postcanvas 0.1.1

Generate pixel-perfect social media images from Python Pydantic models

postcanvas 🎨

Generate pixel-perfect social-media images from Python — just describe what you want.

Install

pip install postcanvas

Quick start

from postcanvas import generate
from postcanvas.presets import instagram_post
from postcanvas.models import BackgroundConfig, TextConfig, ShadowConfig

post = instagram_post(
    background=BackgroundConfig(color="#1a1a2e"),
    texts=[
        TextConfig(
            content="Hello World!",
            y="50%",
            font_size=96,
            color="#e94560",
            shadow=ShadowConfig(blur_radius=12),
        )
    ],
    output_dir="./output",
)

generate(post)   # → ./output/post.png

Cloud Storage & Return Raw Images

Generate images without saving to disk for direct cloud uploads:

from postcanvas import generate, image_to_bytes, GenerateResult
from postcanvas.models import OutputFormat

# Get raw PIL Images without saving to disk
images = generate(post, save=False, return_images=True)

# Convert to bytes for cloud storage
for img in images:
    data = image_to_bytes(img, format=OutputFormat.PNG)
    # s3_client.put_object(Bucket='bucket', Key='image.png', Body=data)

# Or save to custom locations
from postcanvas import save_image_to_path
save_image_to_path(images[0], "./custom/path/image.png")

# Get both: save locally AND return images
result = generate(post, save=True, return_images=True)  # Returns GenerateResult
print(result.paths)    # List of saved file paths
print(result.images)   # List of PIL Image objects

Generate Parameters & Return Types

generate(
    post,
    save=True,              # Save to disk
    return_images=False     # Return PIL Image objects
)

Return types:

• save=True, return_images=False (default) → List[str] (file paths only)
• save=False, return_images=True → List[Image.Image] (PIL Images only)
• save=True, return_images=True → GenerateResult (consistent dataclass with both)

Error handling:

• save=False, return_images=False → raises ValueError (must specify at least one output type)

Platforms & formats

Helper	Size
instagram_post()	1080 × 1080
instagram_portrait()	1080 × 1350
instagram_story()	1080 × 1920
x_post()	1600 × 900
reddit_post()	1920 × 1080
blog_og()	1200 × 628
linkedin_post()	1080 × 1080
youtube_thumbnail()	1280 × 720
facebook_post()	1080 × 1080
tiktok_story()	1080 × 1920

Use preset(Platform.CUSTOM, PostFormat.CUSTOM, width=800, height=600) for custom sizes.

Carousel / multi-image

from postcanvas.models import CanvasConfig, BackgroundConfig

post = instagram_post(
    canvases=[
        CanvasConfig(background=BackgroundConfig(color="#e94560"),
                     texts=[TextConfig(content="Slide 1", ...)]),
        CanvasConfig(background=BackgroundConfig(color="#0f3460"),
                     texts=[TextConfig(content="Slide 2", ...)]),
    ]
)

Key model reference

PostConfig (root)

Field	Type	Description
platform	Platform	Target platform
width / height	int	Canvas size in px
background	BackgroundConfig	Global background
padding	PaddingConfig	Safe-area insets
texts	List[TextConfig]	Global text elements
images	List[ImageElementConfig]	Global image elements
shapes	List[ShapeConfig]	Global shapes
canvases	List[CanvasConfig]	Slides (carousel)
watermark	WatermarkConfig	Applied to every slide
output_dir	str	Where to save files
output_format	OutputFormat	png / jpeg / webp

Positioning

Every x, y, width, height accepts:

• Absolute pixels: 540, 200
• Relative string: "50%", "80%"

Anchors

anchor can be: topleft, topcenter, topright, left, center, right, bottomleft, bottomcenter, bottomright

z_index

Elements are composited in ascending z_index order across all types (shapes, images, texts). Default values: shapes=1, images=5, texts=10.

Text inside images and shapes

Both ImageElementConfig and ShapeConfig now support a texts list:

from postcanvas.models import ImageElementConfig, ShapeConfig, ShapeType, TextConfig

ShapeConfig(
    type=ShapeType.ROUNDED_RECTANGLE,
    x="50%", y="35%", width="70%", height="30%", anchor="center",
    fill_color="#1f3b4d",
    texts=[
        TextConfig(content="Inside Shape", x="50%", y="50%", anchor="center")
    ],
)

ImageElementConfig(
    src="assets/photo.jpg",
    x="50%", y="70%", width="60%", height="35%", anchor="center",
    texts=[
        TextConfig(content="Inside Image", x="50%", y="88%", anchor="bottomcenter")
    ],
)

Nested text coordinates are resolved relative to the element's own box, not the full canvas.

Font inheritance (Post > Canvas > Text override)

You can define default text font at post level, override it per canvas, and still override per text:

from postcanvas.presets import instagram_post
from postcanvas.models import CanvasConfig, TextConfig

post = instagram_post(
    text_font_path="Roboto/static/Roboto-Regular.ttf",   # default for whole post
    texts=[
        TextConfig(content="Uses post default", x="50%", y="15%"),
        TextConfig(content="Custom text font", x="50%", y="25%", font_path="Roboto/static/Roboto-Bold.ttf"),
    ],
    canvases=[
        CanvasConfig(
            text_font_path="Roboto/static/Roboto-Italic.ttf",  # overrides post default on this slide
            texts=[
                TextConfig(content="Uses canvas override", x="50%", y="50%"),
                TextConfig(content="Text-level still wins", x="50%", y="60%", font_path="Roboto/static/Roboto-Medium.ttf"),
            ],
        )
    ],
)

Precedence: TextConfig > CanvasConfig > PostConfig > internal Arial fallback.