Claude-skill-registry flowerpower

Create and manage data pipelines using the FlowerPower framework with Hamilton DAGs and uv. Use when users request creating flowerpower projects, pipelines, Hamilton dataflows, or ask about flowerpower configuration, execution, or CLI commands.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/flowerpower" ~/.claude/skills/majiayu000-claude-skill-registry-flowerpower && rm -rf "$T"

manifest: skills/data/flowerpower/SKILL.md

source content

FlowerPower Pipeline Skill

Create and manage data processing pipelines using FlowerPower with Hamilton DAGs.

Quick Start

# Install flowerpower
uv pip install flowerpower

# Initialize project
flowerpower init --name my-project

# Create pipeline
flowerpower pipeline new my_pipeline

# Run pipeline
flowerpower pipeline run my_pipeline

Project Initialization

Use

scripts/init_project.py

or CLI:

# CLI
flowerpower init --name <project-name>

# Python
from flowerpower import FlowerPowerProject
project = FlowerPowerProject.init(name='my-project')

Creates structure:

my-project/
├── conf/
│   ├── project.yml
│   └── pipelines/
├── pipelines/
└── hooks/

Creating Pipelines

Use

scripts/create_pipeline.py

or CLI:

flowerpower pipeline new <name>

Creates:

```
pipelines/<name>.py
```
- Hamilton functions
```
conf/pipelines/<name>.yml
```
- Configuration

Pipeline Module Template

from hamilton.function_modifiers import parameterize
from pathlib import Path
from flowerpower.cfg import Config

PARAMS = Config.load(
    Path(__file__).parents[1], pipeline_name="my_pipeline"
).pipeline.h_params

@parameterize(**PARAMS.input_config)
def load_data(source: str) -> dict:
    """Load data from source."""
    return {"source": source}

def process_data(load_data: dict) -> dict:
    """Process loaded data."""
    return {"processed": load_data}

def final_result(process_data: dict) -> str:
    """Return final result."""
    return str(process_data)

Pipeline Config Template

params:
  input_config:
    source: "data.csv"

run:
  final_vars:
    - final_result
  executor:
    type: threadpool
    max_workers: 4
  retry:
    max_retries: 3
    retry_delay: 1.0

Running Pipelines

# Basic run
flowerpower pipeline run my_pipeline

# With inputs
flowerpower pipeline run my_pipeline --inputs '{"key": "value"}'

# With executor
flowerpower pipeline run my_pipeline --executor threadpool --executor-max-workers 8

# With retries
flowerpower pipeline run my_pipeline --max-retries 3 --retry-delay 2.0

Python API:

from flowerpower import FlowerPowerProject

project = FlowerPowerProject.load('.')
result = project.run('my_pipeline')

# With RunConfig
from flowerpower.cfg.pipeline.run import RunConfig
config = RunConfig(inputs={"key": "value"}, final_vars=["output"])
result = project.run('my_pipeline', run_config=config)

CLI Commands

Command	Description
`flowerpower init --name <name>`	Initialize project
`flowerpower pipeline new <name>`	Create pipeline
`flowerpower pipeline run <name>`	Run pipeline
`flowerpower pipeline show-pipelines`	List pipelines
`flowerpower pipeline show-dag <name>`	Visualize DAG
`flowerpower pipeline delete <name>`	Delete pipeline

Executor Types

Type	Use Case	Config
`synchronous`	Default, sequential	-
`threadpool`	I/O-bound tasks	`max_workers: N`
`processpool`	CPU-bound tasks	`max_workers: N`
`ray`	Distributed computing	`num_cpus: N`
`dask`	Distributed computing	`num_cpus: N`

Optional Dependencies

uv pip install flowerpower[io]   # I/O plugins
uv pip install flowerpower[ui]   # Hamilton UI
uv pip install flowerpower[all]  # All extras

Resources

references/overview.md - Key concepts, architecture, project structure
references/configuration.md - Complete YAML configuration patterns
references/hamilton-patterns.md - Hamilton function decorators and patterns

Scripts

scripts/init_project.py - Initialize new flowerpower project
scripts/create_pipeline.py - Create new pipeline with template
scripts/run_pipeline.py - Execute pipeline with options
scripts/list_pipelines.py - List available pipelines