s3sql 0.0.3

A simple CLI to query cloud storage objects with SQL.

S3SQL

Overview

S3SQL is a lightweight command line utility for querying data stored in s3.

Features

• Return S3 data straight to your terminal
• Write SQL queries to filter and manipulate S3 data
• List S3 objects available to current scoped credentials

Demo

Installation

1. Install with:

   pip install s3sql
   

Usage

1. Open a new terminal window

2. Test the CLI is properly configured with:

   s3sql --help
   

3. Set the AWS access key with:

   s3sql set-key --api-key AKIA*******
   

   This command returns the following message:

   API secret saved successfully!
   

[!TIP] Credentials are stored in the ~/s3sql directory. I.E. Windows = C:\Users\Ian\s3sql\credentials MacOS = /Users/Ian/s3sql

4. Set the AWS access secret with:

   s3sql set-secret --api-secret Gy096********
   

   This command returns the following message:

   API key saved successfully!
   

[!TIP] Credentials are stored in the ~/s3sql directory. I.E. Windows = C:\Users\Ian\s3sql\credentials MacOS = /Users/Ian/s3sql

5. List objects available. For example, to list the objects in the bucket named: osg-repo-scan-data:

   s3sql ls --bucket "s3sql-demo"
   

   This command returns a formatted table of the objects available in the bucket:

   Query executed in 0.3216 seconds
   +------------------------------------------+---------------------------+------------------------------------+---------------------+--------+----------------+
   | Key                                      | LastModified              | ETag                               | ChecksumAlgorithm   |   Size |StorageClass   |
   +==========================================+===========================+====================================+=====================+========+================+
   | folder_example/                          | 2025-06-13 01:22:05+00:00 | "d41d8cd98f00b204e9800998ecf8427e" | ['CRC64NVME']       |      0 | STANDARD       |
   +------------------------------------------+---------------------------+------------------------------------+---------------------+--------+----------------+
   | folder_example/sql_database_releases.csv | 2025-06-13 01:57:02+00:00 | "90089983c8e30097002094756b5f7478" | ['CRC64NVME']       |    438 | STANDARD       |
   +------------------------------------------+---------------------------+------------------------------------+---------------------+--------+----------------+
   | sql_database_features.csv                | 2025-06-13 01:45:38+00:00 | "8a46b42d596d9310bcd4ac9db14df718" | ['CRC64NVME']       |   1991 | STANDARD       |
   +------------------------------------------+---------------------------+------------------------------------+---------------------+--------+----------------+
   | sql_engines.csv                          | 2025-06-13 01:21:49+00:00 | "586f00530a11fcbb46c244210f625292" | ['CRC64NVME']       |    407 | STANDARD       |
   +------------------------------------------+---------------------------+------------------------------------+---------------------+--------+----------------+
   | sql_user_base.csv                        | 2025-06-13 01:45:58+00:00 | "ff5e96d2ca7f3475dc38c537cc1f6c36" | ['CRC64NVME']       |    597 | STANDARD       |
   +------------------------------------------+---------------------------+------------------------------------+---------------------+--------+----------------+
   

6. Query an object with the following command:

   s3sql query --uri "s3://s3sql-demo/sql_engines.csv" --sql "SELECT * FROM df WHERE 1=1"
   

   This command returns a formatted table of the data from the specified object:

   Query executed in 0.4116 seconds
   +------+---------------+-----------+--------------------+-------------------------------------+-------------------------+
   |   Id | engine_name   |   version | license_type       | developer                           | primary_use_case        |
   +======+===============+===========+====================+=====================================+=========================+
   |    1 | SQLite        |      3.46 | Public Domain      | D. Richard Hipp                     | Embedded systems        |
   +------+---------------+-----------+--------------------+-------------------------------------+-------------------------+
   |    2 | PostgreSQL    |     16.4  | PostgreSQL License | PostgreSQL Global Development Group | General-purpose OLTP    |
   +------+---------------+-----------+--------------------+-------------------------------------+-------------------------+
   |    3 | MySQL         |      8.4  | GPLv2              | Oracle Corporation                  | Web applications        |
   +------+---------------+-----------+--------------------+-------------------------------------+-------------------------+
   |    4 | SQLServer     |   2022    | Proprietary        | Microsoft Corporation               | Enterprise applications |
   +------+---------------+-----------+--------------------+-------------------------------------+-------------------------+
   |    5 | DuckDB        |      1    | MIT License        | DuckDB Labs                         | Analytical queries      |
   +------+---------------+-----------+--------------------+-------------------------------------+-------------------------+
   

   Apply a LIMIT 1 to the previous query:

   s3sql query --uri "s3://s3sql-demo/sql_engines.csv" --sql "SELECT * FROM df WHERE 1=1 LIMIT 1"
   

   This command returns a formatted table of the data from the specified object:

   Query executed in 0.3426 seconds
   +------+---------------+-----------+----------------+-----------------+--------------------+
   |   Id | engine_name   |   version | license_type   | developer       | primary_use_case   |
   +======+===============+===========+================+=================+====================+
   |    1 | SQLite        |      3.46 | Public Domain  | D. Richard Hipp | Embedded systems   |
   +------+---------------+-----------+----------------+-----------------+--------------------+
   

