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-3.0.7.tar.gz (396.5 kB view details)

Uploaded Source

Built Distribution

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

tdda-3.0.7-py3-none-any.whl (455.3 kB view details)

Uploaded Python 3

File details

Details for the file tdda-3.0.7.tar.gz.

File metadata

  • Download URL: tdda-3.0.7.tar.gz
  • Upload date:
  • Size: 396.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.5

File hashes

Hashes for tdda-3.0.7.tar.gz
Algorithm Hash digest
SHA256 af5160f3ff30ff1c6b5d4fec55e8be34ded0072c8e138e7549b844c1ae5f4caf
MD5 49642b30eae14a806ac219484eb0e8cc
BLAKE2b-256 bb6b764c45a1adf5ba1defcc18a761d3df50bfeb1f8bb09a4f4aa7d4fb82905c

See more details on using hashes here.

File details

Details for the file tdda-3.0.7-py3-none-any.whl.

File metadata

  • Download URL: tdda-3.0.7-py3-none-any.whl
  • Upload date:
  • Size: 455.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.5

File hashes

Hashes for tdda-3.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 ec87dc4efdf42dcf7a4634186321579b9dd1ada4818dbdf0ab64026ae6e97335
MD5 15174d35d3ec3f9875d35bd18b28e407
BLAKE2b-256 0fdaa43e0905661b4a6fc9dc15b6b4e48f05a915f1dc68755ecbb5af2394b9ab

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