allowing them to collaborate with the ML model sampling: str Type of sampling to use for task labeling. Uncertainty sampling is Enterprise only. Enum: "Sequential sampling" "Uniform sampling" "Uncertainty sampling" show_ground_truth_first: bool Whether to show tasks with ground truth annotations first (Enterprise only) show_overlap_first: bool Whether to show tasks with overlap first (Enterprise only) overlap_cohort_percentage: int Percentage of tasks that must be annotated multiple times. (Enterprise only) task_data_login: str User credentials for accessing task data. (Enterprise only) task_data_password: str Password credentials for accessing task data. (Enterprise only) control_weights: object Weights for control tags used when calculating agreement metrics. (Enterprise only) evaluate_predictions_automatically: bool Retrieve and display predictions when loading a task Raises LabelStudioException in case of errors. rrz /api/projectsrszProject not createdN)rj status_coderlrWrrBrYr@s r start_projectzProject.start_projectysCz$$V_6$J   3 &"--/DK&'<= =rNc||j|j|j|j|j|j }|rt |tr||_||jd<|S)N)urlapi_keysession extra_headersversionsmake_request_raiserk) rrrheadersrr isinstancedictrW)clsrg project_idrWprojects r_create_from_idzProject._create_from_ids` NNNN ..__%88   j.#GN)trreturncJ|j||}|j|S)zClass factory to create a project instance from an existing project ID. Parameters ---------- client: class Client project_id: int Project ID Returns ------- `Project` )rr)rrgrrs r get_from_idzProject.get_from_ids'%%fj9rpreannotated_from_fieldscddi}|rdj||d<t|ttfr%|j dd|j d||d }nt|t tfrjtjj|std |t|d 5}|j dd|j dd |i|d}dddntdt|j}d|vrd}ddg}t!j } |j dd|j d|dj} | ddk(r| dS| ddk(rt| dt!j |z |k\r tdt!j"|d|d|d|dzg}|dS#1swYxYw)aImport JSON-formatted labeling tasks. Tasks can be unlabeled or contain predictions. Parameters ---------- tasks: list of dicts | dict | path to file Tasks in Label Studio JSON format preannotated_from_fields: list of strings Turns flat task JSON formatted like: `{"column1": value, "column2": value}` into Label Studio prediction data format: `{"data": {"column1"..}, "predictions": [{..."column2"}]` Useful when all your data is stored in tabular format with one column dedicated to model predictions. Returns ------- list of int Imported task IDs return_task_ids1,rrrrez/import) iX)methodrrlrWtimeoutzNot found import tasks file rb)modefile)rrfilesrWrNz1Not supported type provided as "tasks" argument: importi,rrdz /imports/)rrrEr=task_idsr<errorzImport timeoutr)joinrlistrrjrkstrrospathisfileropen TypeErrorrrltimesleep) rBtasksrrWr@frfibonacci_backoff start_time import_statuss r import_taskszProject.import_taskss($S) #14:R1SF- . edD\ *(($TWWIW5! )HT{ +77>>%(*-I%+QRRe$' 1,,!( 9!1+!% -  CDK=Q ==? x G!"A J $ 1 1 ( 8H;M:NO!2!$& !*k9(44 *h6.}W/EFF99;+w6./?@@ ,Q/0%a(%a(+ the Label Studio converter code. download_all_tasks: bool Default download_all_tasks is False. If true, download all tasks regardless of status. If false, download only annotated tasks. download_resources: bool Default download_resources is False. If true, download all resource files such as images, audio, and others relevant to the tasks. ids: list of ints Optional, specify a list of task IDs to retrieve only the details for those tasks. export_location: str or path Optional, specify a location to save the export to, this is mandatory for the YOLO export. A pathlib.Path object will be returned instead of the deserialized json. Returns ------- list of dicts if export_location is None Tasks with annotations pathlib.Path if export_location is not None Path to the export ) exportTyperrrrdrez/export)rrrWNJSONz8 export type requires an export location to be specifiedT)parentsexist_okwbi) chunk_size) rjrkupper ValueErrorrlpathlibrparentmkdirr iter_contentwrite) rBrrrrrrWr@ export_pathout_filers r export_taskszProject.export_tasks-sN&"4"4  F5M$$twwiw?%   "[..00 "m#[\==? "ll?3     = +t $ &!../ &u% & &   & s )CCc h|jdd|j|}|jdk(sJy)z-Low level function to set project parameters.PATCHrersNrjrkrrs r set_paramszProject.set_paramsqs8$$Wtwwi.Hv$V##s***rsamplingc<|j|jy)z8Set the project sampling method for the labeling stream.)rN)rvalue)rBrs r set_samplingzProject.set_samplingvs 0r is_publishedc(|j|y)zSet the project publication state. (Enterprise only) Parameters ---------- is_published: bool Project publication state for reviewers and annotators )rNr)rBrs r set_publishedzProject.set_publishedzs \2r model_versionc(|j|y)a9Set the current model version to use for displaying predictions to annotators, perform uncertainty sampling and annotation evaluations in Label Studio Enterprise, and other operations. Parameters ---------- model_version: string It can be any string you want )rNr)rBrs rset_model_versionzProject.set_model_versions m4ronly_idsc d}g}i}|jds8 |j||||||d}||dz }|dz }|jds8|S#t$r#} tj d| Yd} ~ |Sd} ~ wwxYw)aRetrieve a subset of tasks from the Data Manager based on a filter, ordering mechanism, or a predefined view ID. Parameters ---------- filters: label_studio_sdk.data_manager.Filters.create() JSON objects representing Data Manager filters. Use `label_studio_sdk.data_manager.Filters.create()` helper to create it. Example: ```json { "conjunction": "and", "items": [ { "filter": "filter:tasks:id", "operator": "equal", "type": "Number", "value": 1 } ] } ``` ordering: list of label_studio_sdk.data_manager.Column List with one string representing Data Manager ordering. Use `label_studio_sdk.data_manager.Column` helper class. Example: ```[Column.total_annotations]```, ```['-' + Column.total_annotations]``` - inverted order view_id: int View ID, visible as a Data Manager tab, for which to retrieve filters, ordering, and selected items selected_ids: list of ints Task IDs only_ids: bool If true, return only task IDs Returns ------- list Task list with task data, annotations, predictions and other fields from the Data Manager rend_paginationd)filtersorderingview_id selected_idsrpage page_sizerzError during pagination: N)getget_paginated_tasksrrr) rBrrrrrrresultdataes r get_taskszProject.get_taskssb((+, //#%#!