https://github.com/quantopian/aqueduct-client

Python wrapper for Quantopian's Aqueduct API
https://github.com/quantopian/aqueduct-client

Last synced: 9 months ago
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Python wrapper for Quantopian's Aqueduct API

• Host: GitHub
• URL: https://github.com/quantopian/aqueduct-client
• Owner: quantopian
• License: apache-2.0
• Created: 2019-05-10T18:14:01.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-04-07T02:37:25.000Z (almost 3 years ago)
• Last Synced: 2025-04-15T07:42:44.855Z (9 months ago)
• Language: Python
• Size: 59.6 KB
• Stars: 2
• Watchers: 12
• Forks: 15
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

          
``AqueductClient``

==================

``AqueductClient`` is a simple Python wrapper around Quantopian's Aqueduct API.

It lets you easily create Pipeline executions and load their results.

``AqueductClient`` supports Python 2.7 and Python 3.4+.

Installation

~~~~~~~~~~~~

.. code-block:: shell

   $ pip install aqueduct-client

Configuration

~~~~~~~~~~~~~

To use ``AqueductClient``, you need a Quantopian API Key.  Once you have it, there

are several ways to use it:

1) Use a credentials file:  create ``~/.quantopian/credentials`` (Linux or OS X) or ``%UserProfile%\.quantopian\credentials`` (Windows) and put the following in it:

  .. code-block:: shell

      [default]

      API_KEY = your_api_key

      

  Users with Windows can follow the steps below in the Command Prompt:

   a) cd %UserProfile%

   b) mkdir .quantopian

   c) cd .quantopian

   d) echo [default] >> credentials && echo API_KEY = 'enter your api key here inside single quotes' >> credentials

2) Use an environment variable: set ``QUANTOPIAN_API_KEY`` to your API key.

3) Pass your API key directly into the ``create_client`` method (see below) using the ``api_key`` kwarg.

Usage

~~~~~

Note: Fuller documentation is available at https://factset.quantopian.com/docs/user-guide/tools/aqueduct.

To use ``AqueductClient``, create an instance. In this case, we are loading credentials from disk or environment variable.

.. code-block:: python

  from aqueduct_client import create_client

  from aqueduct_client.utils import load_api_key

  

  API_KEY = load_api_key()

  client = create_client(API_KEY)

To run a new pipeline execution, use ``submit_pipeline_execution``.  Required parameters are ``code`` (string), ``start_date`` and ``end_date`` (date-like strings, dates, or Pandas timestamps).  Optional parameters are  ``name`` (string), ``params`` (a dict of parameters to pass to your pipeline), and ``asset_identifier_format`` (which can be "symbol", "sid", and "fsym_region_id").  ``submit_pipeline_execution`` returns an id, which you can pass to ``get_pipeline_execution`` to monitor this pipeline's execution status.

``get_all_pipeline_executions`` and ``get_pipeline_execution(id)`` let you load existing pipelines.  Each pipeline has a ``status`` field, which can be ``IN-PROGRESS``, ``SUCCESS``, or ``FAILED``.

For a successful pipeline, ``get_pipeline_results_dataframe(id)`` loads that pipeline's results into a pandas DataFrame.  For a failed pipeline, ``get_pipeline_execution_error(id)`` shows you the information about the error.