Metadata-Version: 2.4
Name: datasentinel
Version: 0.1.0
Summary: Data Sentinel is a powerful tool to monitor data pipelines and ensure data quality.
Author: Sumz SAS
License: Apache Software License (Apache 2.0)
Project-URL: Homepage, https://github.com/SumzCol/datasentinel
Project-URL: Bug Tracker, https://github.com/SumzCol/datasentinel
Keywords: data quality,data engineering,monitoring,data validation,data pipelines,pipelines,audit logging
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: python-ulid~=2.7.0
Requires-Dist: pydantic~=2.10
Provides-Extra: pyspark-base
Requires-Dist: pyspark<4.0,>=3.4.0; extra == "pyspark-base"
Provides-Extra: deltatable-base
Requires-Dist: delta-spark<4.0,>=3.1.0; extra == "deltatable-base"
Provides-Extra: pandas-base
Requires-Dist: pandas<3.0,>=1.3; extra == "pandas-base"
Provides-Extra: pandas-cualleecheck
Requires-Dist: cuallee[pandas]~=0.15.2; extra == "pandas-cualleecheck"
Provides-Extra: pyspark-cualleecheck
Requires-Dist: cuallee[pyspark]~=0.15.2; extra == "pyspark-cualleecheck"
Provides-Extra: cualleecheck
Requires-Dist: datasentinel[pandas-cualleecheck,pyspark-cualleecheck]; extra == "cualleecheck"
Provides-Extra: pandas-rowlevelresultcheck
Requires-Dist: datasentinel[pandas-base]; extra == "pandas-rowlevelresultcheck"
Provides-Extra: pyspark-rowlevelresultcheck
Requires-Dist: datasentinel[pyspark-base]; extra == "pyspark-rowlevelresultcheck"
Provides-Extra: rowlevelresultcheck
Requires-Dist: datasentinel[pandas-rowlevelresultcheck,pyspark-rowlevelresultcheck]; extra == "rowlevelresultcheck"
Provides-Extra: pandas-checks
Requires-Dist: datasentinel[pandas-cualleecheck,pandas-rowlevelresultcheck]; extra == "pandas-checks"
Provides-Extra: pyspark-checks
Requires-Dist: datasentinel[pyspark-cualleecheck,pyspark-rowlevelresultcheck]; extra == "pyspark-checks"
Provides-Extra: all-checks
Requires-Dist: datasentinel[pandas-checks,pyspark-checks]; extra == "all-checks"
Provides-Extra: spark-deltatableresultstore
Requires-Dist: datasentinel[deltatable-base,pyspark-base]; extra == "spark-deltatableresultstore"
Provides-Extra: all-resultstores
Requires-Dist: datasentinel[spark-deltatableresultstore]; extra == "all-resultstores"
Provides-Extra: database-databaseauditstore
Requires-Dist: SQLAlchemy<3.0,>=1.4; extra == "database-databaseauditstore"
Provides-Extra: spark-deltatableauditstore
Requires-Dist: datasentinel[deltatable-base,pyspark-base]; extra == "spark-deltatableauditstore"
Provides-Extra: all-auditstores
Requires-Dist: datasentinel[database-databaseauditstore,spark-deltatableauditstore]; extra == "all-auditstores"
Provides-Extra: slack-slacknotifier
Requires-Dist: slack-sdk~=3.34.0; extra == "slack-slacknotifier"
Provides-Extra: all-notifiers
Requires-Dist: datasentinel[slack-slacknotifier]; extra == "all-notifiers"
Provides-Extra: email-templateemailmessagerenderer
Requires-Dist: openpyxl==3.1.5; extra == "email-templateemailmessagerenderer"
Requires-Dist: Jinja2==3.1.5; extra == "email-templateemailmessagerenderer"
Provides-Extra: all-renderers
Requires-Dist: datasentinel[email-templateemailmessagerenderer]; extra == "all-renderers"
Provides-Extra: test
Requires-Dist: pytest<9.0,>=7.2; extra == "test"
Requires-Dist: pytest-cov<7,>=3; extra == "test"
Requires-Dist: pendulum>=2.1.2; extra == "test"
Requires-Dist: coverage[toml]; extra == "test"
Requires-Dist: datasentinel[all-auditstores,all-checks,all-notifiers,all-renderers,all-resultstores]; extra == "test"
Provides-Extra: scripts
Requires-Dist: click==8.1.0; extra == "scripts"
Provides-Extra: lint
Requires-Dist: ruff==0.11.12; extra == "lint"
Requires-Dist: pre-commit<5.0,>=2.9.2; extra == "lint"
Requires-Dist: pyright==1.1.403; extra == "lint"
Provides-Extra: all
Requires-Dist: datasentinel[lint,scripts,test]; extra == "all"
Dynamic: license-file

# Data Sentinel

**Data Sentinel** is a comprehensive suite designed to perform data quality validations and log audit data in various destinations. It ensures that your data meets predefined standards and provides comprehensive audit logs for tracking and transparency.

## Features

- **Data Quality Validations**: Execute checks to ensure data accuracy, completeness, consistency, integrity and many more rules.
- **Audit Logging**: Log audit data to multiple sources.
- **Notifications**: Send notifications to different destinations when data quality issues are identified.
- **Data Quality Metrics Logging**: Log metrics related to data quality validations for reporting and analysis.

## Installation

To install **Data Sentinel**, run the following command:

```sh
pip install datasentinel
