bored-charts 0.3.2

Easy, minimal, PDF-able data reports with python and markdown.

bored-charts

Build easy, minimal, PDF-able data reports with markdown and python.

The idea is you do your analysis in Python, as you normally would, and dumping your figures into a nice report written in markdown is now super low-effort: you decorate the function to generate the figure (that you already wrote when doing your analysis) and it becomes available to bored-charts so you can present your findings clearly.

Minimal example

Install bored-charts and uvicorn:

pip install bored-charts uvicorn

Create your app

# main.py
from pathlib import Path

import plotly.express as px
import plotly.graph_objects as go
from boredcharts import BCRouter, boredcharts

pages = Path(__file__).parent.absolute() / "pages"
figure_router = BCRouter()


@figure_router.chart("population")
async def population(country: str) -> go.Figure:
    df = px.data.gapminder().query(f"country=='{country}'")
    fig = px.bar(df, x="year", y="pop")
    return fig


app = boredcharts(
    pages=pages,
    figure_router=figure_router,
)

Write a markdown report

pages/populations.md:

## Populations

USA's population has been growing linearly for the last 70 years:

{{ figure("population", country="United States") }}

Run your app

uvicorn main:app --reload

🎉Now you can view your reports at http://localhost:8000!

Going further

A more full project structure might look like this:

my-reports
├── myreports
│   ├── pages           <-- put your markdown reports here
│   │   └── example.md
│   ├── __init__.py
│   ├── app.py          <-- spin up the app here
│   └── figures.py      <-- define your figures here
├── README.md
└── pyproject.toml

Extensibility

The bored-charts app is just a FastAPI (ASGI) app, so you can integrate it into your existing projects or extend it as needed.

Roadmap

See the Github repo