apifunc: Modular Pipeline Framework with Dynamic graphs

• python.apifunc.com

RPC Services

Overview

apifunc is a Python framework for building modular data processing pipelines. It allows you to define pipeline components as functions and dynamically generate gRPC services for them. This enables you to create flexible and scalable data processing workflows that can be easily integrated with other systems via gRPC.

Key Features

• Modular Design: Build pipelines from reusable components.
• Dynamic gRPC Generation: Automatically generate gRPC service definitions and code from Python functions.
• Input Validation: Each component can define its own input validation logic.
• Pipeline Orchestration: Easily define and execute complex pipelines.
• Example Components: Includes example components for JSON to HTML and HTML to PDF conversion.

Installation

1. Clone the repository:

git clone https://github.com/tom-sapletta-com/apifunc.git

2. Install the package:

pip install .

Usage

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

python cli.py run

python src/apifunc/cli.py run -o my_report.pdf

python src/apifunc/apifunc.py

pip install coverage
coverage run -m unittest discover -s tests
coverage report -m
python -m unittest discover -s tests

/home/linuxbrew/.linuxbrew/opt/[email protected]/bin/python -m venv venv
source venv/bin/activate
pip install grpcio grpcio-tools jinja2 weasyprint
python -m unittest tests.test_apifunc

To install the required dependencies for testing:

pip install jinja2 weasyprint grpcio grpcio-tools

This will generate raport.pdf file.

Example

The python/src/apifunc/apifunc.py file includes a complete example that demonstrates:

• Converting JSON data to HTML using Jinja2 templates.
• Converting HTML to PDF using WeasyPrint.
• Creating a pipeline with these two components.

gRPC Service Generation

When you create a DynamicgRPCComponent, the framework automatically:

1. Generates a .proto file defining a gRPC service with a Transform method.
2. Compiles the .proto file into Python code.

The generated files are stored in the generated_protos directory.

Dependencies

The project requires the following Python packages, as listed in python/requirements.txt:

• grpcio
• grpcio-tools
• protobuf
• jinja2
• weasyprint

Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.