Entities¶
Organization¶
- class Organization(members: list, groups: list, accounts: list, created_at, updated_at, id, name, logo_url, plan, owner, created_by, client_api: dtlpy.services.api_client.ApiClient, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Organization entity
- add_member(email, role: dtlpy.entities.organization.MemberOrgRole = <enum 'MemberOrgRole'>)[source]¶
Add members to your organization. Read about members and groups [here](https://dataloop.ai/docs/org-members-groups).
Prerequisities: To add members to an organization, you must be in the role of an “owner” in that organization.
- delete_member(user_id: str, sure: bool = False, really: bool = False)[source]¶
Delete member from the Organization.
Prerequisites: Must be an organization “owner” to delete members.
- classmethod from_json(_json, client_api, is_fetched=True)[source]¶
Build a Project entity object from a json
- Parameters
is_fetched – is Entity fetched from Platform
_json – _json response from host
client_api – ApiClient entity
- Returns
Project object
- list_groups()[source]¶
List all organization groups (groups that were created within the organization).
Prerequisites: You must be an organization “owner” to use this method.
- Returns
groups list
- Return type
- list_members(role: Optional[dtlpy.entities.organization.MemberOrgRole] = None)[source]¶
List all organization members.
Prerequisites: You must be an organization “owner” to use this method.
- to_json()[source]¶
Returns platform _json format of object
- Returns
platform json format of object
- Return type
- update(plan: str)[source]¶
Update Organization.
Prerequisities: You must be an Organization superuser to update an organization.
- Parameters
plan (str) – OrganizationsPlans.FREEMIUM, OrganizationsPlans.PREMIUM
- Returns
organization object
- update_member(email: str, role: dtlpy.entities.organization.MemberOrgRole = MemberOrgRole.MEMBER)[source]¶
Update member role.
Prerequisities: You must be an organization “owner” to update a member’s role.
Integration¶
- class Integration(id, name, type, org, created_at, created_by, update_at, client_api: dtlpy.services.api_client.ApiClient, project=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Integration object
- delete(sure: bool = False, really: bool = False) bool [source]¶
Delete integrations from the Organization
- classmethod from_json(_json: dict, client_api: dtlpy.services.api_client.ApiClient, is_fetched=True)[source]¶
Build a Integration entity object from a json
- Parameters
_json – _json response from host
client_api – ApiClient entity
is_fetched – is Entity fetched from Platform
- Returns
Integration object
Project¶
- class Project(contributors, created_at, creator, id, name, org, updated_at, role, account, is_blocked, feature_constraints, client_api: dtlpy.services.api_client.ApiClient, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Project entity
- add_member(email, role: dtlpy.entities.project.MemberRole = MemberRole.DEVELOPER)[source]¶
Add a member to the project.
- classmethod from_json(_json, client_api, is_fetched=True)[source]¶
Build a Project entity object from a json
- Parameters
is_fetched – is Entity fetched from Platform
_json – _json response from host
client_api – ApiClient entity
- Returns
Project object
- list_members(role: Optional[dtlpy.entities.project.MemberRole] = None)[source]¶
List the project members.
- Parameters
role – “owner” ,”engineer” ,”annotator” ,”annotationManager”
- Returns
list of the project members
- Return type
- to_json()[source]¶
Returns platform _json format of object
- Returns
platform json format of object
- Return type
- update(system_metadata=False)[source]¶
Update the project
- Parameters
system_metadata (bool) – to update system metadata
- Returns
Project object
- Return type
- update_member(email, role: dtlpy.entities.project.MemberRole = MemberRole.DEVELOPER)[source]¶
Update member’s information/details from the project.
User¶
- class User(created_at, updated_at, name, last_name, username, avatar, email, role, type, org, id, project, client_api=None, users=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
User entity
- classmethod from_json(_json, project, client_api, users=None)[source]¶
Build a User entity object from a json
- Parameters
_json (dict) – _json response from host
project (dtlpy.entities.project.Project) – project entity
client_api – ApiClient entity
users – Users repository
- Returns
User object
- Return type
Dataset¶
- class Dataset(id, url, name, annotated, creator, projects, items_count, metadata, directoryTree, export, expiration_options, created_at, items_url, readable_type, access_level, driver, readonly, client_api: dtlpy.services.api_client.ApiClient, instance_map=None, project=None, datasets=None, repositories=NOTHING, ontology_ids=None, labels=None, directory_tree=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Dataset object
- add_label(label_name, color=None, children=None, attributes=None, display_label=None, label=None, recipe_id=None, ontology_id=None, icon_path=None)[source]¶
Add single label to dataset
- Parameters
label_name – str - label name
color – color
children – children (sub labels)
attributes – attributes
display_label – display_label
label – label
recipe_id – optional recipe id
ontology_id – optional ontology id
icon_path – path to image to be display on label
- Returns
label entity
- add_labels(label_list, ontology_id=None, recipe_id=None)[source]¶
Add labels to dataset
- Parameters
label_list – label list
ontology_id – optional ontology id
recipe_id – optional recipe id
- Returns
label entities
- clone(clone_name, filters=None, with_items_annotations=True, with_metadata=True, with_task_annotations_status=True)[source]¶
Clone dataset
- Parameters
clone_name – new dataset name
filters (dtlpy.entities.filters.Filters) – Filters entity or a query dict
with_items_annotations – clone all item’s annotations
with_metadata – clone metadata
with_task_annotations_status – clone task annotations status
- Returns
dataset object
- Return type
- delete_labels(label_names)[source]¶
Delete labels from dataset’s ontologies
- Parameters
label_names – label object/ label name / list of label objects / list of label names
- Returns
- download(filters=None, local_path=None, file_types=None, annotation_options: Optional[dtlpy.entities.annotation.ViewAnnotationOptions] = None, annotation_filters=None, overwrite=False, to_items_folder=True, thickness=1, with_text=False, without_relative_path=None, alpha=None)[source]¶
Download dataset by filters. Filtering the dataset for items and save them local Optional - also download annotation, mask, instance and image mask of the item
- Parameters
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
local_path – local folder or filename to save to.
