rdsclient 0.1.0

A Python wrapper for querying AWS RDS with mysql-connector-python, returning Pandas or Spark DataFrames.

rdsclient

is a Python package designed to simplify the interaction with AWS RDS instances using the package. It allows executing SQL queries and fetching the results as Pandas or Spark DataFrames.

Features

• Singleton RDS connection: Ensures a single connection to the RDS instance.
• Query execution: Execute SELECT, INSERT, UPDATE, DELETE queries on your RDS database.
• Return data as Pandas DataFrame: Fetch query results directly as Pandas DataFrames for easy data manipulation.
• Spark DataFrame support: Optionally convert query results to Spark DataFrames for distributed computing.
• Context-managed MySQL connection: Automatically manage the connection lifecycle with Python's .

Installation

You can install directly from PyPI:

pip install rdsclient

Prerequisites

• Python 3.7+

• Dependencies:

These dependencies are automatically installed when you install .

Usage

Simple Query Example

from rdsclient import query_rds

# Define your RDS connection details
host = 'your-rds-host'
user = 'your-username'
password = 'your-password'
database = 'your-database'

# Execute the query and get the result as a Pandas DataFrame
df = query_rds(
    query='SELECT * FROM your_table',
    host=host,
    user=user,
    password=password,
    database=database
)

# Display the result
print(df.head())

Using the RDS Class Directly

from rdsclient import RDS

# Create an RDS instance
rds = RDS(
    host='your-rds-host',
    user='your-username',
    password='your-password',
    database='your-database'
)

# Execute a query and fetch results as a Pandas DataFrame
df = rds.execute_query('SELECT * FROM your_table')

# Optionally, get the results as a Spark DataFrame
spark_df = rds.query_to_spark_df('SELECT * FROM your_table')

# Display the Pandas DataFrame
print(df.head())

Executing Non-Select Queries

You can also execute non-SELECT queries (such as INSERT, UPDATE, DELETE):

# Example for executing an UPDATE query
affected_rows = rds.execute_update('UPDATE your_table SET column_name = %s WHERE condition = %s', ('new_value', 'condition_value'))

print(f'{affected_rows} rows affected.')

Contributing

Contributions are welcome! If you find a bug or have a feature request, please feel free to open an issue or submit a pull request.

Steps for Contributing:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -am 'Add feature').
4. Push to the branch (git push origin feature-name).
5. Create a new pull request.

License

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