DBnomics Python Client
Project description
DBnomics Python client
Access DBnomics time series from Python.
This project relies on Python Pandas.
Tutorial
A tutorial is available as a Jupyter notebook.
Use with a proxy
This Python package uses requests, which is able to work with a proxy (HTTP/HTTPS, SOCKS). For more information, please check its documentation.
Install
pip install dbnomics
See also: https://pypi.org/project/DBnomics/
Development
To work on dbnomics-python-client source code:
git clone https://git.nomics.world/dbnomics/dbnomics-python-client.git
cd dbnomics-python-client
pip install -r requirements.txt
pip install -r requirements-dev.txt
pip install -e .
If you plan to use a local Web API, running on the port 5000, you'll need to use the api_base_url
parameter of the fetch_*
functions, like this:
dataframe = fetch_series(
api_base_url='http://localhost:5000',
provider_code='AMECO',
dataset_code='ZUTN',
)
Or globally change the default API URL used by the dbnomics
module, like this:
import dbnomics
dbnomics.default_api_base_url = "http://localhost:5000"
Open the demo notebook
Install jupyter if not already done, in a virtualenv:
pip install jupyter
jupyter notebook index.ipynb
Tests
Run tests:
# Only once
pip install -r requirements.txt
pip install -r requirements-test.txt
pip install -e .
pytest
# Specify an alterate API URL
API_URL=http://localhost:5000 pytest
Release
To release a version on PyPI:
- merge one or many feature branches into master (no need to do a release for every feature...)
- update
setup.py
incrementing the package version (we use Semantic Versioning so determine if it's a major, minor or patch increment) - ensure the changelog is up to date
git commit setup.py CHANGELOG.md -m "Release"
- create a Git tag with a
v
before version number and push it (git tag v1.2.0; git push; git push --tags
) - the CI will run a job to publish the package on PyPI at https://pypi.org/project/DBnomics/
It's advised to do pip install -e .
to let your virtualenv know about the new version number.
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