file_types – a list of file type to download. e.g [‘video/webm’, ‘video/mp4’, ‘image/jpeg’, ‘image/png’]
annotation_options – download annotations options: list(dl.ViewAnnotationOptions) not relevant for JSON option
annotation_filters – Filters entity to filter annotations for download not relevant for JSON option
overwrite – optional - default = False
to_items_folder – Create ‘items’ folder and download items to it
thickness – optional - line thickness, if -1 annotation will be filled, default =1
with_text – optional - add text to annotations, default = False
without_relative_path – string - remote path - download items without the relative path from platform
alpha – opacity value [0 1], default 1
- Returns
List of local_path per each downloaded item
- download_annotations(local_path=None, filters=None, annotation_options: Optional[dtlpy.entities.annotation.ViewAnnotationOptions] = None, annotation_filters=None, overwrite=False, thickness=1, with_text=False, remote_path=None, include_annotations_in_output=True, export_png_files=False, filter_output_annotations=False, alpha=None)[source]¶
Download dataset by filters. Filtering the dataset for items and save them local Optional - also download annotation, mask, instance and image mask of the item
- Parameters
local_path – local folder or filename to save to.
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
annotation_options – download annotations options: list(dl.ViewAnnotationOptions)
annotation_filters – Filters entity to filter annotations for download
overwrite – optional - default = False
thickness – optional - line thickness, if -1 annotation will be filled, default =1
with_text – optional - add text to annotations, default = False
remote_path – DEPRECATED and ignored. use filters
include_annotations_in_output – default - False , if export should contain annotations
export_png_files – default - if True, semantic annotations should be exported as png files
filter_output_annotations – default - False, given an export by filter - determine if to filter out annotations
alpha – opacity value [0 1], default 1
- Returns
List of local_path per each downloaded item
- download_partition(partition, local_path=None, filters=None, annotation_options=None)[source]¶
Download a specific partition of the dataset to local_path This function is commonly used with dl.ModelAdapter which implements thc convert to specific model structure
- Parameters
partition – dl.SnapshotPartitionType name of the partition
local_path – local path directory to download the data
filters (dtlpy.entities.filters.Filters) – dl.entities.Filters to add the specific partitions constraint to
:return List str of the new downloaded path of each item
- classmethod from_json(project: dtlpy.entities.project.Project, _json: dict, client_api: dtlpy.services.api_client.ApiClient, datasets=None, is_fetched=True)[source]¶
Build a Dataset entity object from a json
- Parameters
- Returns
Dataset object
- Return type
- get_partitions(partitions, filters=None, batch_size: Optional[int] = None)[source]¶
Returns PagedEntity of items from one or more partitions
- Parameters
partitions – dl.entities.SnapshotPartitionType or a list. Name of the partitions
filters (dtlpy.entities.filters.Filters) – dl.Filters to add the specific partitions constraint to
batch_size – int how many items per page
- Returns
dl.PagedEntities of dl.Item preforms items.list()
- static serialize_labels(labels_dict)[source]¶
Convert hex color format to rgb
- Parameters
labels_dict – dict of labels
- Returns
dict of converted labels
- set_partition(partition, filters=None)[source]¶
Updates all items returned by filters in the dataset to specific partition
- Parameters
partition – dl.entities.SnapshotPartitionType to set to
filters (dtlpy.entities.filters.Filters) – dl.entities.Filters to add the specific partitions constraint to
- Returns
dl.PagedEntities
- switch_recipe(recipe_id=None, recipe=None)[source]¶
Switch the recipe that linked to the dataset with the given one
- Parameters
recipe_id – recipe id
recipe – recipe entity
- Returns
- sync(wait=True)[source]¶
Sync dataset with external storage
- Parameters
wait – wait the command to finish
- Returns
True if success
- Return type
- to_json()[source]¶
Returns platform _json format of object
- Returns
platform json format of object
- Return type
- update(system_metadata=False)[source]¶
Update dataset field
- Parameters
system_metadata (bool) – bool - True, if you want to change metadata system
- Returns
Dataset object
- Return type
- update_label(label_name, color=None, children=None, attributes=None, display_label=None, label=None, recipe_id=None, ontology_id=None, upsert=False, icon_path=None)[source]¶
Add single label to dataset
- Parameters
label_name – label name
color – color
children – children (sub labels)
attributes – attributes
display_label – display label
label – label
recipe_id – optional recipe id
ontology_id – optional ontology id
upsert – if True will add in case it does not existing
icon_path – path to image to be display on label
- Returns
label entity
- update_labels(label_list, ontology_id=None, recipe_id=None, upsert=False)[source]¶
Add labels to dataset
- Parameters
label_list – label list
ontology_id – optional ontology id
recipe_id – optional recipe id
upsert – if True will add in case it does not existing
- Returns
label entities
- upload_annotations(local_path, filters=None, clean=False, remote_root_path='/')[source]¶
Upload annotations to dataset.
- Parameters
local_path – str - local folder where the annotations files is.
