py-auto-migrate 0.2.3

A Tool For Transferring Data, Tables, And Datasets Between Different Databases.

𝐏𝐲-𝐀𝐮𝐭𝐨-𝐌𝐢𝐠𝐫𝐚𝐭𝐞

A powerful database migration tool to transfer data (e.g., between MongoDB → MySQL or PostgreSQL and Oracle), with automatic table/database creation, existence checks, and support for full database migrations.

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Installation

pip install py-auto-migrate

Download Shell

If you don’t have Python, or you want to use it with the Shell, you can download the dedicated PAM-Shell from the Releases on GitHub epository.

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Help

py-auto-migrate --help

After installation using pip, open your terminal (command line). This command displays a detailed guide on how to use the package, including available commands, arguments, and examples. It’s the best place to start if you want to quickly understand how to work with py-auto-migrate.

‌But in PAM-Shell , you just need to type `help`

py-auto-migrate> help

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Usage

py-auto-migrate migrate --source <source_uri> --target <target_uri> --table <table_name>

Argument	Description
--source	Source database URI (e.g., mysql://user:pass@host:3306/dbname)
--target	Target database URI (e.g., oracle://:@:/<service_name>)
--table	Optional. Specific table/collection to migrate. If omitted, all tables/collections will be migrated.

Example

Example 1:

py-auto-migrate migrate --source "mongodb://username:password@<host>:<port>/mydb" --target "mongodb://username:password@<host>:<port>/mydb2"

Example 2:

py-auto-migrate migrate --source "postgresql://<user>:<password>@<host>:<port>/mydb" --target "mysql://<user>:<password>@<host>:<port>/mydb" --table users

If the database or table does not exist, it will create them for you based on the column types of the DataFrame.

You can also use MongoDB → MongoDB or PostgreSQL → PostgreSQL

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Supported Databases

Database
MySQL
PostgreSQL
MongoDB
MariaDB
Oracle
Redis
DynamoDB
SQL Server
SQLite

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Future Plans

Feature	Status
Support for Redis migrations	✔️
Support for DynamoDB migrations	✔️
Index creation on tables/collections	Planned
Performance optimizations for large datasets	Planned