lokkiflow 0.3.14

Python library for defining, building, and deploying data pipelines to AWS Step Functions

lokki

A Python library for defining, building, and deploying data pipelines to AWS Step Functions.

Features

• Simple Python decorators - Define pipelines using @step and @flow decorators
• Local execution - Test your flows locally before deploying
• AWS Step Functions - Deploy to AWS Step Functions with Distributed Map for parallel processing
• Lambda packaging - Auto-generates Docker images or ZIP archives for each step
• CloudFormation - Generates complete CloudFormation templates for deployment
• Retry configuration - Configure automatic retries for failed steps
• Flow parameters - Pass parameters to flows at runtime

Installation

pip install lokkiflow

Or install by uv (recommended):

uv add lokkiflow

Quick Start

Define a flow with steps:

from lokki import flow, step

@step
def get_birds() -> list[str]:
    return ["goose", "duck", "seagull"]

@step
def flap_bird(bird: str) -> str:
    return f"flappy {bird}"

@step
def join_birds(birds: list[str]) -> str:
    return ", ".join(birds)

@flow
def birds_flow():
    return get_birds().map(flap_bird).agg(join_birds)

if __name__ == "__main__":
    from lokki import main
    main(birds_flow)

Run locally:

python birds_flow.py run
# Output: flappy goose, flappy duck, flappy seagull

Build for deployment:

python birds_flow.py build

This creates:

• lokki-build/lambdas/ - One directory per step with Dockerfile or ZIP
• lokki-build/statemachine.json - AWS Step Functions state machine
• lokki-build/template.yaml - CloudFormation template

Configuration

Create a lokki.toml in your project:

# lokki.toml
build_dir = "lokki-build"

[aws]
artifact_bucket = "my-lokki-artifacts"
image_repository = "local"  # or ECR prefix like "123456789.dkr.ecr.us-east-1.amazonaws.com/myproject"
endpoint = ""  # for LocalStack: "http://localhost:4566"

[lambda]
package_type = "image"  # or "zip" for simpler deployments
timeout = 900
memory = 512
image_tag = "latest"

[lambda.env]
LOG_LEVEL = "INFO"

[logging]
level = "INFO"
format = "human"  # or "json"

Configuration Precedence

Environment variables override TOML config (highest to lowest):

Environment Variable	Config Field
LOKKI_ARTIFACT_BUCKET	aws.artifact_bucket
LOKKI_IMAGE_REPOSITORY	aws.image_repository
LOKKI_AWS_ENDPOINT	aws.endpoint
LOKKI_BUILD_DIR	build_dir
LOKKI_LOG_LEVEL	logging.level

Flow Syntax

Basic Example

from lokki import step, flow, main

@step
def get_data():
    return [1, 2, 3]

@step
def process_item(item, mult):
    return item * mult

@step
def process_item_2(item):
    return item * item

@step  
def sum_items(items):
    return sum(items)

@flow
def my_flow(mult=2):
    return get_data().map(process_item, mult=mult).next(process_item_2).agg(sum_items)

if __name__ == "__main__":
    main(my_flow)

The example gets item list, maps them through two processing functions and aggregates the result.

Chaining Methods

• .map(step) - Run step in parallel for each item in the list (fan-out)
• .agg(step) - Aggregate results from map into a single value (fan-in)
• .next(step) - Run step sequentially after the previous step

Chain multiple maps: step1().map(step2).next(step3).agg(agg_step)

Flow Parameters

Pass parameters to flows at runtime:

@step
def fetch_data(limit: int, offset: int = 0):
    return list(range(limit))[offset:]

@step
def process(item, mult):
    return item * mult

@flow
def paginated_flow(limit: int = 100, offset: int = 0, mult: int = 2):
    return fetch_data(limit=limit, offset=offset).map(process, mult=mult)

if __name__ == "__main__":
    main(paginated_flow)

Run with parameters:

python flow.py run --limit 50 --offset 10

Retry Configuration

Configure automatic retries for failed steps:

from lokki import flow, step
from lokki.decorators import RetryConfig

@step
def unreliable_step(data):
    import random
    if random.random() < 0.5:
        raise ValueError("Random failure")
    return data

@flow
def flow_with_retry():
    return unreliable_step(retry=RetryConfig(retries=3, delay=1.0, backoff=2.0))

Retry options:

• retries - Number of retry attempts (default: 0)
• delay - Initial delay between retries in seconds (default: 1.0)
• backoff - Backoff multiplier for delay (default: 2.0)

CLI Commands

python my_flow.py run              # Run locally with optional params
python my_flow.py build            # Build deployment artifacts
python my_flow.py deploy           # Build and deploy to AWS
python my_flow.py show             # Show execution status
python my_flow.py logs             # Fetch CloudWatch logs
python my_flow.py destroy          # Destroy the CloudFormation stack
python my_flow.py --help           # Show help

Run Command

python flow.py run --param1 value1 --param2 value2

Deploy Command

python flow.py deploy --stack-name my-stack --region us-east-1

Show Command

python flow.py show                    # Show last 10 executions
python flow.py show --n 5              # Show last 5 executions
python flow.py show --run <run_id>      # Show specific execution

Logs Command

python flow.py logs                     # Fetch logs from last hour
python flow.py logs --start 2024-01-15T10:00:00Z
python flow.py logs --tail              # Tail logs in real-time
python flow.py logs --run <run_id>      # Filter by run ID

Deployment

Option 1: Docker Images (Default)

1. Build your flow:

   python my_flow.py build
   

2. Push Lambda images to ECR (from each lokki-build/lambdas/<step>/ directory):

   docker build -t <ecr-repo>/<step>:<tag> .
   docker push <ecr-repo>/<step>:<tag>
   

3. Deploy CloudFormation:

   aws cloudformation deploy \
     --template-file lokki-build/template.yaml \
     --stack-name my-flow \
     --parameter-overrides \
       FlowName=my-flow \
       S3Bucket=my-bucket \
       ImageRepository=123456789.dkr.ecr.us-east-1.amazonaws.com/myproject
   

Option 2: ZIP Archives (Simpler)

For simpler deployments without Docker:

[lambda]
package_type = "zip"

python my_flow.py deploy

The Lambda code will be uploaded directly as ZIP archives - no ECR push needed.

Local Development with LocalStack

Test your flows locally before deploying to AWS:

1. Start LocalStack:

   cd dev
   docker-compose up -d
   

2. Configure for LocalStack:

   [aws]
   artifact_bucket = "lokki"
   endpoint = "http://localhost:4566"
   image_repository = "local"
   
   [lambda]
   package_type = "zip"
   

3. Build and deploy:

   python flow.py build
   python flow.py deploy --confirm
   

See dev/README.md for more detailed LocalStack testing instructions.

Architecture

• @step - Decorator that marks a function as a pipeline step
• @flow - Decorator that wraps a function returning a FlowGraph
• FlowGraph - Resolved execution graph with TaskEntry, MapOpenEntry, MapCloseEntry
• LocalRunner - Executes flows locally using temporary files
• Builder - Generates Lambda packages, state machine, and CloudFormation

Development

# Install dev dependencies
uv sync --extra dev

# Run tests
uv run pytest

# Type check
uv run mypy lokki/

# Lint
uv run ruff check lokki/

License

MIT