-%!0$w-' ((+,  (  8<=  s%A A>A99A>rrr resolve_uric ||xsg|rd|dndgdd} |j|||tj| d|d} |rd| d <|jd d | d } | jd k(rgddS| jdk7r"|j |  | j | j} | d}|r|Dcgc]}|d c}| d<| S#t$r} td| d} ~ wwxYwcc}w)aRetrieve a subset of tasks from the Data Manager based on a filter, ordering mechanism, or a predefined view ID. For non-existent pages it returns 404 error. Parameters ---------- filters: label_studio_sdk.data_manager.Filters.create() JSON objects representing Data Manager filters. Use `label_studio_sdk.data_manager.Filters.create()` helper to create it. Example: { "conjunction": "and", "items": [ { "filter": "filter:tasks:id", "operator": "equal", "type": "Number", "value": 1 } ] } ordering: list of label_studio_sdk.data_manager.Column List with one string representing Data Manager ordering. Use `label_studio_sdk.data_manager.Column` helper class. Example: ```[Column.total_annotations]```, ```['-' + Column.total_annotations]``` - inverted order view_id: int View ID, visible as a Data Manager tab, for which to retrieve filters, ordering, and selected items selected_ids: list of ints Task IDs page: int Page. Default is 1. page_size: int Page size. Default is 100, to retrieve all tasks in the project you can use get_tasks(). only_ids: bool If true, return only task IDs resolve_uri: bool Resolve pre-sign urls to https links Returns ------- dict Example: { "tasks": [{...}], "total_annotations": 50, "total_predictions": 100, "total": 100 } tasks: list of dicts Tasks with task data, annotations, predictions and other fields from the Data Manager total: int Total number of tasks in filtered result total_annotations: int Total number of annotations in filtered tasks total_predictions: int Total number of predictions in filtered tasks FryTrzexcluded)rrr~rz)rrrviewqueryfieldsrrkincluderdz /api/tasks)raise_exceptionsi)rrrzError loading tasks: Nr) rkrldumpsrjrlog_response_errorraise_for_statusrr)rBrrrrrrrrr rWr@rrrtasks rrzProject.get_paginated_taskss/V B <8!r2  ww"ZZ&&   $F9 $$ <%%    3 &48 8  ! !S (  # #H - H))+}}W  49:DT$Z:DM  H*-B1#+FGG H ;s C 8 C+ C(C##C(c0d|d<|j|i|S)zQSame as `label_studio_sdk.project.Project.get_tasks()` but returns only task IDs.TrrrBrXrYs r get_tasks_idszProject.get_tasks_idsJs"!zt~~t.v..rc0d|d<|j|i|S)zlSame as `label_studio_sdk.project.Project.get_paginated_tasks()` but returns only task IDs. Tr)rrs rget_paginated_tasks_idszProject.get_paginated_tasks_idsOs&"z't''888rc`|jdd|j}|jS)aGet all views related to the project Returns ------- list List of view dicts The each dict contains the following fields: id: int View ID project: int Project ID user: int User ID who created this tab data: dict Filters, orderings and other visual settings rdz/api/dm/views?project=rrAs r get_viewszProject.get_viewsVs.$$$U.DTWWI,NO}}rcp|j|||dd}|jdd|}|jS)akCreate view Parameters ---------- filters: dict Specify the filters(`label_studio_sdk.data_manager.Filters`) of the view ordering: list of label_studio_sdk.data_manager.Column List with one string representing Data Manager ordering. Use `label_studio_sdk.data_manager.Column` helper class. Example: ```[Column.total_annotations]```, ```['-' + Column.total_annotations]``` - inverted order title: str Tab name Returns ------- dict: dict with created view )titlerr)rrrrz /api/dm/viewsrsrt)rBrrrrr@s r create_viewzProject.create_viewksA*ww#gN $$V_4$H}}rc.|jdd|}y)zDelete view Parameters ---------- view_id: int View ID Returns ------- dict: dict with deleted view DELETEz/api/dm/views/N)rj)rBrr@s r delete_viewzProject.delete_views $$Xy/IJrc"|jS)zbRetrieve all tasks from the project. This call can be very slow if the project has a lot of tasks.rrGs rrz Project.taskss~~rc"|jS)z]IDs for all tasks for a project. This call can be very slow if the project has lots of tasks.)rrGs rrzProject.tasks_idss!!##rc:|jddddddgd|S) a=Retrieve all tasks that have been completed, i.e. where requested number of annotations have been created Parameters ---------- only_ids: bool Return only task IDs. Returns ------- list List of task dicts, the same as in `get_tasks`. andfilter:tasks:completed_atemptyFDatetimefilteroperatorrr conjunctionitemsrrrrBrs rget_labeled_taskszProject.get_labeled_taskss?~~$#>$+!& *    rc&|jdS)zRetrieve all task IDs for completed tasks, i.e. where requested number of annotations have been created Returns ------- list List of task IDs Tr)r.rGs rget_labeled_tasks_idszProject.get_labeled_tasks_idss%%t%44rc:|jddddddgd|S) aRetrieve all tasks that are not completed. If using Label Studio Enterprise, this can include tasks that have been labeled one or more times, but not the full number of times defined in the project labeling settings. Parameters ---------- only_ids: bool Return only task IDs Returns ------- list List of task dicts, the same as in `get_tasks`. r"r#r$Tr%r&r)r,rr-s rget_unlabeled_taskszProject.get_unlabeled_taskss? ~~$#>$+!