Metadata-Version: 2.1
Name: labelbox
Version: 2.2
Summary: Labelbox Python API
Home-page: https://labelbox.com
Author: Labelbox
Author-email: engineering@labelbox.com
License: UNKNOWN
Description: # Labelbox Python API
        
        Labelbox is the training data workbench for ML teams. It allows you to label
        data with the fastest and most intuitive annotation tools. Visit
        https://labelbox.com/ for more information.
        
        The Labelbox Python API allows you to interact with Labelbox back-end in a
        simple, user-friendly way.
        
        ## Requirements
        
        To use the Labelbox Python API you will need a Labelbox account. Once you login
        to the Labelbox web page, generate an API key as described in the documentation:
        https://labelbox.com/docs/api/api-keys. Store the key to a safe location. You
        will need it for using the Labelbox Python API.
        
        ## Installation
        
        Labelbox Python API can be installed using Python's Pip manager:
        ```
        pip install labelbox
        ```
        
        ## Usage
        
        ### API Key
        
        Your Labelbox API key is required to execute the library. It can be passed to
        Labelbox Python API via an environment variable `LABELBOX_API_KEY`. It is then
        automatically picked up by the `Client`:
        ```
        from labelbox import Client
        client = Client() # will use the API key from the environment variable
        ```
        
        Alternatively you can pass it to the `Client` object initialization:
        ```
        from labelbox import Client
        client = Client("<your_api_key_here>")
        ```
        
        ### Basic commands
        
        The Labelbox Python API allows you to create, update and delete all standard
        Labelbox data types, such as Projects, Datasets, DataRows, Labels and others.
        For more info about the Labelbox data model please visit
        https://labelbox.com/docs.
        
        Here is an example code for uploading some data from scratch:
        ```
        from labelbox import Client
        
        client = Client()
        
        # Create a project and a dataset , automatically reflected on the server
        project = client.create_project(name="My Great Project")
        dataset = client.create_dataset(name="My Dataset")
        project.datasets.connect(dataset)
        
        # Upload some files to the dataset
        task = dataset.create_data_rows(['file1.jpg', 'file2.jpg'])
        # Bulk DataRow creation might take a while on the server-side
        task.wait_till_done()
        
        # Your data is now uploaded to Labelbox and ready for labeling!
        ```
        
        ### Documentation and API specification
        
        Documentation for the Labelbox Python Client package can be found at
        https://labelbox.helpdocs.io/docs/python-client-api. The API documentation
        is available at
        https://labelbox.helpdocs.io/docs/python-client-api/api-specification.
        
Keywords: labelbox
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