7. Query an object and output the query results to a file with the following command:

   s3sql query --uri "s3://s3sql-demo/folder_example/sql_database_releases.csv" --sql "SELECT * FROM df WHERE 1=1 LIMIT 1" --out "output.csv"
   

   This command returns a formatted table of the data with an additional message specifying the filename the data was written to:

   Query executed in 0.3414 seconds
   +---------------+------------------------+-----------------+-----------------------+--------------------------+
   | engine_name   |   initial_release_year | designer        | organization          | current_stable_version   |
   +===============+========================+=================+=======================+==========================+
   | SQLite        |                   2000 | D. Richard Hipp | Hipp Wyrick & Company | 3.50.1                   |
   +---------------+------------------------+-----------------+-----------------------+--------------------------+
   Data successfully written to file: output.csv
   

8. Query an object within the folder_example folder with the following command:

   s3sql query --uri "s3://s3sql-demo/folder_example/sql_database_releases.csv" --sql "SELECT * FROM df WHERE 1=1"
   

   This command returns a formatted table of the data from the specified object:

   Query executed in 0.3591 seconds
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | engine_name   |   initial_release_year | designer                            | organization                       | current_stable_version   |
   +===============+========================+=====================================+====================================+==========================+
   | SQLite        |                   2000 | D. Richard Hipp                     | Hipp Wyrick & Company              | 3.50.1                   |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | PostgreSQL    |                   1986 | Michael Stonebraker                 | University of California  Berkeley | 16.4                     |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | MySQL         |                   1995 | Michael Widenius and David Axmark   | MySQL AB                           | 8.4                      |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | SQLServer     |                   1989 | Donald Chamberlin and Raymond Boyce | Microsoft Corporation              | 2022                     |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | DuckDB        |                   2019 | Mark Raasveldt and Hannes Muhleisen | Centrum Wiskunde & Informatica     | 1.0.0                    |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   

9. Query an object and save the output to your local file system using the following command:

   s3sql query --uri "s3://s3sql-demo/folder_example/sql_database_releases.csv" --sql "SELECT * FROM df WHERE 1=1 LIMIT 1" --out "output.csv"
   

   This command returns a formatted table of the data from the specified object and an additional Data successfully written to file: output.csv:

   Query executed in 0.3391 seconds
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | engine_name   |   initial_release_year | designer                            | organization                       | current_stable_version   |
   +===============+========================+=====================================+====================================+==========================+
   | SQLite        |                   2000 | D. Richard Hipp                     | Hipp Wyrick & Company              | 3.50.1                   |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | PostgreSQL    |                   1986 | Michael Stonebraker                 | University of California  Berkeley | 16.4                     |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | MySQL         |                   1995 | Michael Widenius and David Axmark   | MySQL AB                           | 8.4                      |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | SQLServer     |                   1989 | Donald Chamberlin and Raymond Boyce | Microsoft Corporation              | 2022                     |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   | DuckDB        |                   2019 | Mark Raasveldt and Hannes Muhleisen | Centrum Wiskunde & Informatica     | 1.0.0                    |
   +---------------+------------------------+-------------------------------------+------------------------------------+--------------------------+
   Data successfully written to file: output.csv
   

10. Query a .csv object and convert it to a .parquet file with the following command:

s3sql query --uri "s3://s3sql-demo/sql_engines.csv" --sql "SELECT * FROM df WHERE 1=1 LIMIT 1" --out "output.parquet"

This command returns a formatted table of the data from the specified object and an additional Data successfully written to file: output.parquet:

Query executed in 0.3399 seconds
+------+---------------+-----------+----------------+-----------------+--------------------+
|   Id | engine_name   |   version | license_type   | developer       | primary_use_case   |
+======+===============+===========+================+=================+====================+
|    1 | SQLite        |      3.46 | Public Domain  | D. Richard Hipp | Embedded systems   |
+------+---------------+-----------+----------------+-----------------+--------------------+
Data successfully written to file: output.parquet

Directory Structure

project/
├── .github/
│   └── workflows/
│       └── publish.yml
├── dist/
│   └── s3sql-*.*.*-py3-none-any.whl
│   └── s3sql-*.*.*.tar.gz
├── s3sql/
│   └── cli.py
│   └── test_cli.py
├── .env
├── .gitignore
├── mycli.spec
├── poetry.lock
└── README.md

Testing

• Use the PyTest VS code extension or the following command to run all tests pytest -s s3sql/test_cli.py:

  

Github

https://github.com/Ian-Fogelman/s3sql

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Rebase your current branch (git pull --rebase)
4. Add changes to your commit (git add .)
5. Commit your changes (git commit -m 'Add your feature')
6. Push to the branch (git push origin feature/your-feature)
7. Create a Pull Request

PyPI

https://pypi.org/project/s3sql/

License

This project is licensed under the MIT License - see the LICENSE file for details.