% *    rc&|jdS)aPRetrieve all task IDs for tasks that are not completed. If using Label Studio Enterprise, this can include tasks that have been labeled one or more times, but not the full number of times defined in the project labeling settings. Returns ------- list List of task IDs Tr0)r3rGs rget_unlabeled_tasks_idszProject.get_unlabeled_tasks_idss'''66rcL|jdd|}|jS)aGet specific task by ID. Parameters ---------- task_id: int Task ID you want to retrieve Returns ------- dict: dict of task data containing all initial data and annotation results in [Label Studio JSON format](https://labelstud.io/guide/tasks.html#Basic-Label-Studio-JSON-format) ``` id: int Task ID predictions: dict Predictions object annotations: dict Annotations object drafts: dict Drafts object data: object User imported or uploaded data for a task. Data is formatted according to the project label config. meta: object Meta is user imported (uploaded) data and can be useful as input for an ML Backend for embeddings, advanced vectors, and other info. It is passed to ML during training/predicting steps. (Deprecated) created_at: str Date time string representing the time a task was created. updated_at: str Date time string representing the last time a task was updated. is_labeled: bool True if the number of annotations for this task is greater than or equal to the number of maximum_completions for the project. overlap: int Number of distinct annotators that processed the current task. project: int Project ID for this task file_upload: str Uploaded file used as data source for this task ``` rd /api/tasks/)rjrlrBtask_idr@s rget_taskzProject.get_tasks*R$$Uk',CD}}rc p|jdd||}|j|jS)aUpdate specific task by ID. Parameters ---------- task_id: int Task ID you want to update kwargs: kwargs parameters List of parameters to update. Check all available parameters [here](https://labelstud.io/api#operation/api_tasks_partial_update) Returns ------- dict: Dict with updated task rr7rsrjrrlrBr9rYr@s r update_taskzProject.update_tasks: $$W G9.EF$S!!#}}rr9rscorec|||d}|||d<|jdd|}|j}tjd||S)aCreate a prediction for a specific task. Parameters ---------- task_id: int Task ID result: list or dict or str Result in the Label Studio JSON format as for annotations. For the labeling config: The following inputs are equivalent, result could be either full `"predictions"`: [{ "from_name": "class_name", "to_name": "image", "type": "choices", "value": { "choices": ["Class A"] } }] or just `"value"` payload {"choices": ["Class A"]} or just the class name: "Class A" score: float Model prediction score model_version: str Any string identifying your model )rrr?rrrz/api/predictionsrsz Response: )rjrlrr)rBr9rr?rrr@rls rcreate_predictionzProject.create_prediction3s\d 6EB  $$1D !$$V-?d$K}} z$() rcf|jdd|jd|}|jS)aBulk create predictions for tasks. See more details about pre-annotated tasks. Parameters ---------- predictions: list of dicts List of dicts with predictions in the Label Studio JSON format as for annotations. rrrez/import/predictionsrsr)rB predictionsr@s rcreate_predictionszProject.create_predictionsms<$$ nTWWI-@A % }}rcdgd|g|jdgdd}|jddd|jd | }|jS) aCreate annotations from all predictions that exist for project tasks from specific ML model versions. Parameters ---------- model_versions: list or None Convert predictions with these model versions to annotations. If `None`, all existing model versions are used Returns ------- dict Dict with counter of created predictions r"r)Tr)rrrrr~rrz/api/dm/actionspredictions_to_annotations)rkr)rWrlrt)rBmodel_versionsrur@s r#create_annotations_from_predictionsz+Project.create_annotations_from_predictions|sb(-r:+ww%)r:  $$  6477K %  }}rcn|jdd|d}|j|jS)zList all annotations for a task. Parameters ---------- task_id: int Task ID Returns ------- list of dict: List of annotations objects rdr7z /annotationsr<r8s rlist_annotationszProject.list_annotationss7$$Uk',,OP!!#}}rc r|jdd|d|}|j|jS)a Add annotations to a task like an annotator does. Parameters ---------- task_id: int Task ID you want to update kwargs: kwargs parameters List of parameters to create. Check all available parameters [here](https://labelstud.io/api#operation/api_tasks_annotations_create). Labeling is stored in the `result` field as a list of dicionaries, [{...}, {...}, ...] Returns ------- dict: Dict with created annotation rrr7z /annotations/rsr<r=s rcreate_annotationzProject.create_annotationsC"$$ k'-8v%  !!#}}r annotation_idcl|jdd|}|j|jS)a&Retrieve a specific annotation for a task using the annotation ID. Parameters ---------- annotation_id: int A unique integer value identifying this annotation. Returns ---------- dict Retreived annotation object rd/api/annotations/r<rBrMr@s rget_annotationzProject.get_annotations6$$U.? ,OP!!#}}rc p|jdd||}|j|jS)aUpdate specific annotation with new annotation parameters, e.g. ``` project.update_annotation(annotation_id=123, ground_truth=True) ``` Parameters ---------- annotation_id: int Existing annotation ID from current project. Could be retrieved from `project.get_tasks()` response kwargs: kwargs parameters List of annotation parameters. Check all available parameters [here](https://labelstud.io/guide/export.html#Label-Studio-JSON-format-of-annotated-tasks) Returns ------- dict Dict with updated annotation rrOrsr<)rBrMrYr@s rupdate_annotationzProject.update_annotationsB&$$ (8v%  !!#}}rcd|jdd|}|j|jS)a,Delete an annotation using the annotation ID. This action can't be undone! Parameters ---------- annotation_id: int A unique integer value identifying this annotation. Returns ---------- int Status code for operation rrO)rjrrrPs rdelete_annotationzProject.delete_annotations6$$X1B=//RS!!