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Package to create JRAGBEER Common Functions

Project description

jragbeer_common

License Python 3.10 pre-commit

Overview

A Python utility library containing common functions and tools used across various projects. This library provides reusable components for:

  • Data processing and engineering
  • Azure blob storage operations
  • Dask distributed computing
  • Ubuntu system operations

Features

  • Data Engineering Utilities

    • DataFrame manipulation and cleaning
    • SQL database operations
    • Email notifications
    • Date/time processing
    • Logging configuration
  • Azure Integration

    • Blob storage upload/download
    • Parquet file handling
    • Container management
    • Batch operations
  • Dask Distributed Computing

    • Cluster deployment and management
    • Worker allocation
    • Task scheduling
    • Remote execution
  • Ubuntu System Operations

    • Remote command execution
    • Process management
    • System monitoring
    • File operations

Installation

  1. Install uv (recommended):
pip install uv
  1. Create and activate a virtual environment:
uv venv
source .venv/bin/activate  # Linux/Mac
# or
.venv\Scripts\activate  # Windows
  1. Install the package:
uv pip install jragbeer-common

Development Setup

  1. Clone the repository:
git clone https://github.com/jragbeer/jragbeer_common.git
cd jragbeer_common
  1. Create a virtual environment and install dependencies:
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
  1. Install development dependencies:
uv pip install -e ".[dev]"
  1. Install pre-commit hooks:
pre-commit install

Usage

from jragbeer_common import (
    jragbeer_common_data_eng,
    jragbeer_common_azure,
    jragbeer_common_dask,
    jragbeer_common_ubuntu
)

# Data Engineering
jragbeer_common_data_eng.parse_date_features(df)

# Azure Operations
jragbeer_common_azure.adls_upload_file("path/to/file", "blob_name")

# Dask Operations
jragbeer_common_dask.deploy_dask_home_setup()

# Ubuntu Operations
jragbeer_common_ubuntu.execute_cmd_ubuntu_sudo("command")

Environment Variables

The following environment variables are required:

# Azure Storage
adls_connection_string="your_connection_string"
adls_container_name="your_container"

# Database
local_db_username="username"
local_db_password="password"
local_db_address="address"
local_db_port="port"

# Cluster Configuration
cluster_server_1_address="address"
cluster_server_1_username="username"
cluster_server_1_password="password"

Building and Distribution

  1. Build the package:
uv build
  1. Install locally for testing:
uv pip install dist/jragbeer_common-0.2.0-py3-none-any.whl

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Run tests and linting:
uv sync --extra dev
pre-commit run --all-files
uv run pytest

CI runs the same full suite on each push and pull request (see .github/workflows/test.yml), including tests marked integration (Docker Postgres, etc.). You need a working Docker daemon for a green run locally and in GitHub Actions (the runner provides Docker). Markers (unit, integration, contract) still classify tests in pyproject.toml; nothing is excluded by default.

Integration tests (Docker Postgres)

Database tests that open PostgreSQL live in test/db/test_jragbeer_common_db.py and are marked @pytest.mark.integration. They use the session-scoped container from test/fixtures/postgresql.py plus the docker Python client and psycopg2-binary. They run as part of the default uv run pytest (and in CI).

Optional environment variables (defaults in parentheses):

  • TEST_POSTGRESQL_PORT — host port mapped to the container (54329)
  • TEST_POSTGRESQL_USER, TEST_POSTGRESQL_PASSWORD, TEST_POSTGRESQL_DATABASE — bootstrap credentials (devuser / devpassword / postgres)
  • TEST_POSTGRESQL_VERSION — image tag after postgres: (17.4)

Readiness is checked with TCP connections via psycopg2 from the host (same as SQLAlchemy), not docker exec psql, so you do not need the docker CLI or host postgresql-client for the wait loop.

Future work: tests that hit real services should live under the appropriate test/<subpackage>/ package, be marked @pytest.mark.integration, and document required environment variables in the test module docstring.

License

Copyright 2026 Julien Ragbeer

Licensed under the Apache License, Version 2.0

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