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
clean – bool - if True it remove the old annotations
remote_root_path – str - the remote root path to match remote and local items
For example, if the item filepath is a/b/item and remote_root_path is /a the start folder will be b instead of a
- class ExpirationOptions(item_max_days: Optional[int] = None)[source]¶
Bases:
object
ExpirationOptions object
Driver¶
- class Driver(bucket_name, creator, allow_external_delete, allow_external_modification, created_at, region, path, type, integration_id, metadata, name, id, client_api: dtlpy.services.api_client.ApiClient)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Driver entity
Item¶
- class Item(annotations_link, dataset_url, thumbnail, created_at, dataset_id, annotated, metadata, filename, stream, name, type, url, id, hidden, dir, spec, creator, annotations_count, client_api: dtlpy.services.api_client.ApiClient, platform_dict, dataset, project, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Item object
- clone(dst_dataset_id=None, remote_filepath=None, metadata=None, with_annotations=True, with_metadata=True, with_task_annotations_status=False, allow_many=False, wait=True)[source]¶
Clone item
- Parameters
dst_dataset_id – destination dataset id
remote_filepath – complete filepath
metadata – new metadata to add
with_annotations – clone annotations
with_metadata – clone metadata
with_task_annotations_status – clone task annotations status
allow_many – bool if True use multiple clones in single dataset is allowed, (default=False)
wait – wait the command to finish
- Returns
Item
- download(local_path=None, file_types=None, save_locally=True, to_array=False, annotation_options: Optional[dtlpy.entities.annotation.ViewAnnotationOptions] = None, overwrite=False, to_items_folder=True, thickness=1, with_text=False, annotation_filters=None, alpha=None)[source]¶
Download dataset by filters. Filtering the dataset for items and save them local Optional - also download annotation, mask, instance and image mask of the item
- Parameters
local_path – local folder or filename to save to disk or returns BytelsIO
file_types – a list of file type to download. e.g [‘video/webm’, ‘video/mp4’, ‘image/jpeg’, ‘image/png’]
save_locally – bool. save to disk or return a buffer
to_array – returns Ndarray when True and local_path = False
annotation_options – download annotations options: list(dl.ViewAnnotationOptions)
overwrite – optional - default = False
to_items_folder – Create ‘items’ folder and download items to it
thickness – optional - line thickness, if -1 annotation will be filled, default =1
with_text – optional - add text to annotations, default = False
annotation_filters – Filters entity to filter annotations for download
alpha – opacity value [0 1], default 1
- Returns
Output (list)
- classmethod from_json(_json, client_api, dataset=None, project=None, is_fetched=True)[source]¶
Build an item entity object from a json
- Parameters
project – project entity
_json – _json response from host
dataset – dataset in which the annotation’s item is located
client_api – ApiClient entity
is_fetched – is Entity fetched from Platform
- Returns
Item object
- move(new_path)[source]¶
Move item from one folder to another in Platform If the directory doesn’t exist it will be created
- Parameters
new_path – new full path to move item to.
- Returns
True if update successfully
- set_description(text: str)[source]¶
Update Item description
- Parameters
text – if None or “” description will be deleted
:return
- to_json()[source]¶
Returns platform _json format of object
- Returns
platform json format of object
- Return type
- update(system_metadata=False)[source]¶
Update items metadata
- Parameters
system_metadata – bool - True, if you want to change metadata system
- Returns
Item object
Item Link¶
Annotation¶
- class Annotation(annotation_definition: dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition, id, url, item_url, item, item_id, creator, created_at, updated_by, updated_at, type, source, dataset_url, platform_dict, metadata, fps, hash=None, dataset_id=None, status=None, object_id=None, automated=None, item_height=None, item_width=None, label_suggestions=None, frames=None, current_frame=0, end_frame=0, end_time=0, start_frame=0, start_time=0, dataset=None, datasets=None, annotations=None, Annotation__client_api=None, items=None, recipe_2_attributes=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Annotations object
- add_frame(annotation_definition, frame_num=None, fixed=True, object_visible=True)[source]¶
Add a frame state to annotation
- add_frames(annotation_definition, frame_num=None, end_frame_num=None, start_time=None, end_time=None, fixed=True, object_visible=True)[source]¶
Add a frames state to annotation
- Parameters
annotation_definition – annotation type object - must be same type as annotation
frame_num (int) – first frame number
end_frame_num (int) – last frame number
start_time – starting time for video
end_time – ending time for video
fixed (bool) – is fixed
object_visible (bool) – does the annotated object is visible
- Returns
- download(filepath: str, annotation_format: dtlpy.entities.annotation.ViewAnnotationOptions = ViewAnnotationOptions.MASK, height: Optional[float] = None, width: Optional[float] = None, thickness: int = 1, with_text: bool = False, alpha: Optional[float] = None)[source]¶
Save annotation to file
- Parameters
filepath (str) – local path to where annotation will be downloaded to
annotation_format (list) – options: list(dl.ViewAnnotationOptions)
height (float) – image height
width (float) – image width
thickness (int) – thickness
with_text (bool) – get mask with text
alpha (float) – opacity value [0 1], default 1
- Returns
filepath
- Return type
- classmethod from_json(_json, item=None, client_api=None, annotations=None, is_video=None, fps=None, item_metadata=None, dataset=None, is_audio=None)[source]¶
Create an annotation object from platform json
- Parameters
_json (dict) – platform json
item (dtlpy.entities.item.Item) – item
client_api – ApiClient entity
annotations –
is_video (bool) – is video
fps – video fps
item_metadata – item metadata
dataset – dataset entity
is_audio (bool) – is audio
- Returns
annotation object
- Return type
- classmethod new(item=None, annotation_definition=None, object_id=None, automated=True, metadata=None, frame_num=None, parent_id=None, start_time=None, item_height=None, item_width=None)[source]¶
Create a new annotation object annotations
- Parameters
item (dtlpy.entities.item.Items) – item to annotate
annotation_definition – annotation type object
object_id (str) – object_id
automated (bool) – is automated
metadata (dict) – metadata
frame_num (int) – optional - first frame number if video annotation
parent_id (str) – add parent annotation ID
start_time – optional - start time if video annotation
item_height (float) – annotation item’s height
item_width (float) – annotation item’s width
- Returns
annotation object
- Return type
- show(image=None, thickness=None, with_text=False, height=None, width=None, annotation_format: dtlpy.entities.annotation.ViewAnnotationOptions = ViewAnnotationOptions.MASK, color=None, label_instance_dict=None, alpha=None)[source]¶
Show annotations mark the annotation of the image array and return it
- Parameters
image – empty or image to draw on
thickness (int) – line thickness
with_text (bool) – add label to annotation
height (float) – height
width (float) – width
annotation_format – list(dl.ViewAnnotationOptions)
color (tuple) – optional - color tuple
label_instance_dict – the instance labels
alpha (float) – opacity value [0 1], default 1
- Returns
list or single ndarray of the annotations
- to_json()[source]¶
Convert annotation object to a platform json representation
- Returns
platform json
- Return type
- update(system_metadata=False)[source]¶
Update an existing annotation in host.