####rc|j}|j}|d}|jDcic] \}}|||z  }}}|Scc}}w)apPrediction coverage stats for all model versions for the project. Returns ------- dict Example: { "2021-01-01": 0.9, "2021-02-01": 0.7 } `0.9` means that 90% of project tasks is covered by predictions with model_version `"2021-01-01"` task_number)rrr+)rBrGrW tasks_numberrcountcoverages rget_predictions_coveragez Project.get_predictions_coveragesj 002"m, )7(<(<(> $ u 5</ /    sActr?NotImplementedErrorrGs rget_predictions_conflictz Project.get_predictions_conflict!!rctr?r]rGs rget_predictions_precisionz!Project.get_predictions_precisionr`rbucketprefix regex_filter use_blob_urlsgoogle_application_credentialspresign presign_ttlr descriptionc |rCtjj|r$t|5} | j }ddd||j |||||||| d } |j dd| } | jS#1swYDxYw)aConnect a Google Cloud Storage (GCS) bucket to Label Studio to use as source storage and import tasks. Parameters ---------- bucket: string Specify the name of the GCS bucket prefix: string Optional, specify the prefix or folder within the GCS bucket with your data regex_filter: string Optional, specify a regex filter to use to match the file types of your data use_blob_urls: bool Optional, true by default. Specify whether your data is raw image or video data, or JSON tasks. google_application_credentials: string Optional, provide a file with your Google application credentials. If not specified, it will use path stored in `GOOGLE_APPLICATION_CREDENTIALS` environmental variable. Read more about [Google Cloud authentication](https://cloud.google.com/docs/authentication/getting-started) presign: bool Optional, true by default. Specify whether or not to create presigned URLs. presign_ttl: int Optional, 1 by default. Specify how long to keep presigned URLs active. title: string Optional, specify a title for your GCS import storage that appears in Label Studio. description: string Optional, specify a description for your GCS import storage. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync N) rcrrdrerfrgrhrirrjrrz/api/storages/gcsrsrrrrreadrkrjrl) rBrcrdrerfrgrhrirrjrrur@s rconnect_google_import_storagez%Project.connect_google_import_storagesh *bggnn */ 45 :12. :ww(*.L&&  $$V-@w$O}}! : :s BB can_delete_objectsctjj|r$t|5}|j }ddd|||||||j d}|j dd|} | jS#1swYAxYw)aConnect a Google Cloud Storage (GCS) bucket to Label Studio to use as target storage and export tasks. Parameters ---------- bucket: string Specify the name of the GCS bucket prefix: string Optional, specify the prefix or folder within the GCS bucket to export your data to google_application_credentials: string Optional, provide a file with your Google application credentials. If not specified, it will use path stored in `GOOGLE_APPLICATION_CREDENTIALS` environmental variable. Read more about [Google Cloud authentication](https://cloud.google.com/docs/authentication/getting-started) title: string Optional, specify a title for your GCS export storage that appears in Label Studio. description: string Optional, specify a description for your GCS export storage. can_delete_objects: bool False by default. Specify whether to delete tasks in the GCS bucket if they are deleted in Label Studio. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync N)rcrdrgrrjrorrrz/api/storages/export/gcsrsrl) rBrcrdrgrrjrorrur@s rconnect_google_export_storagez%Project.connect_google_export_storageesV 77>>8 945 :12. :.L&"4ww $$V-Gg$V}} : :s A<<Baws_access_key_idaws_secret_access_keyaws_session_token region_name s3_endpointrecursive_scanc||||| | | | | |||||j|d}|jdd|}|jS)aConnect an Amazon S3 bucket to Label Studio to use as source storage and import tasks. Parameters ---------- bucket: string Specify the name of the S3 bucket. prefix: string Optional, specify the prefix within the S3 bucket to import your data from. regex_filter: string Optional, specify a regex filter to use to match the file types of your data. use_blob_urls: bool Optional, true by default. Specify whether your data is raw image or video data, or JSON tasks. presign: bool Optional, true by default. Specify whether or not to create presigned URLs. presign_ttl: int Optional, 1 by default. Specify how long to keep presigned URLs active. title: string Optional, specify a title for your S3 import storage that appears in Label Studio. description: string Optional, specify a description for your S3 import storage. aws_access_key_id: string Optional, specify the access key ID for your bucket. aws_secret_access_key: string Optional, specify the secret access key for your bucket. aws_session_token: string Optional, specify a session token to use to access your bucket. region_name: string Optional, specify the AWS region of your S3 bucket. s3_endpoint: string Optional, specify an S3 endpoint URL to use to access your bucket instead of the standard access method. recursive_scan: bool Optional, specify whether to perform recursive scan over the bucket content. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync )rcrdrerfrrrsrtrurvrhrirrjrrwrrz/api/storages/s3rsrt)rBrcrdrerfrhrirrjrrrsrtrurvrwrur@s rconnect_s3_import_storagez!Project.connect_s3_import_storagescF(*!2%:!2&&&&ww, "$$V-?g$N}}rrole_arn external_idaws_sse_kms_key_idc||j}|d}||||||| | | || | ||j|d}|jdd|}|jS)aSCreate S3 secured import storage with IAM role access. Enterprise only. Parameters ---------- role_arn: string Required, specify the AWS Role ARN to assume. external_id: string or None Optional, specify the external ID to use to assume the role. If None, SDK will call api/organizations/ and use external_id from the response. You can find this ID on the organization page in the Label Studio UI. bucket: string Specify the name of the S3 bucket. prefix: string Optional, specify the prefix within the S3 bucket to import your data from. regex_filter: string Optional, specify a regex filter to use to match the file types of your data. use_blob_urls: bool Optional, true by default. Specify whether your data is raw image or video data, or JSON tasks. presign: bool Optional, true by default. Specify whether or not to create presigned URLs. presign_ttl: int Optional, 1 by default. Specify how long to keep presigned