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Simplify the testing of SQL data models and queries by allowing users to mock input data and create tests for various scenarios. It provides a consistent and convenient way to test the execution of your query without the need to process a massive amount of data.

Project description

SQL Mock: Python Library for Mocking SQL Queries with Dictionary Inputs

PyPI version Supported Python versions License: MIT

The primary purpose of this library is to simplify the testing of SQL data models and queries by allowing users to mock input data and create tests for various scenarios. It provides a consistent and convenient way to test the execution of your query without the need to process a massive amount of data.

Documentation

A full documentation can be found on the documentation page

The library currently supports the following databases.

  • BigQuery
  • Clickhouse

Installation

The library can be installed from PyPI using pip:

# BigQuery
pip install --upgrade "sql-mock[bigquery]"

# Clickhouse
pip install --upgrade "sql-mock[clickhouse]"

If you need to modify this source code, install the dependencies using poetry:

poetry install --all-extras

Contributing

We welcome contributions to improve and enhance this open-source project. Whether you want to report issues, suggest new features, or directly contribute to the codebase, your input is valuable. To ensure a smooth and collaborative experience for both contributors and maintainers, please follow these guidelines:

Reporting Issues

If you encounter a bug, have a feature request, or face any issues with the project, we encourage you to report them using the project's issue tracker. When creating an issue, please include the following information:

  • A clear and descriptive title.
  • A detailed description of the problem or suggestion.
  • Steps to reproduce the issue (if applicable).
  • Any error messages or screenshots that help clarify the problem.

Feature Requests

If you have ideas for new features or improvements, please use the project's issue tracker to submit a feature request. We appreciate well-documented feature requests that explain the motivation and potential use cases.

Contributing Code

Find more about contributing code in the Contribution Guidelines

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