- Parameters
system_metadata – True, if you want to change metadata system
- Returns
Annotation object
- Return type
- update_status(status: dtlpy.entities.annotation.AnnotationStatus = AnnotationStatus.ISSUE)[source]¶
Set status on annotation
- Parameters
status (str) – can be AnnotationStatus.ISSUE, AnnotationStatus.APPROVED, AnnotationStatus.REVIEW, AnnotationStatus.CLEAR
- Returns
Annotation object
- Return type
- class FrameAnnotation(annotation, annotation_definition, frame_num, fixed, object_visible, recipe_2_attributes=None, interpolation=False)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
FrameAnnotation object
- classmethod from_snapshot(annotation, _json, fps)[source]¶
new frame state to annotation
- Parameters
annotation – annotation
_json – annotation type object - must be same type as annotation
fps – frame number
- Returns
FrameAnnotation object
- classmethod new(annotation, annotation_definition, frame_num, fixed, object_visible=True)[source]¶
new frame state to annotation
- Parameters
annotation – annotation
annotation_definition – annotation type object - must be same type as annotation
frame_num – frame number
fixed – is fixed
object_visible – does the annotated object is visible
- Returns
FrameAnnotation object
Collection of Annotation entities¶
- class AnnotationCollection(item=None, annotations=NOTHING, dataset=None, colors=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Collection of Annotation entity
- add(annotation_definition, object_id=None, frame_num=None, end_frame_num=None, start_time=None, end_time=None, automated=True, fixed=True, object_visible=True, metadata=None, parent_id=None, model_info=None)[source]¶
Add annotations to collection
- Parameters
annotation_definition – dl.Polygon, dl.Segmentation, dl.Point, dl.Box etc
object_id – Object id (any id given by user). If video - must input to match annotations between frames
frame_num – video only, number of frame
end_frame_num – video only, the end frame of the annotation
start_time – video only, start time of the annotation
end_time – video only, end time of the annotation
automated –
fixed – video only, mark frame as fixed
object_visible – video only, does the annotated object is visible
metadata – optional- metadata dictionary for annotation
parent_id – set a parent for this annotation (parent annotation ID)
model_info – optional - set model on annotation {‘name’,:’’, ‘confidence’:0}
- Returns
- download(filepath, img_filepath=None, annotation_format: dtlpy.entities.annotation.ViewAnnotationOptions = ViewAnnotationOptions.MASK, height=None, width=None, thickness=1, with_text=False, orientation=0, alpha=None)[source]¶
Save annotations to file
- Parameters
filepath – path to save annotation
img_filepath – img file path - needed for img_mask
annotation_format – how to show thw annotations. options: list(dl.ViewAnnotationOptions)
height – height
width – width
thickness – thickness
with_text – add a text to the image
orientation – the image orientation
alpha – opacity value [0 1], default 1
- Returns
- from_instance_mask(mask, instance_map=None)[source]¶
convert annotation from instance mask format :param mask: the mask annotation :param instance_map: labels
- from_vtt_file(filepath)[source]¶
convert annotation from vtt format :param filepath: path to the file
- get_frame(frame_num)[source]¶
Get frame
- Parameters
frame_num – frame num
- Returns
AnnotationCollection
- show(image=None, thickness=None, with_text=False, height=None, width=None, annotation_format: dtlpy.entities.annotation.ViewAnnotationOptions = ViewAnnotationOptions.MASK, label_instance_dict=None, color=None, alpha=None)[source]¶
Show annotations according to annotation_format
- Parameters
image – empty or image to draw on
height – height
width – width
thickness – line thickness
with_text – add label to annotation
annotation_format – how to show thw annotations. options: list(dl.ViewAnnotationOptions)
label_instance_dict – instance label map {‘Label’: 1, ‘More’: 2}
color – optional - color tuple
alpha – opacity value [0 1], default 1
- Returns
ndarray of the annotations
Annotation Definition¶
Box Annotation Definition¶
- class Box(left=None, top=None, right=None, bottom=None, label=None, attributes=None, description=None, angle=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Box annotation object Can create a box using 2 point using: “top”, “left”, “bottom”, “right” (to form a box [(left, top), (right, bottom)]) For rotated box add the “angel”
- classmethod from_segmentation(mask, label, attributes=None)[source]¶
Convert binary mask to Polygon
- Parameters
mask – binary mask (0,1)
label – annotation label
attributes – annotations list of attributes
- Returns
Box annotations list to each separated segmentation
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Classification Annotation Definition¶
- class Classification(label, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Classification annotation object
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Cuboid Annotation Definition¶
- class Cube(label, front_tl, front_tr, front_br, front_bl, back_tl, back_tr, back_br, back_bl, angle=None, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Cube annotation object
- classmethod from_boxes_and_angle(front_left, front_top, front_right, front_bottom, back_left, back_top, back_right, back_bottom, label, angle=0, attributes=None)[source]¶
Create cuboid by given front and back boxes with angle the angle calculate fom the center of each box
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Item Description Definition¶
Ellipse Annotation Definition¶
- class Ellipse(x, y, rx, ry, angle, label, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Ellipse annotation object
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Note Annotation Definition¶
- class Message(msg_id: Optional[str] = None, creator: Optional[str] = None, msg_time=None, body: Optional[str] = None)[source]¶
Bases:
object
Note message object