URLs active. title: string Optional, specify a title for your S3 import storage that appears in Label Studio. description: string Optional, specify a description for your S3 import storage. region_name: string Optional, specify the AWS region of your S3 bucket. s3_endpoint: string Optional, specify an S3 endpoint URL to use to access your bucket instead of the standard access method. recursive_scan: bool Optional, specify whether to perform recursive scan over the bucket content. aws_sse_kms_key_id: string Optional, specify an AWS SSE KMS Key ID for server-side encryption. synchronizable, last_sync, last_sync_count, last_sync_job, status, traceback, meta: Parameters for synchronization details and storage status. Returns ------- dict: containing the response from the API including storage ID and type, among other details. r{)rcrdrerfrhrirrjrwrzrurvr|rr{rrz/api/storages/s3s/rs)get_organizationrkrjrl)rBrzr{rcrdrerfrhrirrjrurvrwr| organizationrur@s rconnect_s3s_iam_import_storagez&Project.connect_s3s_iam_import_storagest  002L&}5K(*&&, &&"4ww& "$$V-A$P}}rc z||||||| ||| |jd } |jdd| } | jS)ajConnect an Amazon S3 bucket to Label Studio to use as target storage and export tasks. Parameters ---------- bucket: string Specify the name of the S3 bucket. prefix: string Optional, specify the prefix or folder within the S3 bucket to export your data to. title: string Optional, specify a title for your S3 export storage that appears in Label Studio. description: string Optional, specify a description for your S3 export storage. aws_access_key_id: string Optional, specify the access key ID for your bucket. aws_secret_access_key: string Optional, specify the secret access key for your bucket. aws_session_token: string Optional, specify a session token to use to access your bucket. region_name: string Optional, specify the AWS region of your S3 bucket. s3_endpoint: string Optional, specify an S3 endpoint URL to use to access your bucket instead of the standard access method. can_delete_objects: bool False by default. Specify whether to delete tasks in the S3 bucket if they are deleted in Label Studio. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync ) rcrdrrrsrtrurvrrjrorrrz/api/storages/export/s3rsrt) rBrcrdrrjrrrsrtrurvrorur@s rconnect_s3_export_storagez!Project.connect_s3_export_storageHsWp!2%:!2&&&"4ww  $$V-FW$U}}r container account_name account_keyc z||||| | |||||jd } |jdd| } | jS)aConnect a Microsoft Azure BLOB storage container to Label Studio to use as source storage and import tasks. Parameters ---------- container: string Specify the name of the Azure container. prefix: string Optional, specify the prefix or folder within the Azure container with your data. regex_filter: string Optional, specify a regex filter to use to match the file types of your data. use_blob_urls: bool Optional, true by default. Specify whether your data is raw image or video data, or JSON tasks. presign: bool Optional, true by default. Specify whether or not to create presigned URLs. presign_ttl: int Optional, 1 by default. Specify how long to keep presigned URLs active. title: string Optional, specify a title for your Azure import storage that appears in Label Studio. description: string Optional, specify a description for your Azure import storage. account_name: string Optional, specify the name of the account with access to the container. account_key: string Optional, specify the key for the account with access to the container. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync ) rrdrerfrrrhrirrjrrrz/api/storages/azurersrt) rBrrdrerfrhrirrjrrrur@s rconnect_azure_import_storagez$Project.connect_azure_import_storagesWn#(*(&&&ww  $$V-B$Q}}rc t||||||||jd}|jdd|} | jS)aNConnect Microsoft Azure BLOB storage to Label Studio to use as target storage and export tasks. Parameters ---------- container: string Specify the name of the Azure storage container. prefix: string Optional, specify the prefix or folder within the Azure container to export your data to. title: string Optional, specify a title for your Azure export storage that appears in Label Studio. description: string Optional, specify a description for your Azure export storage. can_delete_objects: bool False by default. Specify whether to delete tasks in the Azure container if they are deleted in Label Studio. account_name: string Optional, specify the name of the account with access to the container. account_key: string Optional, specify the key for the account with access to the container. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync )rrdrrrrjrorrrz/api/storages/export/azurersrt) rBrrdrrjrrrorur@s rconnect_azure_export_storagez$Project.connect_azure_export_storagesO\#(&&"4ww  $$V-IPW$X}}rlocal_store_pathc dtjvr tdtjd}tjj |st|dt |t |j vdur>ttt |dtt |j |||dd|||jd}|jdd |j| }|jS) a7Connect a Local storage to Label Studio to use as source storage and import tasks. Parameters ---------- local_store_path: string Path to declare as local storage. regex_filter: string Optional, specify a regex filter to use to match the file types of your data use_blob_urls: bool Optional, true by default. Specify whether your data is raw image or video data, or JSON tasks. title: string Optional, specify a title for your GCS import storage that appears in Label Studio. description: string Optional, specify a description for your GCS import storage. Returns ------- dict: containing the same fields as in the request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync &LABEL_STUDIO_LOCAL_FILES_DOCUMENT_ROOTzTo use connect_local_import_storage() you should set LABEL_STUDIO_LOCAL_FILES_DOCUMENT_ROOT environment variable, read more: https://labelstud.io/guide/storage.html#Prerequisites-2z is not a directoryFz/ is not presented in local_store_path parents: r)rerfrrhrirrjrrrz!