A full python stack application for acquiring financial data and generating arbitrary data sets. Can be deployed as a REST API for dataset generation as a service, or run from the command line to create ad-hoc data sets for machine learning.
Currently, the simplest method for installing is from source. This guide assumes that Python 3.7 or greater is installed with pip and virtualenv available. It is assumed and recommended that a virtual environment is created, and will be denoted in the scripts shown:
$> git clone https://github.com/UVU-PFP-Research/Personal-Financial-Planner
$> cd Personal-Financial-Planner/stock-data-acquisition
(env) $> python setup.py installOnce the installation has been completed, you'll want to run the installer to setup the database. The installer can be found within the sDAS package and can be run by calling:
(env) $> python -m pydas.install -h
usage: install.py [-h] [-a ALEMBIC] [-r REQUIREMENTS] [-u USERNAME]
[-p PASSWORD] [-d DATABASE] [--deploy-rest]
Stock Data Acquisition Service installation script for configuring the
metadata database and REST API on a server.
optional arguments:
-h, --help show this help message and exit
-a ALEMBIC, --alembic ALEMBIC
Path to alembic configuration file (typically
alembic.ini)
-r REQUIREMENTS, --requirements REQUIREMENTS
Path to project dependency file (typically
requirements.txt)
-u USERNAME, --user USERNAME
Database username for opening connections
-p PASSWORD, --password PASSWORD
Database password for opening connections
-d DATABASE, --database DATABASE
Database name to deploy metadata database into
--deploy-rest Flag indicating whether the REST API server should be
deployed. DO NOT USE THIS OPTION! uWSGI support is not
currently supported and using this flag will result in
undefined/unsupported behavior.Once the installer has been executed, the sDAS metadata database will be deployed, and (optionally) the REST API deployed.