Skip to main content

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.

The "Binder" tool allows you to run it interactively in your browser. Click on Binder then wait a couple of seconds. After loading a list of files should be displayed. Click on index.ipynb to open the tutorial notebook, where you'll be able to play with the DBnomics Python client.

Install

pip install dbnomics

See also: https://pypi-hypernode.com/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 --editable .

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 set the default API URL by monkey-patching the dbnomics module, like this:

import dbnomics
dbnomics.default_api_base_url = "http://localhost:5000"

Tests

Run tests:

pytest

# Specify an alterate API URL
API_URL=http://localhost:5000 pytest

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DBnomics-1.0.2.tar.gz (5.5 kB view details)

Uploaded Source

Built Distribution

DBnomics-1.0.2-py3-none-any.whl (17.4 kB view details)

Uploaded Python 3

File details

Details for the file DBnomics-1.0.2.tar.gz.

File metadata

  • Download URL: DBnomics-1.0.2.tar.gz
  • Upload date:
  • Size: 5.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3

File hashes

Hashes for DBnomics-1.0.2.tar.gz
Algorithm Hash digest
SHA256 c3016f7170c3c2321aba14c2946db4fcb0ef3ab3e0749ab71351c47f0fb5bdec
MD5 cdaad23aa679f57ce8386986034d88a4
BLAKE2b-256 db1e9f1120443deab1847f1b09a11bca4a8f20f47caedff02f4551675b6ba9ae

See more details on using hashes here.

File details

Details for the file DBnomics-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: DBnomics-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 17.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3

File hashes

Hashes for DBnomics-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 66aa368edc47c377351311dd2eaef0924bf2f62d62e1c33b58e2c218bbf1b6a1
MD5 ae6511957d4216226c0ea84f39e14632
BLAKE2b-256 8ed9412e6790004f0ee32d8f3c10491a75f8d5a91ae7c4a7c6ca00a9c1830416

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page