/api/storages/localfiles?project=rs) renvironrrisdirrrrrkrjrl) rBrrerfrrjrootrur@s rconnect_local_import_storagez$Project.connect_local_import_storagesH 42:: EU  zzBCww}}-. 011DEF F J$/088 8U BtDz?##Rt,-55679  )*$&ww  $$ 7yA% }}rc f|jdd|dt|d}|jS)aSynchronize Import (Source) Cloud Storage. Parameters ---------- storage_type: string Specify the type of the storage container. See ProjectStorage for available types. storage_id: int Specify the storage ID of the storage container. See get_import_storages() to get ids. Returns ------- dict: containing the same fields as in the original storage request and: id: int Storage ID type: str Type of storage created_at: str Creation time last_sync: str Time last sync finished, can be empty. last_sync_count: int Number of tasks synced in the last sync rrz/api/storages///syncrjrrlrB storage_type storage_idr@s rsync_import_storagezProject.sync_import_storageRs;6$$ n\N!C O3DEJ }}rc f|jdd|dt|d}|jS)aSynchronize Export (Target) Cloud Storage. Parameters ---------- storage_type: string Specify the type of the storage container. See ProjectStorage for available types. storage_id: int Specify the storage ID of the storage container. See get_export_storages() to get ids. Returns ------- dict: containing the same fields as in the original storage request and: id: int Storage ID type: str Type of storage created_at: str Creation time other fields: See more https://api.labelstud.io/#tag/Storage:S3/operation/api_storages_export_s3_sync_create rrz/api/storages/export/rrrrs rsync_export_storagezProject.sync_export_storagess<0$$ +L>3z?:K5Q }}rc`|jdd|j}|jS)a Get Import (Source) Cloud Storage. Returns ------- list of dicts: List of dicts with source storages, each dict consists of these fields: ------- Each dict consists of these fields: id : int A unique integer value identifying this storage. type : str The type of the storage. Default is "s3". synchronizable : bool Indicates if the storage is synchronizable. Default is True. presign : bool Indicates if the storage is presign. Default is True. last_sync : str or None The last sync finished time. Can be None. last_sync_count : int or None The count of tasks synced last time. Can be None. last_sync_job : str or None The last sync job ID. Can be None. status : str The status of the storage. Can be one of "initialized", "queued", "in_progress", "failed", "completed". traceback : str or None The traceback report for the last failed sync. Can be None. meta : dict or None Meta and debug information about storage processes. Can be None. title : str or None The title of the cloud storage. Can be None. description : str or None The description of the cloud storage. Can be None. created_at : str The creation time of the storage. bucket : str or None The S3 bucket name. Can be None. prefix : str or None The S3 bucket prefix. Can be None. regex_filter : str or None The cloud storage regex for filtering objects. Can be None. use_blob_urls : bool Indicates if objects are interpreted as BLOBs and generate URLs. aws_access_key_id : str or None The AWS_ACCESS_KEY_ID. Can be None. aws_secret_access_key : str or None The AWS_SECRET_ACCESS_KEY. Can be None. aws_session_token : str or None The AWS_SESSION_TOKEN. Can be None. aws_sse_kms_key_id : str or None The AWS SSE KMS Key ID. Can be None. region_name : str or None The AWS Region. Can be None. s3_endpoint : str or None The S3 Endpoint. Can be None. presign_ttl : int The presigned URLs TTL (in minutes). recursive_scan : bool Indicates if a recursive scan over the bucket content is performed. glob_pattern : str or None The glob pattern for syncing from bucket. Can be None. synced : bool Flag indicating if the dataset has been previously synced or not. rdz/api/storages/?project=rrAs rget_import_storageszProject.get_import_storagess/F$$U.EdggY,OP}}rc`|jdd|j}|jS)aS Get Export (Target) Cloud Storage. Returns ------- list of dicts: List of dicts with target storages ------- Each dict consists of these fields: id : int A unique integer value identifying this storage. type : str The type of the storage. Default is "s3". synchronizable : bool Indicates if the storage is synchronizable. Default is True. last_sync : str or None The last sync finished time. Can be None. last_sync_count : int or None The count of tasks synced last time. Can be None. last_sync_job : str or None The last sync job ID. Can be None. status : str The status of the storage. Can be one of "initialized", "queued", "in_progress", "failed", "completed". traceback : str or None The traceback report for the last failed sync. Can be None. meta : dict or None Meta and debug information about storage processes. Can be None. title : str or None The title of the cloud storage. Can be None. description : str or None The description of the cloud storage. Can be None. created_at : str The creation time of the storage. can_delete_objects : bool or None Deletion from storage enabled. Can be None. bucket : str or None The S3 bucket name. Can be None. prefix : str or None The S3 bucket prefix. Can be None. regex_filter : str or None The cloud storage regex for filtering objects. Can be None. use_blob_urls : bool Indicates if objects are interpreted as BLOBs and generate URLs. aws_access_key_id : str or None The AWS_ACCESS_KEY_ID. Can be None. aws_secret_access_key : str or None The AWS_SECRET_ACCESS_KEY. Can be None. aws_session_token : str or None The AWS_SESSION_TOKEN. Can be None. aws_sse_kms_key_id : str or None The AWS SSE KMS Key ID. Can be None. region_name : str or None The AWS Region. Can be None. s3_endpoint : str or None The S3 Endpoint. Can be None. project : int A unique integer value identifying this project. rdz/api/storages/export?project=rrAs rget_export_storageszProject.get_export_storagess/x$$U.KDGG9,UV}}r?rhassign_functionrrfractionoverlapcTt|dkDsJdt||k\sJdt|dtr.