qualidator 0.3.0

A lightweight data quality CLI tool

🛡️ Qualidator

A modern CLI for managing SQL-based data quality checks — now with connector setup.

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📌 Overview

Qualidator is a command-line tool that helps you define, manage, and store SQL-based data quality validations.
It can set up a connector to your data source and organize validation queries in a .qualidations folder for easy reuse and version control.

With Qualidator, you can:

• 📂 Initialize a validations project
• 🔌 Configure a connector (Databricks, Snowflake, Postgres, or None)
• ➕ Add a variety of built-in validation checks
• 🗑 Remove one or all validations
• 📊 View project status and existing validations
• 💥 Destroy the project

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🚀 Installation

pip install qualidator

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⚡ Usage

Run qualidator --help to see available commands:

qualidator --help

Command	Description
init	Initialize .qualidations and optionally set up a data connector
destroy	Delete the .qualidations folder (use --force for full removal)
add	Add a validation
remove	Remove a validation or all validations
status	Show project status and validations
run	Execute validations and show results

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🛠 Examples

1️⃣ Initialize and set up connector

qualidator init

📦 Creates .qualidations, then asks for a data provider:

1. Databricks
2. Snowflake
3. Postgres
4. None

If you pick one of the first three, it prompts for credentials and saves them in:

.qualidations/config.json

2️⃣ Add validations

qualidator add --name is_not_null

Please enter the column name to check for NOT NULL: customer_id
✔ Will check that column "customer_id" is not null.

Supported validations:

Validation	Description
is_not_null	Checks that column values are NOT NULL
has_no_duplicates	Checks that the column has no duplicate values
column_values_are_unique	Checks that all values in the column are unique
column_unique_value_count_is_between	Checks that the number of unique values in the column is between given bounds
column_value_frequency_is_between	Checks that the frequency of each distinct value in the column is within given min and max
no_empty_strings	Checks that the column contains no empty string values
primary_key_check	Checks that the column can serve as a primary key (unique and not null)
distinct_ratio_is_above	Checks that the ratio of distinct values in the column is at least the given threshold
column_max_is_between	Checks that the column's MAX value is between given bounds
column_min_is_between	Checks that the column's MIN value is between given bounds
column_sum_is_between	Checks that the column's SUM value is between given bounds
column_mean_is_between	Checks that the column's MEAN value is between given bounds
column_standard_deviation_is_between	Checks that the column's standard deviation is between given bounds
column_values_are_between	Checks that all values in the column are between given bounds
column_has_no_nulls	Checks that the column contains no NULL values
column_has_values_greater_than	Checks that all values in the column are greater than a given threshold
column_median_is_between	Checks that the median value of the column is between given bounds
column_non_negative	Checks that all values in the column are non-negative
table_row_count_is_between	Checks that the table's row count is between given bounds
table_row_count_equals	Checks that the table's row count equals a given expected count

3️⃣ Check status

qualidator status

============================================================
📋 VALIDATIONS IN YOUR PROJECT
------------------------------------------------------------
1. customer_id_is_not_null
2. email_column_values_are_unique
------------------------------------------------------------
✅ Total: 2 validation(s) ready to go!
💡 You can remove with:
   qualidator remove --name your_validation_name
============================================================

4️⃣ Remove validations

Remove all:

qualidator remove --all

Remove one:

qualidator remove --name email_column_values_are_unique

5️⃣ Run validations

Run all validations:

qualidator run --all

Run a single validation:

qualidator run --name my_catalog_my_schema_my_table_customer_id_is_not_null

6️⃣ Destroy the project

qualidator destroy --force

This deletes .qualidations entirely (including config and validations).

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📂 Project Structure

qualidator/
│
├── connectors/
│   └── databricks.py
├── inspectors/
│   ├── uniq.py
│   ├── numeric.py
├── __init__.py
├── cli.py
├── validations_registry.py
└── README.md

🤝 Contributing

Pull requests and ideas are welcome! Open an issue if you have suggestions for new validation types or integrations.

📜 License

This project is licensed under the MIT License.