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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.
Install bored-charts and uvicorn:
pip install bored-charts uvicorn
# main.py
from pathlib import Path
import plotly.express as px
import plotly.graph_objects as go
from boredcharts import FigureRouter, boredcharts
figures = FigureRouter()
@figures.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=Path(__file__).parent, figures=figures)
<!-- populations.md -->
## Populations
USA's population has been growing linearly for the last 70 years:
{{ figure("population", country="United States") }}
uvicorn main:app --reload
🎉Now you can view your reports at http://localhost:8000!
A more full project structure might look like this (see the full example here):
my-reports
├── analysis <-- do your analysis and define your figures
│ ├── __init__.py
│ ├── figures.py
│ └── ...
├── pages <-- write your markdown reports
│ ├── example.md
│ └── ...
├── app.py <-- spin up the bored-charts app
├── pyproject.toml
└── README.md
The bored-charts app is just a FastAPI (ASGI) app, so you can integrate it into your existing projects or extend it as needed with existing solutions (e.g., adding authentication).
See the Github repo
FAQs
Easy, minimal, PDF-able data reports with python and markdown.
We found that bored-charts 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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