Low-level API
Overview
The low-level API is useful if you need to work directly with REST API, but want to have data validation and syntax assistance from your code editor. The code on this layer is autogenerated.
Code of this component is located in cvat_sdk.api_client
.
Example
Let’s see how a task with local files can be created. We will use the basic auth to make things simpler.
from time import sleep
from cvat_sdk.api_client import Configuration, ApiClient, models, apis, exceptions
configuration = Configuration(
host="http://localhost",
username='YOUR_USERNAME',
password='YOUR_PASSWORD',
)
# Enter a context with an instance of the API client
with ApiClient(configuration) as api_client:
# Parameters can be passed as a plain dict with JSON-serialized data
# or as model objects (from cvat_sdk.api_client.models), including
# mixed variants.
#
# In case of dicts, keys must be the same as members of models.I<ModelName>
# interfaces and values must be convertible to the corresponding member
# value types (e.g. a date or string enum value can be parsed from a string).
#
# In case of model objects, data must be of the corresponding
# models.<ModelName> types.
#
# Let's use a dict here. It should look like models.ITaskWriteRequest
task_spec = {
'name': 'example task',
"labels": [{
"name": "car",
"color": "#ff00ff",
"attributes": [
{
"name": "a",
"mutable": True,
"input_type": "number",
"default_value": "5",
"values": ["4", "5", "6"]
}
]
}],
}
try:
# Apis can be accessed as ApiClient class members
# We use different models for input and output data. For input data,
# models are typically called like "*Request". Output data models have
# no suffix.
(task, response) = api_client.tasks_api.create(task_spec)
except exceptions.ApiException as e:
# We can catch the basic exception type, or a derived type
print("Exception when trying to create a task: %s\n" % e)
# Here we will use models instead of a dict
task_data = models.DataRequest(
image_quality=75,
client_files=[
open('image1.jpg', 'rb'),
open('image2.jpg', 'rb'),
],
)
# If we pass binary file objects, we need to specify content type.
# For this endpoint, we don't have response data
(_, response) = api_client.tasks_api.create_data(task.id,
data_request=task_data,
_content_type="multipart/form-data",
# we can choose to check the response status manually
# and disable the response data parsing
_check_status=False, _parse_response=False
)
assert response.status == 202, response.msg
# Wait till task data is processed
for _ in range(100):
(status, _) = api_client.tasks_api.retrieve_status(task.id)
if status.state.value in ['Finished', 'Failed']:
break
sleep(0.1)
assert status.state.value == 'Finished', status.message
# Update the task object and check the task size
(task, _) = api_client.tasks_api.retrieve(task.id)
assert task.size == 4
ApiClient and configuration
The starting point in the low-level API is the cvat_sdk.api_client.ApiClient
class.
It encapsulates session and connection logic, manages headers and cookies,
and provides access to various APIs.
To create an instance of ApiClient
, you need to set up a cvat_sdk.api_client.Configuration
object and pass it to the ApiClient
class constructor. Additional connection-specific
options, such as extra headers and cookies can be specified in the class constructor.
ApiClient
implements the context manager protocol. Typically, you create ApiClient
this way:
from cvat_sdk.api_client import ApiClient, Configuration
configuration = Configuration(host="http://localhost")
with ApiClient(configuration) as api_client:
...
After creating an ApiClient
instance, you can send requests to various server endpoints
via *_api
member properties and directly, using the rest_client
member.
Read more about API wrappers below.
Typically, the first thing you do with ApiClient
is log in.
Read more about authentication options below.
Authentication
CVAT supports 2 authentication options:
- basic auth, with your username and password
- token auth, with your API key
Token auth requires a token, which can be obtained after performing the basic auth.
The low-level API supports 2 ways of authentication.
You can specify authentication parameters in the Configuration
object:
configuration = Configuration(
username='YOUR_USERNAME',
password='YOUR_PASSWORD',
)
configuration = Configuration(
api_key={
"sessionAuth": "<sessionid cookie value>",
"csrfAuth": "<csrftoken cookie value>",
"tokenAuth": "Token <auth key value>",
}
)
You can perform a regular login using the auth_api
member of ApiClient
and
set the Authorization
header using the Token
prefix. This way, you’ll be able to
obtain API tokens, which can be reused in the future to avoid typing your credentials.
from cvat_sdk.api_client import models
(auth, _) = api_client.auth_api.create_login(
models.LoginRequest(username=credentials[0], password=credentials[1])
)
assert "sessionid" in api_client.cookies
assert "csrftoken" in api_client.cookies
api_client.set_default_header("Authorization", "Token " + auth.key)
API wrappers
API endpoints are grouped by tags into separate classes in the cvat_sdk.api_client.apis
package.
APIs can be accessed as ApiClient
object members:
api_client.auth_api.<operation>(...)
api_client.tasks_api.<operation>(...)
