Figurex
Make figures with context managers in python: quicker, simpler, more readable.
with Figure() as ax:
ax.plot([1,2],[3,4])
Idea
Tired of lengthy matplotlib code just for simple plotting?
# How plotting used to be:
import matplotlib.pyplot as plt
fig, axes = plt.subplots(1,2, figsize=(4,5))
plt.set_title("My plot")
ax = axes[0]
ax.plot([1,2],[3,4])
ax = axes[1]
ax.plot([2,3],[4,5])
fig.savefig("file.png", bbox_inches='tight')
plt.show()
Beautify your daily work with shorter and more readable code:
# How plotting becomes with figurex:
from figurex import Figure, Panel
with Figure("My plot", layout=(1,2), size=(4,5), save="file.png"):
with Panel() as ax:
ax.plot([1,2],[3,4])
with Panel() as ax:
ax.plot([2,3],[4,5])
The Figure() environment generates the matplotlib-based figure and axes for you, and automatically shows, saves, and closes the figure when leaving the context. It is just a wrapper around standard matplotlib code, you can use ax to modify the plot as you would normally do. Extend it your way without limits!
Examples
Make a simple plot:
with Figure("A simple plot") as ax:
ax.plot([1,2],[3,4])
A plot with two panels:
with Figure(layout=(1,2), size=(6,3)):
with Panel("a) Magic") as ax:
ax.plot([1,2],[3,4])
with Panel("b) Reality", grid="") as ax:
ax.plot([5,5],[6,4])
Save a plot into memory for later use (e.g. in FPDF):
with Figure("Tea party", show=False):
with Panel() as ax:
ax.plot([5,5],[6,4])
my_figure = Figure.as_object()
# <_io.BytesIO at 0x...>
Plotting maps:
from figurex.basemap import Basemap
with Figure(size=(3,3)):
with Basemap("Germany", extent=(5,15,46,55), tiles="relief") as Map:
x,y = Map(12.385, 51.331)
Map.scatter(x, y, marker="x", color="red", s=200)
- Check out the Examples Notebook!
Documentation
A documentation and API reference can be found on ReadTheDocs:
- Figure (context manager)
- Panel (context manager)
- Basemap (context manager)
- Cartopy (context manager)
Install
pip install figurex
If you want to use geospatial mapping features with Basemap or Cartopy, install the corresponding optional features:
pip install figurex[basemap]
pip install figurex[cartopy]
If you work with uv, replace pip install by uv add.
Requirements
- python >3.10
- numpy >2.0
- matplotlib >3.0
- basemap >=2.0 (optional)
- cartopy >=0.25 (optional)
- scipy (optional, required by cartopy)
Related
- A discussion on GitHub/matplotlib actually requested this feature long ago.
- The project GitHub/contextplt has implemented a similar concept.
1 maintainer
Metadata
1 maintainer
Release files for figurex 0.2.15
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| figurex-0.2.15.tar.gz | 15.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| figurex-0.2.15-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 30.1 kB
Release files / figurex-0.2.15.tar.gz
| Download URL | figurex-0.2.15.tar.gz |
|---|---|
| Size | 15.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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No |
| Uploaded via |
uv/0.8.5
|
Release files / figurex-0.2.15-py3-none-any.whl
| Download URL | figurex-0.2.15-py3-none-any.whl |
|---|---|
| Size | 14.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.8.5
|
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