Test driven data wrangling.
Project description
Datatest extends the Python standard library’s unittest package to provide testing tools for asserting data correctness.
- Documentation:
- Official Releases:
- Development:
Datatest can help prepare messy data that needs to be cleaned, integrated, formatted, and verified. It can provide structure for the tidying process, automate checklists, log discrepancies, and measure progress.
Installation
The easiest way to install datatest is to use pip:
pip install datatest
Stuntman Mike
If you need bug-fixes or features that are not available in the current official release, you can “pip install” the unstable development version directly from GitHub:
pip install --upgrade https://github.com/shawnbrown/datatest/archive/master.zip
All of the usual caveats of a bleeding-edge install should apply here. Only use an unstable development version if you can risk some instability or if you know exactly what you’re doing. While care is taken to never break the build, it can happen.
Safety-first Clyde
If you need to review and test packages before installing, you can install datatest manually.
Download the latest source distribution from the Python Package Index (PyPI):
Unpack the file (replacing X.Y.Z with the appropriate version number) and review the source code:
tar xvfz datatest-X.Y.Z.tar.gz
Change to the unpacked directory and run the tests:
cd datatest-X.Y.Z python setup.py test
Don’t worry if some of the tests are skipped. Tests for optional data sources (like pandas DataFrames or MS Excel files) are skipped when the related third-party packages are not installed.
If the source code and test results are satisfactory, install the package:
python setup.py install
Supported Versions
Tested on Python 2.6, 2.7, and 3.1 through 3.5; PyPy and PyPy3. Datatest is pure Python and is also likely to run on Jython, Stackless, and other implementations without issue (check using “setup.py test” before installing).
Backward Compatibility
If you have existing tests that use features which have changed since 0.6.0.dev1, you can still run your old code by adding the following import to the beginning of each file:
from datatest.__past__ import api_dev1
To maintain existing test code, this project makes a best-effort attempt to provide backward compatibility support for older features. The API will be improved in the future but only in measured and sustainable ways.
All of the data used at the National Committee for an Effective Congress has been checked with datatest for more than a year so there is, already, a large and growing codebase that relies on current features and must be maintained into the future.
Dependencies
There are no hard dependencies. But if you want to interface with pandas DataFrames, MS Excel workbooks, or other optional data sources, you will need to install the relevant third-party packages (pandas, xlrd, etc.).
Freely licensed under the Apache License, Version 2.0
Copyright 2014 - 2016 NCEC Services, LLC and contributing authors
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