brycewang-stanford/StatsPAI
StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.
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+10
STARS · LAST 30 DAYS
1
PER DAY
#1,214
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 |
StatsPAI gained 10 stars in the last 30 days, about 1 a day, and now has 331. It is about 1 year old and has averaged roughly 331 stars a year. It ranks #1,214 among Python repositories and #9,609 across all languages on GitHubRepo.
Trending Record
7
DAYS ON TRENDING
#8394
BEST RANK
Oct 7, 2026
FIRST APPEARANCE
Active
STATUS TODAY
StatsPAI has maintained a continuous presence across global trending indexes, peaking at #8394. Below is the 30-day activity profile:
💡 Overview
StatsPAI is an open-source project written in Python: StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-native, ai-agents, causal-discovery. 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 StatsPAI⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
StatsPAI 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
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with StatsPAI.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install StatsPAI using your package manager: `pip install StatsPAI`
Initialize your project workspace or configuration file for StatsPAI.
Import StatsPAI into your codebase or invoke it directly from your terminal.
Execute your test suite or run `StatsPAI --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
brycewang-stanford/StatsPAI is currently ranked #9,609 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #9,598 | MostroP2P/mostro | Rust | ★ 332 | Compare ↗ |
| #9,598 | josdemmers/Diablo4Companion | C# | ★ 332 | Compare ↗ |
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| #9,598 | rwjdk/agent-framework-samples | C# | ★ 332 | Compare ↗ |
| #9,598 | aqua5230/usage | Python | ★ 332 | Compare ↗ |
| #9,609 | brycewang-stanford/StatsPAI This Project | Python | ★ 331 | |
| #9,609 | jeremyevans/forme | Ruby | ★ 331 | Compare ↗ |
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Frequently Asked Questions
What does StatsPAI do? +
StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.
What language is StatsPAI written in? +
The primary language is Python. Topics include: agent-native, ai-agents, causal-discovery, causal-inference, data-science.
Is StatsPAI actively maintained? +
Yes, the last recorded push was on Oct 7, 2026 with 0 open issues being tracked.
How many stars does StatsPAI have? +
StatsPAI has 331 stars and 70 forks on GitHub.
How does StatsPAI rank among GitHub repositories? +
With 331 stars, brycewang-stanford/StatsPAI is ranked #9,609 globally across all repositories tracked on GitHubRepo and #1,214 among Python projects.
What license is StatsPAI distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
