nitro-image 1.1.1

Resize, convert, and optimize images with a chainable API. Generate responsive sizes in one call.

Nitro Image

Fast, friendly image processing for Python web apps and SaaS. Nitro Image wraps Pillow with a chainable, lazy-evaluated pipeline so you can resize, convert, optimize, and generate responsive image sets with one fluent call.

Installation

pip install nitro-image

Optional extras:

pip install nitro-image[url]   # Load images from URLs (httpx)
pip install nitro-image[avif]  # AVIF format support
pip install nitro-image[blur]  # BlurHash generation
pip install nitro-image[all]   # Everything above

Quickstart

from nitro_img import Image

Image("photo.jpg").resize(800).webp(quality=80).save("photo.webp")

Features

• Chainable API - Fluent, readable pipelines instead of verbose PIL boilerplate
• Lazy Execution - Operations queue up and only run on output (.save(), .to_bytes(), etc.)
• Format Conversion - JPEG, PNG, WebP, GIF, and optional AVIF
• Smart Resizing - resize, thumbnail, cover, contain with upscale control
• Responsive Sets - Generate multiple widths for srcset in one call
• Placeholders - LQIP data URIs, dominant colors, palettes, SVG, and BlurHash
• Overlays - Watermarks and text with position, opacity, and scale control
• Batch Processing - Glob-based batch with optional thread parallelism
• Framework Integrations - One-line response helpers for Django, Flask, and FastAPI
• Presets - Opinionated one-call helpers for thumbnails, avatars, OG images, and banners
• Optimization - Target-size encoding with automatic quality tuning

AI Assistant Integration

Add Nitro Image knowledge to your AI coding assistant:

npx skills add nitrosh/nitro-image

This enables AI assistants like Claude Code to understand Nitro Image and generate correct nitro_img code.

Why Nitro Image?

With Pillow alone:

from PIL import Image

img = Image.open("photo.jpg")
img = img.convert("RGB")
width, height = img.size
new_height = int(height * (800 / width))
img = img.resize((800, new_height), Image.LANCZOS)
img.save("photo.webp", "WEBP", quality=80)

With Nitro Image:

from nitro_img import Image

Image("photo.jpg").resize(800).webp(quality=80).save("photo.webp")

Operations queue up and only run when you call an output method like .save() or .to_bytes(), so a long chain still touches the pixels once.

Resize and crop

Image("photo.jpg").resize(800).save("resized.jpg")
Image("photo.jpg").thumbnail(200, 200).save("thumb.jpg")
Image("photo.jpg").cover(400, 400).save("square.jpg")
Image("photo.jpg").contain(400, 400).save("contained.jpg")
Image("photo.jpg").crop(500, 400, anchor="center").save("cropped.jpg")

Format conversion

Image("photo.jpg").webp(quality=80).save("photo.webp")
Image("photo.jpg").png().save("photo.png")
Image("photo.jpg").jpeg(quality=90).save("photo.jpg")
Image("photo.jpg").auto_format().save("photo.webp")  # picks best format

Adjustments and effects

Image("photo.jpg").brightness(1.2).contrast(1.1).save("enhanced.jpg")
Image("photo.jpg").sharpen(1.5).save("sharp.jpg")
Image("photo.jpg").blur(2.0).save("blurred.jpg")
Image("photo.jpg").grayscale().save("gray.jpg")
Image("photo.jpg").sepia().save("sepia.jpg")
Image("photo.jpg").rounded_corners(20).png().save("rounded.png")

Watermarks and text overlays

Image("photo.jpg").watermark("logo.png", position="bottom-right", opacity=0.5).save("watermarked.jpg")
Image("photo.jpg").text_overlay("Sample", font_size=48).save("labeled.jpg")

Responsive images

widths = Image("photo.jpg").responsive([400, 800, 1200, 1600])
# Returns {400: bytes, 800: bytes, 1200: bytes, 1600: bytes}

Image("photo.jpg").webp().save_responsive("output/", [400, 800, 1200], name="hero")
# Saves output/hero_400.webp, output/hero_800.webp, output/hero_1200.webp

Placeholders

Image("photo.jpg").lqip()            # Low-quality base64 data URI
Image("photo.jpg").dominant_color()  # "#3a6b8c"
Image("photo.jpg").color_palette(5)  # ["#3a6b8c", "#d4a574", ...]
Image("photo.jpg").svg_placeholder() # SVG with dominant color
Image("photo.jpg").blurhash()        # "LKO2:N%2Tw=w]~RBVZRi..."

Optimization

Image("photo.jpg").optimize(target_kb=200)
# Returns the encoded bytes, auto-tuning quality to hit the target size

Presets

Presets are opinionated one-call helpers. They take a source (path, bytes, or file-like) and return encoded bytes.

from nitro_img import presets, Image

presets.thumbnail("photo.jpg")                 # 200x200 WebP
presets.avatar("photo.jpg", size=128)          # 128px circle-cropped PNG
presets.og_image("photo.jpg")                  # 1200x630 JPEG social card
presets.banner("photo.jpg")                    # 1920x400 JPEG banner
presets.avatar_placeholder("SN")               # Initials avatar

# Presets are also available via Image.preset for convenience:
Image.preset.thumbnail("photo.jpg")

Batch processing

from nitro_img import BatchImage

BatchImage("photos/*.jpg").resize(800).webp().save("output/{name}.webp")
BatchImage("photos/*.jpg").resize(800).jpeg().save("output/{name}.jpg", parallel=True)

{name} in the save pattern is replaced with each source file's stem.

Web framework responses

# Django
return Image("photo.jpg").resize(400).webp().to_django_response()

# Flask
return Image("photo.jpg").resize(400).webp().to_flask_response()

# FastAPI / Starlette
return Image("photo.jpg").resize(400).webp().to_fastapi_response()

Loading from anywhere

Image("photo.jpg")                          # File path
Image.from_bytes(raw_bytes)                 # Bytes
Image.from_base64(b64_string)               # Base64 string
Image.from_url("https://example.com/img")   # URL (requires httpx)
Image.from_file(file_object)                # File-like object

Output options

img = Image("photo.jpg").resize(400).webp()

img.save("output.webp")       # Save to file
img.to_bytes()                # Raw bytes
img.to_base64()               # Base64 encoded string
img.to_data_uri()             # data:image/webp;base64,...
img.to_response()             # {"body": bytes, "content_type": str, "content_length": int}

Chain everything

All operations are chainable and lazily evaluated:

(
    Image("photo.jpg")
    .resize(800)
    .brightness(1.1)
    .contrast(1.05)
    .sharpen(1.2)
    .sepia()
    .rounded_corners(10)
    .png()
    .save("final.png")
)

Configuration

from nitro_img import config

config.update(
    default_jpeg_quality=85,
    default_webp_quality=80,
    default_png_compression=6,
    allow_upscale=False,
    auto_orient=True,
    strip_metadata=False,
    max_output_dimensions=10_000,
)

Requirements

• Python 3.10+
• Pillow 10.0+

Ecosystem

• nitro-ui - Build HTML with Python, not strings
• nitro-cli - Python-powered static site generator
• nitro-datastore - Schema-free JSON data store with dot notation access
• nitro-dispatch - Framework-agnostic plugin system
• nitro-validate - Dependency-free data validation

License

This project is licensed under the BSD 3-Clause License. See the LICENSE file for details.