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TokenPDF is a lightweight Python library for creating printable PDF files containing RPG tokens and (possibly large) maps. It simplifies the process of generating monster-tokens, and fragmenting maps into printable pages, while minimizing the number of papers required. The library is fully configureable.
See the Changelog for details on recent changes.
To install, use one of the following commands:
pip install tokenpdf
pip install tokenpdf[full]
pip install tokenpdf[full-gpu]
See below for more details on the installation options.
Contains the core functionality of the library, including token generation and map fragmentation, and rendering to .svg files, and conversion to pdf using rsvg-convert executable.
pip install tokenpdf
For other PDF backends, add the pdf-rl
, pdf-qt
, and/or pdf-pr
extras:
pdf-rl
: PDF output using reportlab (default)
pip install tokenpdf[pdf-rl]
pdf-qt
: PDF output using PySide6 (Qt)
pip install tokenpdf[pdf-qt]
pdf-pr
: PDF output using playwright
pip install tokenpdf[pdf-pr]
playwright install
is required to be run before using the playwright backend.The rembg
package is used for background removal. To install it, use either the cpu
or gpu
extras:
pip install tokenpdf[cpu]
The gpu
extra will install onnxruntime-gpu
. See that package for details about system requirements.
To install all extras, use either the full
or the full-gpu
extras:
pip install tokenpdf[full]
For CPU-based and GPU-based installations, respectively.
git clone https://github.com/Dormat2/tokenpdf.git
cd tokenpdf
pip install -r requirements.txt
The library provides both a command-line interface and a Python API. The CLI is the easiest way to get started.
python -m tokenpdf <config_files> [-o OUTPUT] [-v] [-s]
config_files
: One or more configuration files in TOML, JSON, YAML, or INI format. See examples below, or Configuration Reference for more details. Can only be omitted if -e
flag is used.-e
: Use the example configuration file (tokenpdf/data/example.toml
).-o OUTPUT
: The output PDF file (default: output.pdf
). If ommited, the output name is derived from the first configuration file.-v
: Enable verbose output.-s
: Silence most output.Example usage:
python -m tokenpdf example.toml -o my_tokens.pdf -v
Configurations define your monsters, their tokens, the maps, and the pdf layout and generation process.
output = "single_token.pdf"
[monsters.circle]
name = "Circle Token"
size = "Medium"
image_url = "https://picsum.photos/200"
tokens = [
{ type = "circle", size = "medium", count = 1 }
]
{
"output": "single_token.pdf",
"monsters": {
"circle_token": {
"name": "Circle Token",
"size": "Medium",
"image_url": "https://picsum.photos/200",
"tokens": [
{ "type": "circle", "size": "medium", "count": 1 }
]
}
}
}
Add multiple tokens for the same monster:
TOML Example
[monsters.circle_token]
name = "Circle Token"
size = "Medium"
image_url = "https://picsum.photos/200"
tokens = [
{ type = "circle", size = "medium", count = 5 }
]
JSON Example
{
"monsters": {
"circle_token": {
"name": "Circle Token",
"size": "Medium",
"image_url": "https://picsum.photos/200",
"tokens": [
{ "type": "circle", "size": "medium", "count": 5 }
]
}
}
}
Add a standing token for the same monster:
TOML Example
[monsters.circle_token]
name = "Circle Token"
size = "Medium"
image_url = "https://picsum.photos/200"
tokens = [
{ type = "circle", size = "small", count = 5 },
{ type = "standing", size = "medium", count = 5 }
]
Note: The size
field is used to determine the token's dimensions in relation to the page size and the system (default: D&D5e) grid sizing (can be overriden). The size can be specified in the monster's configuration, and/or overriden in the token's configuration.
Scaling:
TOML Example
[monsters.circle_token]
name = "Circle Token"
size = "Medium"
image_url = "https://picsum.photos/200"
tokens = [
{ type = "circle", size = "medium", count = 5, scale = 1.1, scale_rho = 0.1 }
]
JSON Example
{
"monsters": {
"circle_token": {
"name": "Circle Token",
"size": "Medium",
"image_url": "https://picsum.photos/200",
"tokens": [
{ "type": "circle", "size": "medium", "count": 5, "scale": 1.1, "scale_rho": 0.1 }
]
}
}
}
In this example, the scale
field scales the token's size. The scale is determined by a log-normal distribution around 1.1
, with a standard deviation of 0.1
. This provides a more natural variation in token sizes. Omitting scale_rho
will set the scale to a fixed value (1.1
)
Customize the entire output, page, and layout behavior. Here’s how to configure some global settings.
Specify the name of the PDF file:
TOML
output = "my_custom_tokens.pdf"
JSON
{
"output": "my_custom_tokens.pdf"
}
Define the paper size, orientation, and margins:
TOML
# General configuration
output = "wsc_{ps}.pdf"
verbose = true
system = "D&D 5e"
compress = true
# Paper settings
page_size = ["A2", "A3", "A4"]
orientation = "portrait"
margin = 0.05
optimize_images_for_dpi = 100
optimize_images_for_quality = 80
# Layout settings
rotation = true
JSON
{
"output": "wsc_{ps}.pdf",
"verbose": true,
"system": "D&D 5e",
"compress": true,
"page_size": ["A2", "A3", "A4"],
"orientation": "portrait",
"margin": 0.05,
"optimize_images_for_dpi": 100,
"optimize_images_for_quality": 80,
"rotation": true
}
Enable token rotation for better page utilization:
TOML
rotation = true
JSON
{
"rotation": true
}
For a full reference of all available settings, see the Configuration Reference.
Example configuration:
Generated PDF:
Contributions are welcome! Feel free to submit issues or pull requests via GitHub.
FAQs
Generate printable PDF files for tabletop RPG tokens and maps
We found that tokenpdf demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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