DataKitchen/data-observability-installer
Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.
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+10
STARS · LAST 30 DAYS
1
PER DAY
#946
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
data-observability-installer gained 10 stars in the last 30 days, about 1 a day, and now has 141. It is about 2 years old and has averaged roughly 71 stars a year. It ranks #946 among Python repositories and #7,935 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#7317
BEST RANK
Sep 30, 2026
FIRST APPEARANCE
Active
STATUS TODAY
data-observability-installer has maintained a continuous presence across global trending indexes, peaking at #7317. Below is the 30-day activity profile:
💡 Overview
data-observability-installer is an open-source project written in Python: Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.
Engineered for speed, consistency, and developer ease, it solves common hurdles in data, data-engineering, data-observability. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install data-observability-installer⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
data-observability-installer 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 data-observability-installer 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 Apache-2.0 license.
🚀 Getting Started
Install data-observability-installer using your package manager: `pip install data-observability-installer`
Initialize your project workspace or configuration file for data-observability-installer.
Import data-observability-installer into your codebase or invoke it directly from your terminal.
Execute your test suite or run `data-observability-installer --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 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
DataKitchen/data-observability-installer is currently ranked #7,935 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #7,907 | MakrSas/Inferno-iOS | Swift | ★ 142 | Compare ↗ |
| #7,907 | Wunderlandmedia/HotkeyClash | Swift | ★ 142 | Compare ↗ |
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| #7,907 | NotProtonNot/NotProton | Swift | ★ 142 | Compare ↗ |
| #7,907 | NVlabs/Skill2Env | Python | ★ 142 | Compare ↗ |
| #7,935 | DataKitchen/data-observability-installer This Project | Python | ★ 141 | |
| #7,935 | datafusion-contrib/datafusion-distributed | Rust | ★ 141 | Compare ↗ |
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| #7,935 | shaikhspeare/wanderlog-mcp | TypeScript | ★ 141 | Compare ↗ |
| #7,935 | noelrappin/rails-iui | Ruby | ★ 141 | Compare ↗ |
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Frequently Asked Questions
What does data-observability-installer do? +
Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.
What language is data-observability-installer written in? +
The primary language is Python. Topics include: data, data-engineering, data-observability, data-profiling, data-quality.
Is data-observability-installer actively maintained? +
Yes, the last recorded push was on Sep 30, 2026 with 6 open issues being tracked.
How many stars does data-observability-installer have? +
data-observability-installer has 141 stars and 12 forks on GitHub.
How does data-observability-installer rank among GitHub repositories? +
With 141 stars, DataKitchen/data-observability-installer is ranked #7,935 globally across all repositories tracked on GitHubRepo and #946 among Python projects.
What license is data-observability-installer distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
