Python API client for performing REST calls to configurable data curation system (CDCS) databases
# Python CDCS REST API client
This is a base Python package for accessing instances of the NIST Configurable Data Curation System (CDCS) databases, versions 2+. It defines a Python CDCS class that streamlines REST calls to a database by
- Taking access settings once (username, password, etc) and saving them for subsequent REST calls.
- Defining methods that wrap around REST calls to interact with the database in a more Pythonic way.
- Automatically converting any accessed information to pandas Series and DataFrame objects to allow for the information to be easily manipulated.
The package can be installed using pip:
pip install pycdcs
or conda (comming soon):
conda install -c conda-forge pycdcs
Alternatively, the source code can be downloaded from github at [https://github.com/lmhale99/pycdcs](https://github.com/lmhale99/pycdcs)
Documentation for the package is given as Jupyter Notebooks that can be found on the github site. Each Notebook is focused on providing details and examples related to different use cases for the package.
- CDCS Public Data Exploration outlines the basic functions allowing an anonymous user (i.e. not logged in) to explore the available public data on a curator.
- CDCS Data Management outlines the basic pre-defined functions allowing a logged-in user to manage their own templates, data records and blobs.
- CDCS Rest Builder provides a simple explanation of how users can easily build their own functions and make their own REST API calls should they wish to interact with the database in ways outside the pre-defined functions.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size cdcs-0.1.4-py3-none-any.whl (15.6 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size cdcs-0.1.4.tar.gz (11.4 kB)||File type Source||Python version None||Upload date||Hashes View|