intro-to-cc-image-core 0.1.0

Infra-agnostic image processing core for Intro to Cloud Computing exercises

image-core (Python)

Infra-agnostic image processing core for exercise solutions.

Prerequisites

• Python 3.11+
• pip (or uv/pip-tools)

Features

• Validate image payloads
• Resize by longest edge
• Convert output format
• Return required metadata
• Bytes and stream entry points

Install

Published package:

pip install intro-to-cc-image-core

Local package test (without publishing):

pip install .

API Surface

This package intentionally exposes a small student-facing API:

Function	Input style	Typical use case
process_image_bytes	bytes	Use when you already have complete bytes in memory
process_image_stream	BinaryIO stream	Use when image data comes from stream-based IO

Persistence and storage integration stay in your app code.

Bytes Usage

from image_core.models import ProcessingConfig
from image_core.processing import process_image_bytes

result = process_image_bytes(
    source_bytes=input_bytes,
    config=ProcessingConfig(
        max_long_edge_px=1280,
        output_format="JPEG",
        output_quality=85,
    ),
    image_id="img-1",
)

print(result.metadata, result.content_type)

Build and Publish Checklist

python -m pip install --upgrade build twine
python -m build
python -m twine check dist/*
python -m twine upload dist/*

Stream Usage

from image_core.models import ProcessingConfig
from image_core.processing import process_image_stream

with open("./input.png", "rb") as source_stream:
    result = process_image_stream(
        source_stream=source_stream,
        config=ProcessingConfig(
            max_long_edge_px=1280,
            output_format="JPEG",
            output_quality=85,
        ),
        image_id="img-2",
        asset_path="processed/img-2.jpg",
    )

print(result.metadata, result.content_type)