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mikl/django-google-analytics

A simple django application to using Google Analytics in your project and tying different GA tags to different sites

Python ◇ developer-tools MIT
★2STARS
⑂2FORKS
!0ISSUES
🏆#20,728GLOBAL RANK
🔥20DAYS TRENDING
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+10

STARS · LAST 30 DAYS

1

PER DAY

#2,395

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+7+10+90
Per day111
Forks gained+1+3+10

django-google-analytics gained 10 stars in the last 30 days, about 1 a day, and now has 2. It is about 17 years old and has averaged roughly 0 stars a year. It ranks #2,395 among Python repositories and #20,728 across all languages on GitHubRepo.

Trending Record

django-google-analytics has maintained a continuous presence across global trending indexes, peaking at #100. Below is the 30-day activity profile:

💡 Overview

django-google-analytics is an open-source project written in Python: A simple django application to using Google Analytics in your project and tying different GA tags to different sites.

Engineered for speed, consistency, and developer ease, it solves common hurdles in Python. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Python for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ pip install django-google-analytics

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

django-google-analytics coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed django-google-analytics into Python backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open MIT license.

🚀 Getting Started

1

Install django-google-analytics using your package manager: `pip install django-google-analytics`

2

Initialize your project workspace or configuration file for django-google-analytics.

3

Import django-google-analytics into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `django-google-analytics --help` to verify successful setup.

👍 Strengths

Active community backing with 2 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Python for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Python and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

mikl/django-google-analytics is currently ranked #20,728 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

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#20,728 mikl/django-google-analytics This Project Python ★ 2
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Frequently Asked Questions

What does django-google-analytics do? +

A simple django application to using Google Analytics in your project and tying different GA tags to different sites

What language is django-google-analytics written in? +

The primary language is Python. Topics include: software.

Is django-google-analytics actively maintained? +

Yes, the last recorded push was on Dec 2, 2009 with 0 open issues being tracked.

How many stars does django-google-analytics have? +

django-google-analytics has 2 stars and 2 forks on GitHub.

How does django-google-analytics rank among GitHub repositories? +

With 2 stars, mikl/django-google-analytics is ranked #20,728 globally across all repositories tracked on GitHubRepo and #2,395 among Python projects.

What license is django-google-analytics distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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