|j}|Dcgc]}|j|vs|}}g} |j |d} t| dkDsJd|dk7r#tt| |z} t | | } |dkDrt| | |z} ttt| t|zd} |D]}| t| kDr t| } n| dzt| k(r | dk7r| dz} |tjk(r|dk(r t | | } n-|tjk(r |dkDr| d | } ntd |d | j||g| |dkDr| | d } n tt| t| z } t| dk(snt| dkDr6|D]1}| s| S| j}| j||g|g3| Scc}w) a Assigning tasks to Reviewers or Annotators by assign_function with method by fraction from view_id Parameters ---------- users: List[int] users' IDs list assign_function: Callable Function to assign tasks by list of user IDs view_id: int Optional, view ID to filter tasks to assign method: AssignmentSamplingMethod Optional, Assignment method fraction: float Optional, expresses the size of dataset to be assigned overlap: int Optional, expresses the count of assignments for each task Returns ------- list[dict] List of dicts with counter of created assignments rzUsers list is empty.z%Overlap is more than number of users.T)rrzTasks list is empty.rrNzSampling method z is not allowed)lenrintrorkrrrmaxr7r%rrmrsetpop)rBrhrrrrr project_usersrq final_resultsrkn_tasks sample_tasksrs r_assign_by_samplingzProject._assign_by_samplings?<5zA~555~5zW$M&MM$ eAh $ ,,.M&3Hdtww%7GTHEH w>5zA~555~ s?CJ)*A5!$E Q; ENGOEc#e*E 23Q7 DU#e*1E *w!|!A+1888W\%eW5 3:::w{$Xg  #3F8?!KLL  $!F G{ghSZ#l*;;<5zQ) , u:> Fyy{$$_dVdV%DE  F YIs H%&H%cD|j||j||||S)a/ Behaves similarly like `assign_reviewers()` but instead of specify tasks_ids explicitely, it gets users' IDs list and optional view ID and uniformly splits all tasks across reviewers Fraction expresses the size of dataset to be assigned Parameters ---------- users: List[int] users' IDs list view_id: int Optional, view ID to filter tasks to assign method: AssignmentSamplingMethod Optional, Assignment method fraction: float Optional, expresses the size of dataset to be assigned overlap: int Optional, expresses the count of assignments for each task Returns ------- list[dict] List of dicts with counter of created assignments rhrrrrr)rrrBrhrrrrs rassign_reviewers_by_samplingz$Project.assign_reviewers_by_samplingis4:'' 11 (  rcD|j||j||||S)a( Behaves similarly like `assign_annotators()` but instead of specify tasks_ids explicitly, it gets users' IDs list and optional view ID and splits all tasks across annotators. Fraction expresses the size of dataset to be assigned. Parameters ---------- users: List[int] users' IDs list view_id: int Optional, view ID to filter tasks to assign method: AssignmentSamplingMethod Optional, Assignment method fraction: float Optional, expresses the size of dataset to be assigned overlap: int Optional, expresses the count of assignments for each task Returns ------- list[dict] List of dicts with counter of created assignments r)rrrs rassign_annotators_by_samplingz%Project.assign_annotators_by_samplings4:'' 22 (  rcb|jdd|jd}|jS)a Get list of export snapshots for the current project ------- Returns ------- list[dict] List of dict with export snapshots with status: id: int Export ID created_at: str Creation time status: str Export status created_by: dict User data finished_at: str Finished time rdrez/exportsrrAs rexport_snapshot_listzProject.export_snapshot_lists/($$UnTWWIX,NO}}rtask_filter_optionsserialization_options_drafts!serialization_options_predictions/serialization_options_annotations__completed_byannotation_filter_options_usual&annotation_filter_options_ground_truth!annotation_filter_options_skippedinterpolate_key_framesc |i}|d|id|id|i| d||||dd} |jdd|jd| | } | jS) a Create new export snapshot ---------- Parameters ---------- title: str Export title task_filter_options: dict Task filter options, use {"view": tab_id} to apply filter from this tab, check the API parameters for more details serialization_options_drafts: bool Expand drafts (False) or include only ID (True) serialization_options_predictions: bool Expand predictions (False) or include only ID (True) serialization_options_annotations__completed_by: bool Expand user that completed_by (False) or include only ID (True) annotation_filter_options_usual: bool Include not cancelled and not ground truth annotations annotation_filter_options_ground_truth: bool Filter ground truth annotations annotation_filter_options_skipped: bool Filter skipped annotations interpolate_key_frames: bool Interpolate key frames into sequence Returns ------- dict: containing the same fields as in the request and the created export fields: id: int Export ID created_at: str Creation time status: str Export status created_by: dict User data finished_at: str Finished time only_id)draftsrCannotations__completed_byr)usual ground_truthskipped)rserialization_optionsrannotation_filter_optionsrrrez /exports?interpolate_key_frames=rsr) rBrrrrrrrrrrur@s rexport_snapshot_createzProject.export_snapshot_createsj  &"$ $&BC )+LMN.