- class Note(left, top, right, bottom, label, attributes=None, messages=None, status='issue', assignee=None, create_time=None, creator=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.box.Box
Note annotation object
Point Annotation Definition¶
- class Point(x, y, label, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Point annotation object
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Polygon Annotation Definition¶
- class Polygon(geo, label, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Polygon annotation object
- classmethod from_segmentation(mask, label, attributes=None, epsilon=None, max_instances=1, min_area=0)[source]¶
Convert binary mask to Polygon
- Parameters
mask – binary mask (0,1)
label – annotation label
attributes – annotations list of attributes
epsilon – from opencv: specifying the approximation accuracy. This is the maximum distance between the original curve and its approximation. if 0 all points are returns
max_instances – number of max instances to return. if None all wil be returned
min_area – remove polygons with area lower thn this threshold (pixels)
- Returns
Polygon annotation
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Polyline Annotation Definition¶
- class Polyline(geo, label, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Polyline annotation object
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Pose Annotation Definition¶
- class Pose(label, template_id, instance_id=None, attributes=None, points=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Classification annotation object
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Segmentation Annotation Definition¶
- class Segmentation(geo, label, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
Segmentation annotation object
- classmethod from_polygon(geo, label, shape, attributes=None)[source]¶
- Parameters
geo – list of x,y coordinates of the polygon ([[x,y],[x,y]…]
label – annotation’s label
shape – image shape (h,w)
attributes –
- Returns
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Audio Annotation Definition¶
Undefined Annotation Definition¶
- class UndefinedAnnotationType(type, label, coordinates, attributes=None, description=None)[source]¶
Bases:
dtlpy.entities.annotation_definitions.base_annotation_definition.BaseAnnotationDefinition
UndefinedAnnotationType annotation object
- show(image, thickness, with_text, height, width, annotation_format, color, alpha=1)[source]¶
Show annotation as ndarray :param image: empty or image to draw on :param thickness: :param with_text: not required :param height: item height :param width: item width :param annotation_format: options: list(dl.ViewAnnotationOptions) :param color: color :param alpha: opacity value [0 1], default 1 :return: ndarray
Similarity¶
- class Collection(type: dtlpy.entities.similarity.CollectionTypes, name, items=None)[source]¶
Bases:
object
Base Collection Entity
- add(ref, type: dtlpy.entities.similarity.SimilarityTypeEnum = SimilarityTypeEnum.ID)[source]¶
Add item to collection :param ref: :param type: url, id
- class CollectionItem(type: dtlpy.entities.similarity.SimilarityTypeEnum, ref)[source]¶
Bases:
object
Base CollectionItem
- class MultiView(name, items=None)[source]¶
Bases:
dtlpy.entities.similarity.Collection
Multi Entity
- property items¶
list of the collection items
- class MultiViewItem(type, ref)[source]¶
Bases:
dtlpy.entities.similarity.CollectionItem
Single multi view item
- class Similarity(ref, name=None, items=None)[source]¶
Bases:
dtlpy.entities.similarity.Collection
Similarity Entity
- property items¶
list of the collection items
- property target¶
Target item for similarity
- class SimilarityItem(type, ref, target=False)[source]¶
Bases:
dtlpy.entities.similarity.CollectionItem
Single similarity item
Filter¶
- class Filters(field=None, values=None, operator: Optional[dtlpy.entities.filters.FiltersOperations] = None, method: Optional[dtlpy.entities.filters.FiltersMethod] = None, custom_filter=None, resource: dtlpy.entities.filters.FiltersResource = FiltersResource.ITEM, use_defaults=True, context=None)[source]¶
Bases:
object
Filters entity to filter items from pages in platform
- add(field, values, operator: Optional[dtlpy.entities.filters.FiltersOperations] = None, method: Optional[dtlpy.entities.filters.FiltersMethod] = None)[source]¶
Add filter
- Parameters
field – Metadata field / attribute
values – field values
operator – optional - in, gt, lt, eq, ne
method – Optional - or/and
- Returns
- add_join(field, values, operator: Optional[dtlpy.entities.filters.FiltersOperations] = None, method: dtlpy.entities.filters.FiltersMethod = FiltersMethod.AND)[source]¶
join a query to the filter
- Parameters
field – field to add
values – values
operator – optional - in, gt, lt, eq, ne
method – optional - str - FiltersMethod.AND, FiltersMethod.OR
- has_field(field)[source]¶
is filter has field
- Parameters
field – field to check
- Returns
Ture is have it
- Return type
- prepare(operation=None, update=None, query_only=False, system_update=None, system_metadata=False)[source]¶
To dictionary for platform call
- Parameters
operation – operation
update – update
query_only – query only
system_update – system update
system_metadata – True, if you want to change metadata system
- Returns
dict of the filter
- Return type
- sort_by(field, value: dtlpy.entities.filters.FiltersOrderByDirection = FiltersOrderByDirection.ASCENDING)[source]¶
sort the filter
- Parameters
field – field to sort by it
value – FiltersOrderByDirection.ASCENDING, FiltersOrderByDirection.DESCENDING
Recipe¶
- class Recipe(id, creator, url, title, project_ids, description, ontology_ids, instructions, examples, custom_actions, metadata, ui_settings, client_api: dtlpy.services.api_client.ApiClient, dataset=None, project=None, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Recipe object
- clone(shallow=False)[source]¶
Clone Recipe
- Parameters
shallow – If True, link ot existing ontology, clones all ontology that are link to the recipe as well