And APIs can be instantiated directly like this:
from cvat_sdk.api_client import ApiClient, apis
api_client = ApiClient(...)
auth_api = apis.AuthApi(api_client)
auth_api.<operation>(...)
tasks_api = apis.TasksApi(api_client)
tasks_api.<operation>(...)
For each operation, the API wrapper class has a corresponding <operation>_endpoint
member.
This member represents the endpoint as a first-class object, which provides metainformation
about the endpoint, such as the relative URL of the endpoint, parameter names,
types and their placement in the request. It also allows to pass the operation to other
functions and invoke it from there.
For a typical server entity like Task
, Project
, Job
etc., the *Api
classes provide methods
that reflect Create-Read-Update-Delete (CRUD) operations: create
, retrieve
, list
, update
,
partial_update
, delete
. The set of available operations depends on the entity type.
You can find the list of the available APIs and their documentation here.
Models
Requests and responses can include data. It can be represented as plain Python
data structures and model classes (or models). In CVAT API, model for requests and responses
are separated: the request models have the Request
suffix in the name, while the response
models have no suffix. Models can be found in the cvat_sdk.api_client.models
package.
Models can be instantiated like this:
from cvat_sdk.api_client import models
user_model = models.User(...)
Model parameters can be passed as models, or as plain Python data structures. This rule applies recursively, starting from the method parameters. In particular, this means you can pass a dict into a method or into a model constructor, and corresponding fields will be parsed from this data automatically:
task_spec = models.TaskWriteRequest(
name='example task',
labels=[
models.PatchedLabelRequest(
name="car",
color="#ff00ff",
attributes=[
model.AttributeRequest(
name="a",
mutable=True,
input_type="number",
default_value="5",
values=["4", "5", "6"]
)
]
)
],
)
api_client.tasks_api.create(task_spec)
Is equivalent to:
api_client.tasks_api.create({
'name': 'example task',
"labels": [{
"name": "car",
"color": "#ff00ff",
"attributes": [
{
"name": "a",
"mutable": True,
"input_type": "number",
"default_value": "5",
"values": ["4", "5", "6"]
}
]
}],
})
You can mix these variants.
Most models provide corresponding interface classes called like I<model name>
. They can be
used to implement your own classes or describe APIs. They just provide type annotations
and descriptions for model fields.
You can export model values to plain Python dicts using the as_dict()
method and
the cvat_sdk.api_client.model_utils.to_json()
function.
You can find the list of the available models and their documentation here.
Sending requests
To send a request to a server endpoint, you need to obtain an instance of the corresponding *Api
class. You can find summary about available API classes and supported endpoints
here. The *Api
instance object allows to send requests to the relevant
server endpoints.
By default, all operations return 2 objects: the parsed response data and the response itself. A typical call looks like this:
from cvat_sdk.api_client import ApiClient, apis
with ApiClient(...) as api_client:
...
(data, response) = api_client.tasks_api.list()
# process the response ...
Operation parameters can be passed as positional or keyword arguments. There are also several extra arguments which change invocation logic:
_parse_response
- Allows to enable and disable response data parsing. When enabled, the response data is parsed into a model or a basic type and returned as the first value. When disabled, the response is not parsed, andNone
is returned. Can be useful, for instance, if you need to parse data manually, or if you expect an error in the response._check_status
- Allows to enable or disable response status checks. When enabled, the response status code is checked to be positive as defined in the HTTP standards. In case of negative status, an exception is raised._request_timeout
- Allows to control timeout_content_type
- Allows to specify theContent-Type
header value for the request. Endpoints can support different content types and behave differently depending on the value. For file uploads_content_type="multipart/form-data"
must be specified.
NOTE: the API is autogenerated. In some cases the server API schema may be incomplete or underspecified. Please report to us all the problems found. A typical problem is that a response data can’t be parsed automatically due to the incorrect schema. In this case, the simplest workaround is to disable response parsing using the
_parse_response=False
method argument.
You can find many examples of API client usage in REST API tests here.
Organizations
To call an operation in the context of an organization, use one of these method arguments:
org
- The unique organization slugorg_id
- The organization id
...
(updated_annotations, response) = api_client.tasks_api.partial_update_annotations(
id=task_id,
org_id=org_id,
action='update',
patched_labeled_data_request=data
)
Paginated responses
There are several endpoints that allow to request multiple server entities. Typically, these
endpoints are called list_...
. When there are lots of data, the responses can be paginated to
reduce server load. If an endpoint returns paginated data, a single page is returned per request.
In some cases all entries need to be retrieved. CVAT doesn’t provide specific API or parameters
for this, so the solution is to write a loop to collect and join data from multiple requests.
SDK provides an utility function for this at cvat_sdk.core.helpers.get_paginated_collection()
.
Example:
from cvat_sdk.core.helpers import get_paginated_collection
...
project_tasks = get_paginated_collection(
api_client.projects_api.list_tasks_endpoint,
id=project_id,
)