REST API, local file store

Benchmarking usually happens on a different job when running CI jobs and cannot be included in the documentation unless they are stored somewhere. A REST API is better than a local file because it can be distance and do not rely on local path. These functions are a simple implementation of an API to store and retrieve dataframes with FastAPI.

REST API

pyquickhelper.server.filestore_fastapi.fast_api_submit (df, client = None, url = None, name = None, team = None, project = None, version = None, password = None)

Stores a dataframe into a local stores.

pyquickhelper.server.filestore_fastapi.fast_api_query (client = None, url = None, name = None, team = None, project = None, version = None, password = None, as_df = False)

Retrieves the list of dataframe based on partial information.

pyquickhelper.server.filestore_fastapi.fast_api_content (client = None, url = None, name = None, team = None, project = None, version = None, limit = 5, password = None, as_df = True)

Retrieves the dataframes based on partial information. Enumerates a list of dataframes.

pyquickhelper.server.filestore_fastapi.create_app ()

Creates an instance of application class returned by create_fast_api_app. It checks that environment variables PYQUICKHELPER_FASTAPI_PWD and PYQUICKHELPER_FASTAPI_PATH are set up with a password and a filename. Otherwise, the function raised an exception.

Inspired from the guidelines uvicorn/deployment, (2). Some command lines…

File Storage

pyquickhelper.server.filestore_sqlapi.SqlLite3FileStore