- Returns
Cloned ontology object
- delete(force: bool = False)[source]¶
Delete recipe from platform
- Parameters
force (bool) – force delete recipe
- Returns
True
- classmethod from_json(_json, client_api, dataset=None, project=None, is_fetched=True)[source]¶
Build a Recipe entity object from a json
- Parameters
_json – _json response from host
dataset – recipe’s dataset
project – recipe’s project
client_api – ApiClient entity
is_fetched – is Entity fetched from Platform
- Returns
Recipe object
- get_annotation_template_id(template_name)[source]¶
Get annotation template id by template name
- Parameters
template_name –
- Returns
template id or None if does not exist
Ontology¶
- class Ontology(client_api: dtlpy.services.api_client.ApiClient, id, creator, url, title, labels, metadata, attributes, recipe=None, dataset=None, project=None, repositories=NOTHING, instance_map=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Ontology object
- add_label(label_name, color=None, children=None, attributes=None, display_label=None, label=None, add=True, icon_path=None, update_ontology=False)[source]¶
Add a single label to ontology
- Parameters
label_name – label name
color – optional - if not given a random color will be selected
children – optional - children
attributes – optional - attributes
display_label – optional - display_label
label – label
add – to add or not
icon_path – path to image to be display on label
update_ontology – update the ontology, default = False for backward compatible
- Returns
Label entity
- add_labels(label_list, update_ontology=False)[source]¶
Adds a list of labels to ontology
- Parameters
label_list – list of labels [{“value”: {“tag”: “tag”, “displayLabel”: “displayLabel”, “color”: “#color”, “attributes”: [attributes]}, “children”: [children]}]
update_ontology – update the ontology, default = False for backward compatible
- Returns
List of label entities added
- delete_labels(label_names)[source]¶
Delete labels from ontology
- Parameters
label_names – label object/ label name / list of label objects / list of label names
- Returns
- classmethod from_json(_json, client_api, recipe, dataset=None, project=None, is_fetched=True)[source]¶
Build an Ontology entity object from a json
- Parameters
is_fetched – is Entity fetched from Platform
project – project entity
dataset – dataset entity
_json – _json response from host
recipe – ontology’s recipe
client_api – ApiClient entity
- Returns
Ontology object
- to_json()[source]¶
Returns platform _json format of object
- Returns
platform json format of object
- Return type
- update(system_metadata=False)[source]¶
Update items metadata
- Parameters
system_metadata – bool - True, if you want to change metadata system
- Returns
Ontology object
- update_label(label_name, color=None, children=None, attributes=None, display_label=None, label=None, add=True, icon_path=None, upsert=False, update_ontology=False)[source]¶
Update a single label to ontology
- Parameters
label_name – label name
color – optional - if not given a random color will be selected
children – optional - children
attributes – optional - attributes
display_label – optional - display_label
label – label
add – to add or not
icon_path – path to image to be display on label
upsert – if True will add in case it does not existing
update_ontology – update the ontology, default = False for backward compatible
- Returns
Label entity
- update_labels(label_list, upsert=False, update_ontology=False)[source]¶
Update a list of labels to ontology
- Parameters
label_list – list of labels [{“value”: {“tag”: “tag”, “displayLabel”: “displayLabel”, “color”: “#color”, “attributes”: [attributes]}, “children”: [children]}]
upsert – if True will add in case it does not existing
update_ontology – update the ontology, default = False for backward compatible
- Returns
List of label entities added
Label¶
Task¶
- class Task(name, status, project_id, metadata, id, url, task_owner, item_status, creator, due_date, dataset_id, spec, recipe_id, query, assignmentIds, annotation_status, progress, for_review, issues, updated_at, created_at, available_actions, total_items, client_api, current_assignments=None, assignments=None, project=None, dataset=None, tasks=None, settings=None)[source]¶
Bases:
object
Task object
- add_items(filters=None, items=None, assignee_ids=None, workload=None, limit=0, wait=True)[source]¶
Add items to Task
- Parameters
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
items – items list for the assignment
assignee_ids – list of assignee for the assignment
workload – the load of work
limit – limit
wait – wait the command to finish
- Returns
- create_assignment(assignment_name, assignee_id, items=None, filters=None)[source]¶
Create a new assignment
- Parameters
assignment_name – assignment name
assignee_id – list of assignee for the assignment
items – items list for the assignment
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
- Returns
- delete(wait=True)[source]¶
Delete task from platform
- Parameters
wait – wait the command to finish
- Returns
True
- get_items(filters=None)[source]¶
Get the task items
- Parameters
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
- Returns
- set_status(status: str, operation: str, item_ids: List[str])[source]¶
Update item status within task
- Parameters
status – str - string the describes the status
operation – str - ‘create’ or ‘delete’
item_ids – List[str]
:return : Boolean
Assignment¶
- class Assignment(name, annotator, status, project_id, metadata, id, url, task_id, dataset_id, annotation_status, item_status, total_items, for_review, issues, client_api, task=None, assignments=None, project=None, dataset=None, datasets=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Assignment object
- get_items(dataset=None, filters=None)[source]¶
Get all the items in the assignment
- Parameters
dataset (dtlpy.entities.dataset.Dataset) – dataset entity
filters (dtlpy.entities.filters.Filters) – Filters entity or a dictionary containing filters parameters
