orbl-onpremise 0.1.1

A Python package for interacting with ORBL on-premise API

Python API client for ORBL on-premise API

---

This library is mirror of official ORBL on-premise API in terms of methods and interfaces.

For your convenience, you can make API calls using sync or async (asyncio) interface.

Installation

pip install orbl_onpremise

Note that it is always recommended pinning version of your installed packages.

Usage example (sync)

An example of how to create an origin:

from orbl_onpremise import Client


if __name__ == '__main__':
    # api_token is just str with your API token
    api_token = "abcd012345"
    # Now create instance of Client. There should be only one per process.
    client = Client(base_url="http://localhost:8080", api_token=api_token)
    # Issue API request to create an origin
    client.origins.create(name="test_name")

Now that we have our origin created, we can create profile inside that origin:

from orbl_onpremise import Client


def create_profiles_example(client: Client):
    origin_id = 1  # you can inspect response from `client.origins.create`
    with open("image.png", "rb") as f:
        response = client.profiles.create(
            image=f,
            origin_id=origin_id
        )
    print("Profiles Create Response:\n", response.json(), flush=True)


if __name__ == '__main__':
    # api_token is just str with your API token
    api_token = "abcd012345"
    # Now create instance of Client. There should be only one per process.
    client = Client(base_url="http://localhost:8080", api_token=api_token)
    # Issue API request to create a profile
    create_profiles_example(client)

Now that we have our origin & profile created, we can search for profile:

from orbl_onpremise import Client


def search_profiles_example(client: Client):
    with open("image.png", "rb") as f:
        response = client.profiles.search(
            image=f,
            identify_asm=True
        )
    print("Profiles Search Response:\n", response.json(), flush=True)


if __name__ == '__main__':
    # api_token is just str with your API token
    api_token = "abcd012345"
    # Now create instance of Client. There should be only one per process.
    client = Client(base_url="http://localhost:8080", api_token=api_token)
    # Issue API request to search profiles
    search_profiles_example(client)

For more examples and usage, please refer to the docs.

Development setup

To install all the development requirements:

pip install --upgrade pip
pip install poetry
poetry install --no-root

To run linters & test suite:

./scripts/test.sh

How to release

1. Update version in:
   • CHANGELOG.md
   • __init__.py
   • pyproject.toml
2. Lock deps to update version in poetry: poetry lock
3. Get API Token from account settings in PyPI
4. poetry config pypi-token.pypi YOUR_API_TOKEN
5. poetry build
6. poetry publish

Release History

• 0.1.1
  • Fixed types of custom Enum classes and in corresponding methods
• 0.1.0
  • Initial version of package

License

Distributed under the MIT license. See LICENSE for more information.

Contributing

1. Create your feature branch (git checkout -b feature/fooBar)
2. Commit your changes (git commit -am 'Add some fooBar')
3. Push to the branch (git push origin feature/fooBar)
4. Create a new Pull Request