Skip to main content

Test-driven data analysis: command-line tools and Python APIs for data validation, testing analytical pipelines, automatic test generation and more.

Project description

Test-Driven Data Analysis (TDDA)

The tdda package provides Python support for test-driven data analysis (1-page summary, blog, book).

Features

  • Reference Testing (tdda.referencetest): extensions to unittest and pytest for testing data analysis pipelines. Supports file-based comparisons, semantic equivalence, automatic rewriting of reference results, and test tagging.

  • Automatic Test Generation (tdda gentest): generates reference tests for any command-line script or program (Python, R, shell, Makefile, ...). *"Gentest writes tests, so you don't have to."*™

  • Constraints (tdda.constraints): discovers constraints from Pandas DataFrames, Parquet files, flat files, and relational databases; verifies new data against those constraints; detects failing records.

  • Regular Expression Inference (tdda.rexpy): automatically infers regular expressions from a column of string data.

  • Data Diff (tdda diff): compares data frames in Parquet or flat files and reports differences in a visual format.

  • Serial Format (tdda.serial): documents CSV and flat-file formats in .serial metadata files for accurate, portable reading and writing. Supports conversion to/from CSVW and Frictionless metadata.

  • Utility Functions (tdda.utils): Unicode normalization (Normal Form TK), glyph counting, and RFC 9839 support.

Documentation

Full documentation: tdda.readthedocs.io

Installation

pip install tdda

To upgrade an existing installation:

pip install -U tdda

Source installation

git clone https://github.com/tdda/tdda.git
cd tdda
pip install .

Optional database support

pip install pygresql                  # PostgreSQL
pip install mysql-connector-python   # MySQL/MariaDB
pip install pymongo                  # MongoDB

Testing

tdda test

Resources

Authors

  • Nick Radcliffe
  • Simon Brown

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

tdda-3.0.6.tar.gz (20.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tdda-3.0.6-py3-none-any.whl (20.8 MB view details)

Uploaded Python 3

File details

Details for the file tdda-3.0.6.tar.gz.

File metadata

  • Download URL: tdda-3.0.6.tar.gz
  • Upload date:
  • Size: 20.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for tdda-3.0.6.tar.gz
Algorithm Hash digest
SHA256 dfa0997073a853245665251f41ce20808e83e2d959240e0eb3d712c9fc39ab0b
MD5 654246360447015792d004a6ce04cc33
BLAKE2b-256 49805de7f64849cf935bdce8d1443d6b55ffadf17d71e0174288c784f88c7ae6

See more details on using hashes here.

File details

Details for the file tdda-3.0.6-py3-none-any.whl.

File metadata

  • Download URL: tdda-3.0.6-py3-none-any.whl
  • Upload date:
  • Size: 20.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for tdda-3.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 d98af64aa528f1147183f0fcb8d1aafd50c0c9d2e9036bf5f3c1741a49ebb258
MD5 8b06835da7602e0078bbe42f50a8cf6c
BLAKE2b-256 c49a8a1c81917018a62f368ff7a41dd6527d02413a00a8cdf1271d3be1e57ecb

See more details on using hashes here.

Supported by

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