# 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:
```bash
pip install bored-charts uvicorn
```
### Create your app
```python
# 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)
```
### Write a markdown report
```md
<!-- populations.md -->
## Populations
USA's population has been growing linearly for the last 70 years:
{{ figure("population", country="United States") }}
```
### Run your app
```bash
uvicorn main:app --reload
```
🎉Now you can view your reports at [http://localhost:8000](http://localhost:8000)!
## Going further
A more full project structure might look like this
(see the [full example here](https://github.com/oliverlambson/bored-charts/tree/main/examples/full)):
```
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
```
## Supported charting libraries
- [matplotlib](https://matplotlib.org/)
- [plotly](https://plotly.com/python/)
- [vega-altair](https://altair-viz.github.io/)
- [seaborn](https://seaborn.pydata.org/)
## 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
with existing solutions (e.g., adding authentication).
## Roadmap
See the [Github repo](https://github.com/oliverlambson/bored-charts)
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"description": "# bored-charts\n\nBuild easy, minimal, PDF-able data reports with markdown and python.\n\nThe idea is you do your analysis in Python, as you normally would, and dumping your\nfigures into a nice report written in markdown is now super low-effort: you decorate\nthe function to generate the figure (that you already wrote when doing your analysis)\nand it becomes available to bored-charts so you can present your findings clearly.\n\n## Minimal example\n\nInstall bored-charts and uvicorn:\n\n```bash\npip install bored-charts uvicorn\n```\n\n### Create your app\n\n```python\n# main.py\n\nfrom pathlib import Path\n\nimport plotly.express as px\nimport plotly.graph_objects as go\nfrom boredcharts import FigureRouter, boredcharts\n\nfigures = FigureRouter()\n\n\n@figures.chart(\"population\")\nasync def population(country: str) -> go.Figure:\n df = px.data.gapminder().query(f\"country=='{country}'\")\n fig = px.bar(df, x=\"year\", y=\"pop\")\n return fig\n\n\napp = boredcharts(pages=Path(__file__).parent, figures=figures)\n```\n\n### Write a markdown report\n\n```md\n<!-- populations.md -->\n\n## Populations\n\nUSA's population has been growing linearly for the last 70 years:\n\n{{ figure(\"population\", country=\"United States\") }}\n```\n\n### Run your app\n\n```bash\nuvicorn main:app --reload\n```\n\n\ud83c\udf89Now you can view your reports at [http://localhost:8000](http://localhost:8000)!\n\n## Going further\n\nA more full project structure might look like this\n(see the [full example here](https://github.com/oliverlambson/bored-charts/tree/main/examples/full)):\n\n```\nmy-reports\n\u251c\u2500\u2500 analysis <-- do your analysis and define your figures\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 __init__.py\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 figures.py\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 ...\n\u251c\u2500\u2500 pages <-- write your markdown reports\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 example.md\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 ...\n\u251c\u2500\u2500 app.py <-- spin up the bored-charts app\n\u251c\u2500\u2500 pyproject.toml\n\u2514\u2500\u2500 README.md\n```\n\n## Supported charting libraries\n\n- [matplotlib](https://matplotlib.org/)\n- [plotly](https://plotly.com/python/)\n- [vega-altair](https://altair-viz.github.io/)\n- [seaborn](https://seaborn.pydata.org/)\n\n## Extensibility\n\nThe bored-charts app is just a FastAPI (ASGI) app,\nso you can integrate it into your existing projects or extend it as needed\nwith existing solutions (e.g., adding authentication).\n\n## Roadmap\n\nSee the [Github repo](https://github.com/oliverlambson/bored-charts)\n",
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