- Returns
pages of the items
- Return type
- reassign(assignee_id, wait=True)[source]¶
Reassign an assignment
- Parameters
- Returns
Assignment object
- Return type
- redistribute(workload, wait=True)[source]¶
Redistribute an assignment
- Parameters
workload (dtlpy.entities.assignment.Workload) – workload object that contain the assignees and the work load
wait (bool) – wait the command to finish
- Returns
Assignment object
- Return type
dtlpy.entities.assignment.Assignment assignment
Package¶
- class Package(id, url, version, created_at, updated_at, name, codebase, modules, slots: list, ui_hooks, creator, is_global, type, service_config, project_id, project, client_api: dtlpy.services.api_client.ApiClient, revisions=None, repositories=NOTHING, artifacts=None, codebases=None, requirements=None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Package object
- deploy(service_name=None, revision=None, init_input=None, runtime=None, sdk_version=None, agent_versions=None, verify=True, bot=None, pod_type=None, module_name=None, run_execution_as_process=None, execution_timeout=None, drain_time=None, on_reset=None, max_attempts=None, force=False, **kwargs)[source]¶
Deploy package
- Parameters
service_name (str) – service name
revision (str) – package revision - default=latest
init_input – config to run at startup
runtime (dict) – runtime resources
sdk_version (str) –
optional - string - sdk version
agent_versions (dict) –
dictionary - - optional -versions of sdk, agent runner and agent proxy
bot (str) – bot email
pod_type (str) – pod type dl.InstanceCatalog
verify (bool) – verify the inputs
module_name (str) – module name
run_execution_as_process (bool) – run execution as process
execution_timeout (int) – execution timeout
drain_time (int) – drain time
on_reset (str) – on reset
max_attempts (int) – Maximum execution retries in-case of a service reset
force (bool) – optional - terminate old replicas immediately
- Returns
Service object
- classmethod from_json(_json, client_api, project, is_fetched=True)[source]¶
Turn platform representation of package into a package entity
- Parameters
_json – platform representation of package
client_api – ApiClient entity
project – project entity
is_fetched – is Entity fetched from Platform
- Returns
Package entity
- pull(version=None, local_path=None)[source]¶
Push local package
- Parameters
version – version
local_path – local path
- Returns
- push(codebase: Optional[Union[dtlpy.entities.codebase.GitCodebase, dtlpy.entities.codebase.ItemCodebase]] = None, src_path: Optional[str] = None, package_name: Optional[str] = None, modules: Optional[list] = None, checkout: bool = False, revision_increment: Optional[str] = None, service_update: bool = False, service_config: Optional[dict] = None)[source]¶
Push local package
- Parameters
codebase (dtlpy.entities.codebase.Codebase) – PackageCode object - defines how to store the package code
checkout – save package to local checkout
src_path – location of pacjage codebase folder to zip
package_name – name of package
modules – list of PackageModule
revision_increment – optional - str - version bumping method - major/minor/patch - default = None
service_update – optional - bool - update the service
service_config – optional - json of service - a service that have config from the main service if wanted
- Returns
Package Function¶
Package Module¶
Slot¶
- class PackageSlot(module_name='default_module', function_name='run', display_name=None, display_scopes: Optional[list] = None, display_icon=None, post_action: dtlpy.entities.package_slot.SlotPostAction = NOTHING, default_inputs: Optional[list] = None, input_options: Optional[list] = None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Webhook object
Codebase¶
Service¶
- class Service(created_at, updated_at, creator, version, package_id, package_revision, bot, use_user_jwt, init_input, versions, module_name, name, url, id, active, driver_id, secrets, runtime, queue_length_limit, run_execution_as_process: bool, execution_timeout, drain_time, on_reset: dtlpy.entities.service.OnResetAction, project_id, is_global, max_attempts, package, client_api: dtlpy.services.api_client.ApiClient, revisions=None, project=None, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Service object
- activate_slots(project_id: Optional[str] = None, task_id: Optional[str] = None, dataset_id: Optional[str] = None, org_id: Optional[str] = None, user_email: Optional[str] = None, slots=None, role=None, prevent_override: bool = True, visible: bool = True, icon: str = 'fas fa-magic', **kwargs) object [source]¶
Activate service slots
- Parameters
project_id (str) – project id
task_id (str) – task id
dataset_id (str) – dataset id
org_id (str) – org id
user_email (str) – user email
slots (list) – list of entities.PackageSlot
role (str) – user role MemberOrgRole.ADMIN, MemberOrgRole.OWNER, MemberOrgRole.MEMBER
prevent_override (bool) – prevent override
visible (bool) – visible
icon (str) – icon
kwargs –
- Returns
List of user setting for activated slots
- execute(execution_input=None, function_name=None, resource=None, item_id=None, dataset_id=None, annotation_id=None, project_id=None, sync=False, stream_logs=True, return_output=True)[source]¶
Execute a function on an existing service
- Parameters
execution_input – input dictionary or list of FunctionIO entities
function_name – str - function name to run
:param resource:dl.PackageInputType - input type. :param item_id:str - optional - input to function :param dataset_id:str - optional - input to function :param annotation_id:str - optional - input to function :param project_id:str - resource’s project :param sync: bool - wait for function to end :param stream_logs: bool - prints logs of the new execution. only works with sync=True :param return_output: bool - if True and sync is True - will return the output directly :return:
- classmethod from_json(_json: dict, client_api: dtlpy.services.api_client.ApiClient, package=None, project=None, is_fetched=True)[source]¶
