[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
⚡ Executive Summary & Quick Facts
Authoritative SourceDataFlow is DataFlow is an open-source project written in Python: [SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines..
| Repository | OpenDCAI/DataFlow ↗ |
|---|---|
| Primary Category | data |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 8.2K stars · ⑂ 1.2K forks · #1,617 globally |
| Maintenance | ● Active (Last commit: Oct 19, 2026) · 18 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
Star History
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+206
STARS · LAST 30 DAYS
7
PER DAY
#260
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +49 | +206 | +630 |
| Per day | 7 | 7 | 7 |
| Forks gained | +6 | +24 | +60 |
DataFlow gained 206 stars in the last 30 days, about 7 a day, and now has 8.2K. It is about 2 years old and has averaged roughly 4.1K stars a year. It ranks #260 among Python repositories and #1,617 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#5397
BEST RANK
Oct 19, 2026
FIRST APPEARANCE
Active
STATUS TODAY
DataFlow has maintained a continuous presence across global trending indexes, peaking at #5397. Below is the 30-day activity profile:
💡 Overview
DataFlow is an open-source project written in Python: [SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
Engineered for speed, consistency, and developer ease, it solves common hurdles in data, data-agent, data-cleaning. 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 DataFlow⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
DataFlow 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 DataFlow.
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 DataFlow using your package manager: `pip install DataFlow`
Initialize your project workspace or configuration file for DataFlow.
Import DataFlow into your codebase or invoke it directly from your terminal.
Execute your test suite or run `DataFlow --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
OpenDCAI/DataFlow is currently ranked #1,617 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #1,612 | deeplethe/utopia | Rust | ★ 8.3K | Compare ↗ |
| #1,613 | isaac-sim/IsaacLab | Python | ★ 8.3K | Compare ↗ |
| #1,614 | apache/tomcat | Java | ★ 8.3K | Compare ↗ |
| #1,615 | chef/chef | Ruby | ★ 8.3K | Compare ↗ |
| #1,616 | shaka-project/shaka-player | JavaScript | ★ 8.2K | Compare ↗ |
| #1,617 | OpenDCAI/DataFlow This Project | Python | ★ 8.2K | |
| #1,618 | rikkahub/rikkahub | Kotlin | ★ 8.2K | Compare ↗ |
| #1,619 | heartcombo/simple_form | Ruby | ★ 8.2K | Compare ↗ |
| #1,620 | SWE-agent/mini-swe-agent | Python | ★ 8.2K | Compare ↗ |
| #1,621 | ntop/ntopng | Lua | ★ 8.2K | Compare ↗ |
| #1,622 | k8sgpt-ai/k8sgpt | Go | ★ 8.2K | Compare ↗ |
Frequently Asked Questions
What does DataFlow do? +
[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
What language is DataFlow written in? +
The primary language is Python. Topics include: data, data-agent, data-cleaning, data-pipelines, data-processing.
Is DataFlow actively maintained? +
Yes, the last recorded push was on Oct 19, 2026 with 18 open issues being tracked.
How many stars does DataFlow have? +
DataFlow has 8,237 stars and 1,200 forks on GitHub.
How does DataFlow rank among GitHub repositories? +
With 8,237 stars, OpenDCAI/DataFlow is ranked #1,617 globally across all repositories tracked on GitHubRepo and #260 among Python projects.
What license is DataFlow distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