+A &$78 F<* "$$ TWWI%EF\E] ^%  }}rc |r|jd|}d|di}nd}d}|jd ||d|}|d} |j| jr5t j d|j| jr5t j|d |j| || \} } |r|j|d| | | d S) a Export tasks from the project with optional filters, and save the exported data to a specified directory. This method: (1) creates a temporary view with the specified filters if they are not None, (2) creates a new export snapshot using the view ID, (3) checks the status of the snapshot creation while it's in progress, (4) and downloads the snapshot file in the specified export format. (5) After the export, it cleans up and remove the temporary view. Parameters ---------- filters : data_manager.Filters, dict, optional Filters to apply when exporting tasks. If provided, a temporary view is created with these filters. The format of the filters should match the Label Studio filter options. Default is None, which means all tasks are exported. Use label_studio_sdk.data_manager.Filters.create() to create filters, Example of the filters JSON format: ```json { "conjunction": "and", "items": [ { "filter": "filter:tasks:id", "operator": "equal", "type": "Number", "value": 1 } ] } ``` titile : str, optional The title of the export snapshot. Default is 'SDK Export'. export_type : str, optional The format of the exported data. It should be one of the formats supported by Label Studio ('JSON', 'CSV', etc.). Default is 'JSON'. output_dir : str, optional The directory where the exported file will be saved. Default is the current directory. kwargs : kwargs, optional The same parameters as in the export_snapshot_create method. Returns ------- dict containing the status of the export, the filename of the exported file, and the export ID. filename : str Path to the downloaded export file status : int 200 is ok export_id : int Export ID, you can retrieve more details about this export using this ID zTemp SDK export)rrrrkN)rrrT)r)rr)rEfilename export_idr) rrexport_snapshot_statusrLrrrmakedirsexport_snapshot_downloadr) rBrrr output_dirrYrr export_resultrrErs rexportzProject.export s@ ##*;W#MD#)4:"6 "& D433  3  "$' )))4CCE JJsO)))4CCE J. 88 ;Z9     T$Z ( hYOOrrcx|jdd|jd|}t|jS)a Get export snapshot status by Export ID ---------- Parameters ---------- export_id: int Existing Export ID from current project. Can be referred as id from self.exports() Returns ------- `label_studio_sdk.project.ExportSnapshotStatus` ExportSnapshotStatus.response is dict and contains the following fields: id: int Export ID created_at: str Creation time status: str created, completed, in_progress, failed created_by: dict User data finished_at: str Finished time rdre /exports/)rjrkr9rlrBrr@s rrzProject.export_snapshot_status{ s=2$$ ^DGG9Ii[A $HMMO44rrc |jdd|jd|d|}d}|jdk(r|jj d}|rC|j dd j d }tjj|}n td ttjj||d 5}|D]}|j| ddd|j|fS#1swYxYw) a Download file with export snapshot in provided format ---------- Parameters ---------- export_id: int Existing Export ID from current project. Can be referred as id from self.exports() export_type: str Default export_type is JSON. Specify another format type as referenced in the Label Studio converter code. path: str Default path to store downloaded files Returns ------- Status code for operation and downloaded filename rdrerz/download?exportType=NrzContent-Dispositionz filename=z"'zNo filename in responser)rjrkrrrsplitstriprrbasenamerrrr) rBrrrr@rcontent_dispositionrchks rrz Project.export_snapshot_download s($$ TWWIYyk9N{m \    3 &"*"2"2"6"67L"M ".44[A"EKKER77++H5*+DEEbggll42D9 !Q#!CGGCL! !##X-- ! !s C<<Dc^|jdd|jd|}|jS)zDelete an export file by specified export ID Parameters ---------- export_id: int Existing Export ID from current project Returns ---------- Status code for operation rrerrrs rexport_snapshot_deletezProject.export_snapshot_delete s8$$ twwiy D ###rrrcD|r|j}g}|rK|D]F}|dD]<} t|d||j|j}|j |>H|S#t t ttf$r"tjd|d|dY}wxYw)a#Copy files from tasks to cache folder Parameters ---------- tasks: Dict Tasks to download to local storage get_tasks: bool Get all tasks from current project Returns ------- list List of filenames r) access_tokenhostnamezCouldn't copy file .) rrrrrmFileNotFoundErrorrrIOErrorrr)rBrr filenamesrkeyrs rget_files_from_taskszProject.get_files_from_tasks s NN$E  Q< QCQ#1 L-)-%)XX$ "((2 Q Q.}mWUQ ':4<;L:MQ%OPQs9A$$8BBcZt|tsJd|jdd|S)zDelete a task. To remove multiple tasks `use delete_tasks()`. Parameters ---------- task_id: int Task id. ztask_id should be intrr7)rrrj)rBr9s r delete_taskzProject.delete_task s4'3'@)@@'  [ +BCCrrct|tsJd|s tSd|d|jd}|j dd|jd|S) zDelete multiple tasks by IDs. Parameters ---------- task_ids: list of int Task ids. ztask_ids should be list of intFryr~rrr/api/dm/actions?project=&id=delete_tasksrs)rrrrkrj)rBrrus r delete_taskszProject.delete_tasks sk(D)K+KK): %*Aww   .twwi7GHw!  r excluded_idsct|ts |Jd|g}d|d|jd}|jdd|jd|S) zDelete all tasks from the project. Parameters ---------- excluded_ids: list of int Task ids that should be excluded from the deletion. z*excluded_ids should be list of int or NoneTrrrrrrrs)rrrkrj)rBrrus rdelete_all_taskszProject.delete_all_tasks st |T *l.B 8 7 8 B  L%)|Dww   .twwi7GHw!  rr?)rrT)rFFNN)NNNNF)NNNNrrFT)NTasks)F)NrN)NNTNTrr)NNrrF) NNTTrrrNNNNNF) NNNNTTrrrNNFN) NrrNNNNNF) NNTTrrrNN)NrrNNF)NTrr)NTTTTTTF)Nz SDK Exportrr)rr)arrrrCr^propertyrarorvrrrrr\rrrr classmethodrrr rrboolrrr rrrrrr#rrrrrrrrrrrrr.r1r3r5r:r>r floatrArDrHrJrLrrQrSrUr[r_rbrnrqryrrrrrrrrrr7r%r rrrrrrr9rrrrrrrr __classcell__)rZs@rrTrTksS %//22&<**0'?B (A>F  "M$DM$b"#(#(#')- BB!B! B d3i B "# B tW\\! "BH+ 1_1 3$ 3 5s 5 D  DP q  qqqqf/ 9*6"  $$ :5 > 7*X.:>!"'+ 88tDz44568 8  } 8t :"4.CD"2$s$s$$2"" !%&*(,8<"&%&!%'GG Gsm G  ~ G )1 G$Gc]G}Gc]GX!%8<!%'#(99 9)1 9 } 9 c] 9!9|!%&*(,"&%&!%'+//3+/%)%)).TT Tsm T  ~ T $ Tc]T}Tc]T$C=T (}T$C=Tc]Tc]T!Tr&* $ $&*(,"&%&!%'%)%)).,0PPc]P P  P sm P ~P$Pc]P}Pc]Pc]Pc]P!P%SMPj!%!%'+//3+/%)%)#(EE E} E c] E $C= E (}E$C=Ec]Ec]E!ET!%&*(,"&%&!%'&*%)DD Dsm D  ~ D $ Dc]D}Dc]DsmDc]DR!%!%'&*%)#(88 8} 8 c] 8 sm 8c]8!8z'+(,!%' A%AsmA ~ A } A c] AFB N*.N15N,0N!%N Nd ]P~558L5>FI#.#.+.#.?B#. s#.J$$$"$4@ D3 D8 D T h & T X rrT),r$rlloggingrrrenumrrrrandomrrtypingrr r r r Alabel_studio_sdk._extensions.label_studio_tools.core.label_configr =label_studio_sdk._extensions.label_studio_tools.core.utils.iorrequestsrrequests.exceptionsrrrrgrutilsr getLoggerrr Exceptionrr!r#r)r7r9rTrrrrs   "88ZXGG&   8 $ 9  4 bdbETE"t'9'9Tu& fu& r