Build a service entity object from a json
- Parameters
_json – platform json
client_api – ApiClient entity
package – package entity
project – project entity
is_fetched – is Entity fetched from Platform
- Returns
- log(size=None, checkpoint=None, start=None, end=None, follow=False, text=None, execution_id=None, function_name=None, replica_id=None, system=False, view=True, until_completed=True)[source]¶
Get service logs
- Parameters
- Returns
ServiceLog entity
Bot¶
- class Bot(created_at, updated_at, name, last_name, username, avatar, email, role, type, org, id, project, client_api=None, users=None, bots=None, password=None)[source]¶
Bases:
dtlpy.entities.user.User
Bot entity
Trigger¶
- class BaseTrigger(id, url, created_at, updated_at, creator, name, active, type, scope, is_global, input, function_name, service_id, webhook_id, pipeline_id, special, project_id, spec, service, project, client_api: dtlpy.services.api_client.ApiClient, op_type='service', repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Trigger Entity
- classmethod from_json(_json, client_api, project, service=None)[source]¶
Build a trigger entity object from a json
- Parameters
_json – platform json
client_api – ApiClient entity
project – project entity
service – service entity
- Returns
- class CronTrigger(id, url, created_at, updated_at, creator, name, active, type, scope, is_global, input, function_name, service_id, webhook_id, pipeline_id, special, project_id, spec, service, project, client_api: dtlpy.services.api_client.ApiClient, op_type='service', repositories=NOTHING, start_at=None, end_at=None, cron=None)[source]¶
- class Trigger(id, url, created_at, updated_at, creator, name, active, type, scope, is_global, input, function_name, service_id, webhook_id, pipeline_id, special, project_id, spec, service, project, client_api: dtlpy.services.api_client.ApiClient, op_type='service', repositories=NOTHING, filters=None, execution_mode=TriggerExecutionMode.ONCE, actions=TriggerAction.CREATED, resource=TriggerResource.ITEM)[source]¶
Bases:
dtlpy.entities.trigger.BaseTrigger
Trigger Entity
Execution¶
- class Execution(id, url, creator, created_at, updated_at, input, output, feedback_queue, status, status_log, sync_reply_to, latest_status, function_name, duration, attempts, max_attempts, to_terminate: bool, trigger_id, service_id, project_id, service_version, package_id, package_name, client_api: dtlpy.services.api_client.ApiClient, service, project=None, repositories=NOTHING, pipeline: Optional[dict] = None)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Service execution entity
- classmethod from_json(_json, client_api, project=None, service=None, is_fetched=True)[source]¶
- Parameters
_json – platform json
client_api – ApiClient entity
project – project entity
service –
is_fetched – is Entity fetched from Platform
- progress_update(status: Optional[dtlpy.entities.execution.ExecutionStatus] = None, percent_complete: Optional[int] = None, message: Optional[str] = None, output: Optional[str] = None, service_version: Optional[str] = None)[source]¶
Update Execution Progress
Pipeline¶
- class Pipeline(id, name, creator, org_id, connections, created_at, updated_at, start_nodes, project_id, composition_id, url, preview, description, revisions, info, project, client_api: dtlpy.services.api_client.ApiClient, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Package object
- execute(execution_input=None)[source]¶
execute a pipeline and return the execute
- Parameters
execution_input – list of the dl.FunctionIO or dict of pipeline input - example {‘item’: ‘item_id’}
- Returns
entities.PipelineExecution object
- classmethod from_json(_json, client_api, project, is_fetched=True)[source]¶
Turn platform representation of pipeline into a pipeline entity
- Parameters
_json – platform representation of package
client_api – ApiClient entity
project – project entity
is_fetched – is Entity fetched from Platform
- Returns
Package entity
- set_start_node(node: dtlpy.entities.node.PipelineNode)[source]¶
Set the start node of the pipeline
- Parameters
node (PipelineNode) – node to be the start node
Pipeline Execution¶
- class PipelineExecution(id, nodes, executions, created_at, updated_at, pipeline_id, pipeline_execution_id, pipeline, client_api: dtlpy.services.api_client.ApiClient, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Package object
- classmethod from_json(_json, client_api, pipeline, is_fetched=True)[source]¶
Turn platform representation of pipeline_execution into a pipeline_execution entity
- Parameters
_json – platform representation of package
client_api – ApiClient entity
pipeline – Pipeline entity
is_fetched – is Entity fetched from Platform
- Returns
Package entity
Other¶
Pages¶
- class PagedEntities(client_api: dtlpy.services.api_client.ApiClient, page_offset, page_size, filters, items_repository, has_next_page=False, total_pages_count=0, items_count=0, service_id=None, project_id=None, order_by_type=None, order_by_direction=None, execution_status=None, execution_resource_type=None, execution_resource_id=None, execution_function_name=None, items=[])[source]¶
Bases:
object
Pages object
- get_page(page_offset=None, page_size=None)[source]¶
Get page
- Parameters
page_offset – page offset
page_size – page size
Base Entity¶
Command¶
- class Command(id, url, status, created_at, updated_at, type, progress, spec, error, client_api: dtlpy.services.api_client.ApiClient, repositories=NOTHING)[source]¶
Bases:
dtlpy.entities.base_entity.BaseEntity
Com entity
- classmethod from_json(_json, client_api, is_fetched=True)[source]¶
Build a Command entity object from a json
- Parameters
_json – _json response from host
client_api – ApiClient entity
is_fetched – is Entity fetched from Platform
- Returns
Command object
- in_progress()[source]¶
Check if command is still in one of the in progress statuses
- Returns
True if command still in progress
- Return type