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airqo-platform / AirQo-api

This repo contains API definitions for the AirQo platform
MIT License
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Integration of Great Expectations with Airflow DAGs and Unit Testing[WIP] #3231

Closed AnthonyByansi closed 1 week ago

AnthonyByansi commented 3 weeks ago

WHAT DOES THIS PR DO?

WHAT ISSUES ARE RELATED TO THIS PR? AirQo's Data Quality Checks for data profiling process

Summary by CodeRabbit

codecov[bot] commented 3 weeks ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 30.13%. Comparing base (214d559) to head (78cfd26). Report is 96 commits behind head on staging.

Additional details and impacted files [![Impacted file tree graph](https://app.codecov.io/gh/airqo-platform/AirQo-api/pull/3231/graphs/tree.svg?width=650&height=150&src=pr&token=HHq3qS3cL6&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=airqo-platform)](https://app.codecov.io/gh/airqo-platform/AirQo-api/pull/3231?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=airqo-platform) ```diff @@ Coverage Diff @@ ## staging #3231 +/- ## =========================================== - Coverage 30.30% 30.13% -0.18% =========================================== Files 184 184 Lines 24487 24634 +147 Branches 3205 3227 +22 =========================================== + Hits 7421 7423 +2 - Misses 16952 17096 +144 - Partials 114 115 +1 ``` [see 3 files with indirect coverage changes](https://app.codecov.io/gh/airqo-platform/AirQo-api/pull/3231/indirect-changes?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=airqo-platform)
coderabbitai[bot] commented 3 weeks ago
Walkthrough ## Walkthrough The recent updates enhance the AirQo-api project with the integration of Great Expectations for data validation. These changes introduce configurations, expectation suites for air quality datasets, and a setup guide. Additionally, development dependencies are specified to ensure compatibility with Apache Airflow, Great Expectations, and other key tools. ## Changes | File/Path | Change Summary | |-------------------------------------------------------------|----------------------------------------------------------------------------------------------------------| | `gx/.gitignore` | Adds rules to ignore files and directories in the Git repository, including Python files, data, logs, Jupyter Notebooks, and OS-specific files. | | `gx/README.md` | Provides setup and usage instructions for integrating Great Expectations with the AirQo-api project, including directory structure, getting started steps, creating expectation suites, running validations, viewing results, and an example with Airflow DAG. | | `gx/dev-requirements.txt` | Introduces a set of dependencies for the project, including key tools like Apache Airflow, Great Expectations, pytest, SQLAlchemy, pandas-gbq, and Google Cloud BigQuery. | | `gx/expectations/air_quality_completeness.json` | Defines an expectation suite ensuring specific columns like `station_code`, `timestamp`, `temperature`, `humidity`, and others do not contain null values. | | `gx/expectations/air_quality_referential_integrity.json` | Defines an expectation suite for the "station_code" column to have values within a predefined set. | | `gx/expectations/air_quality_schema_validation.json` | Sets expectations for columns in an air quality dataset, ensuring the presence and correct data types for specific columns. | | `gx/expectations/air_quality_uniqueness_integrity.json` | Defines expectations related to air quality, checking for unique column values, compound column uniqueness, and column data types. | | `gx/great_expectations.yml` | Introduces Great Expectations configuration settings, including datasources, stores, plugins directory, data docs sites, and anonymous usage statistics. | ## Poem > In data's dance, precision reigns, > Expectations set, no room for pains. > Airflows guide the cleansing streams, > Validations safeguard our dreams. > Great is the hope that quality brings, > Now AirQo's data truly sings.

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