dataquery 0.1.1

A package for simplified database operations with PostgreSQL and Pandas.

DataQuery

About

DataQuery is a Python package designed to simplify interactions with PostgreSQL databases. It leverages SQLAlchemy and pandas to provide an intuitive interface for retrieving, updating, inserting, and deleting data within a database. This package is ideal for data scientists and developers looking for a streamlined way to handle database operations.

Features

• Easy retrieval of data into pandas DataFrames.
• Simplified update, insert, and delete operations.
• Customizable query capabilities with filtering criteria.
• Designed with best practices in database connections and session management.

Installation

Ensure you have Python 3.11 or higher installed. It's recommended to use a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

Install DataQuery using pip:

pip install dataquery

Or, if you're installing directly from the source:

git clone https://github.com/yourusername/querycraft.git
cd dataquery
pip install .

Usage

Initialization

First, initialize the DataQuery object with your database credentials:

from dataquery import DataQuery

qc = DataQuery(host='localhost', port='5432', username='your_username', password='your_password',
                database='your_database')

Retrieving Data

To retrieve data from a table:

df = qc.retrieve_data('table_name', {'column_name': 'value'})

Updating Data

To update data in a table:

from pandas import DataFrame

data = DataFrame({...})  # Your data to update
qc.update_data('table_name', ['column_to_match'], data)

Replace 'table_name', ['column_to_match'], and data with your specific table name, columns to match, and DataFrame containing the new data.

Contribution and Development Guidelines

Contributions to DataQuery are welcome! If you're interested in contributing, please follow these guidelines:

1. Create a New Branch: Create a new branch for your feature or fix.
2. Commit Your Changes: Make your changes and commit them to your branch.
3. Push to Your Brach: Push your branch on GitHub.
4. Submit a Pull Request: Submit a pull request from your branch to the development branch.

Please ensure your code adheres to PEP 8 standards and include tests for new features or bug fixes.

License

DataQuery is licensed under the BSD 3-Clause License. See the LICENSE file for more details.