Skip to main content

A tiny database de-multiplexer primarily scoped for Web- / Application Server.

Project description

:elephant: Python PgDatabase-Pool Module

push main PyPI version

1. Primary Scope

The pgdbpool Python module is a tiny PostgreSQL Database Connection De-Multiplexer, primarily designed for Web- / Application Servers.

Key Features:

  • Multi-endpoint support: Load balance across multiple PostgreSQL servers
  • Flexible threading models: Choose between threaded and non-threaded modes
  • Transaction control: Manual commit support for complex transactions
  • High availability: Built-in failover and connection management

2. Current Implementation

+----------------------+                         +---------------------
| WebServer Service.py | -- Handler Con #1 ----> | PostgreSQL
| Request / Thread #1  |                         | Backend #1
+----------------------+                         |
                                                 |
+----------------------+                         |
| WebServer Service.py | -- Handler Con #2 ----> | PostgreSQL
| Request / Thread #2  |                         | Backend #2
+----------------------+                         +---------------------

2.1. Multiple Database Endpoints

The connection pool now supports multiple PostgreSQL database endpoints for load balancing and high availability:

  • ✅ Configure multiple database hosts in the configuration
  • ✅ Connections are automatically distributed across available endpoints
  • ✅ Provides built-in load balancing for read operations
  • ✅ Enhances fault tolerance and scalability

2.2. Concept / Simplicity

If configured in a Web Server's WSGI Python script, the pooling logic is straightforward:

  1. Check if a free connection in the pool exists.
  2. Verify if the connection is usable (SQL ping).
  3. Use the connection and protect it from being accessed until the query/queries are completed.
  4. Release the connection for reuse.
  5. Reconnect to the endpoint if the connection is lost.

3. Thread Safety / Global Interpreter Lock

3.1. Threading Model Configuration

The pool now supports two threading models that can be configured based on your application's architecture:

  • threaded (default): Uses threading.Lock() for thread safety, suitable for traditional multi-threaded web servers
  • non-threaded: Disables locking for single-threaded applications, eliminating GIL overhead

3.2. Threaded Mode

Thread safety is ensured via lock = threading.Lock(), which relies on a kernel mutex syscall().

While this concept works, the GIL (Global Interpreter Lock) in Python thwarts scalability under heavy loads in a threaded Web Server setup.

3.3. Non-Threaded Mode

For applications using a single-threaded, process-per-request model (like the FalconAS Python Application Server), the non-threaded mode provides:

  • No locking overhead - eliminates mutex syscalls
  • Better performance - avoids GIL contention
  • Simpler architecture - designed for 1 Process == 1 Python Interpreter

[!IMPORTANT] Refer to Section 6: Future for more details on threading-less architectures.

4. Dependencies / Installation

Python 3 and the psycopg2 module are required.

# install (debian)
apt-get install python3-psycopg2
pip install pgdbpool

5. Documentation / Examples

See documentation either at ./doc or https://pythondocs.webcodex.de/pgdbpool/v1.0 for detailed explanation / illustrative examples.

5.1. Multiple Database Configuration

config = {
    'db': [
        {
            'host': 'postgres-server-1.example.com',
            'name': 'mydb',
            'user': 'dbuser',
            'pass': 'dbpass'
        },
        {
            'host': 'postgres-server-2.example.com', 
            'name': 'mydb',
            'user': 'dbuser',
            'pass': 'dbpass'
        }
    ],
    'groups': {
        'default': {
            'connection_count': 20,
            'autocommit': True
        }
    }
}

5.2. Threading Model Configuration

# for non-threaded applications (e.g., FalconAS)
config = {
    'type': 'non-threaded',
    'db': { ... },
    'groups': { ... }
}

# for traditional threaded applications (default)
config = {
    'type': 'threaded',  # or omit for default
    'db': { ... },
    'groups': { ... }
}

5.3. Manual Transaction Control

import pgdbpool as dbpool

dbpool.Connection.init(config)

# for autocommit=False connections
with dbpool.Handler('group1') as db:
    db.query('INSERT INTO table1 VALUES (%s)', ('value1',))
    db.query('INSERT INTO table2 VALUES (%s)', ('value2',))
    db.commit()  # Manual commit

6. Future

6.1. FalconAS Compatibility

The DB-pooling functionality is now compatible with the FalconAS Python Application Server (https://github.com/WEBcodeX1/http-1.2).

The implemented model: 1 Process == 1 Python Interpreter (threading-less), effectively solving the GIL issue through the non-threaded configuration mode.

6.2. Load Balancing

The pool now supports multiple (read-load-balanced) PostgreSQL endpoints:

  • Implemented: Multiple database endpoint configuration
  • Implemented: Automatic connection distribution across endpoints
  • Implemented: Built-in load balancing for database connections
  • Implemented: Read / write / endpoint group separation

linting: pylint

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pgdbpool-1.0.tar.gz (19.1 kB view details)

Uploaded Source

File details

Details for the file pgdbpool-1.0.tar.gz.

File metadata

  • Download URL: pgdbpool-1.0.tar.gz
  • Upload date:
  • Size: 19.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.2

File hashes

Hashes for pgdbpool-1.0.tar.gz
Algorithm Hash digest
SHA256 263ac0dbbdce57e248c1e9beb0b82cc44ce7bf50a31ff5b5d273046a5fc9b173
MD5 2edf0e7ff61b3a445c499631bde43f2e
BLAKE2b-256 a088c461ceacb5fd849e98b76bd5f781d302dee0661da84007bdb65c352a5a47

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page