https://github.com/olavolav/uniplot
Lightweight plotting to the terminal. 4x resolution via Unicode.
https://github.com/olavolav/uniplot
ascii-art braille ci cli console dataviz observability plot python terminal tui unicode
Last synced: 28 days ago
JSON representation
Lightweight plotting to the terminal. 4x resolution via Unicode.
- Host: GitHub
- URL: https://github.com/olavolav/uniplot
- Owner: olavolav
- License: mit
- Created: 2020-08-15T12:21:10.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2026-01-04T12:38:49.000Z (about 1 month ago)
- Last Synced: 2026-01-06T19:31:34.655Z (about 1 month ago)
- Topics: ascii-art, braille, ci, cli, console, dataviz, observability, plot, python, terminal, tui, unicode
- Language: Python
- Homepage:
- Size: 51.7 MB
- Stars: 431
- Watchers: 3
- Forks: 21
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# Uniplot
[](https://github.com/olavolav/uniplot/actions?query=workflow%3A"Unit+Tests")
[](https://pypi.org/project/uniplot/)
[](https://pepy.tech/project/uniplot)
Lightweight plotting to the terminal. 4x resolution via Unicode.
When working with production data science code it can be handy to have plotting
tool that does not rely on graphics dependencies or works only in a Jupyter
notebook.
The **use case** that this was built for is to have plots as part of your data
science / machine learning CI/CD pipeline - that way whenever something goes
wrong, you get not only the error and backtrace but also plots that show what
the problem was.
## Features
* Unicode drawing, so 4x the resolution (pixels) of usual ASCII plots, or even
8x when using Braille characters
* Super simple API
* Interactive mode (pass `interactive=True`)
* Color mode (pass `color=True`) useful in particular when plotting multiple series
* It's fast: Plotting 1M data points takes 26ms thanks to NumPy magic
Please note that Unicode drawing will work correctly only when using a font
that fully supports the [Block Elements character
set](https://en.wikipedia.org/wiki/Box-drawing_character) or the [Braille
character set](https://en.wikipedia.org/wiki/Braille_Patterns). Please refer to
[this page for a (incomplete) list of supported
fonts](https://www.fileformat.info/info/unicode/block/block_elements/fontsupport.htm)
and the options below to select the character set.
## Simple example
```python
import math
x = [math.sin(i / 20) + i / 300 for i in range(600)]
from uniplot import plot
plot(x, title="Sine wave")
```
Result:
```
Sine wave
┌────────────────────────────────────────────────────────────┐
│ ▟▀▚ │
│ ▗▘ ▝▌ │
│ ▗▛▜▖ ▞ ▐ │
│ ▞ ▜ ▗▌ ▌ │ 2
│ ▟▀▙ ▗▘ ▝▌ ▐ ▜ │
│ ▐▘ ▝▖ ▞ ▜ ▌ ▝▌ │
│ ▗▛▜▖ ▛ ▜ ▗▌ ▝▌ ▐▘ ▜ │
│ ▛ ▙ ▗▘ ▝▖ ▐ ▚ ▞ ▝▌ │
│ ▟▀▖ ▐▘ ▝▖ ▟ ▚ ▌ ▝▖ ▗▌ ▜▄│ 1
│ ▐▘ ▐▖ ▛ ▙ ▌ ▐▖ ▗▘ ▚ ▞ │
│ ▛ ▙ ▗▘ ▐▖ ▐ ▙ ▞ ▝▙▟▘ │
│▐▘ ▐▖ ▐ ▌ ▛ ▐▖ ▗▘ │
│▞ ▌ ▌ ▐ ▗▘ ▜▄▛ │
│▌─────▐────▐▘───────▙──▞────────────────────────────────────│ 0
│ ▌ ▛ ▝▙▟▘ │
│ ▜ ▐▘ │
│ ▙▄▛ │
└────────────────────────────────────────────────────────────┘
100 200 300 400 500 600
```
For more examples, please see the `examples/` folder.
## Parameters
The `plot` function accepts a number of parameters, all listed below. Note that
only `ys` is required, all others are optional.
There is also a `plot_to_string` function with the same signature, if you want
the result as a list of strings, to include the output elsewhere. The only
difference is that `plot_to_string` does not support interactive mode.
### Data
* `xs` - The x coordinates of the points to plot. Can either be `None`, or a
list or NumPy array for plotting a single series, or a list of those for
plotting multiple series. Defaults to `None`, meaning that the x axis will be
just the sample index of `ys`.
* `ys` - The y coordinates of the points to plot. Can either be a list or NumPy
array for plotting a single series, or a list of those for plotting multiple
series.
In both cases, NaN or `None` values are ignored.
Note that since v0.12.0 you can also pass a list or an NumPy array of
timestamps, and the axis labels should be formatted correctly.
### Options
In alphabetical order:
#### Basic options
* `color` - Draw series in color. Defaults to `False` when plotting a single
series, and to `True` when plotting multiple. Also accepts a list of colors,
identified by strings like `"red"` for simple ANSI colors, tuples of RGB
values like `(255,0,0)`, or hexadecimal RGB colors like `"#B4FBB8"`.
Alternaively, you can specify a color theme as a string, as defined in
`uniplot/color_themes.py`. Note that for RGB colors you need to use a
terminal that supports them.
* `height` - The height of the plotting region, in characters. Default is `17`.
* `interactive` - Enable interactive mode. Defaults to `False`.
* `legend_labels` - Labels for the series. Can be `None` or a list of strings.
Defaults to `None`.
* `lines` - Enable lines between points. Can either be `True` or `False`, or a
list of Boolean values for plotting multiple series. Defaults to `False`.
* `title` - The title of the plot. Defaults to `None`.
* `width` - The width of the plotting region, in characters. Default is `60`.
Note that if the `line_length_hard_cap` option (see "Advanced options" below)
is used and there is not enough space, the actual width may be smaller.
* `x_max` - Maximum x value of the view. Defaults to a value that shows all
data points.
* `x_min` - Minimum x value of the view. Defaults to a value that shows all
data points.
* `x_unit` - Unit of the x axis. This is a string that is appended to the axis
labels. Defaults to `""`.
* `y_max` - Maximum y value of the view. Defaults to a value that shows all
data points.
* `y_min` - Minimum y value of the view. Defaults to a value that shows all
data points.
* `y_unit` - Unit of the y axis. This is a string that is appended to the axis
labels. Defaults to `""`.
#### Advanced options
* `character_set` - Which Unicode character set to use. Use `"block"` for
the [Block Elements character
set](https://en.wikipedia.org/wiki/Block_Elements) with 4x resolution, or
`"braille"` for the [Braille character
set](https://en.wikipedia.org/wiki/Braille_Patterns) with 8x resolution,
`"ascii"` to use ASCII characters only. Braille has the highest resolution,
and a lighter look overall. Defaults to `"block"`.
* `force_ascii_characters` - List of characters to use when using the
ASCII character set. Defaults to `["+", "x", "o", "*", "~", "."]`.
* `legend_placement` - Arrangement of the legend labels. `"auto"` attempts to
place them one or more rows next to each other, while `"vertical"` is a
block with one label per row. Defaults to `"auto"`.
* `line_length_hard_cap` - Enforce a hard limit on the number of characters per
line of the plot area. This may override the `width` option if there is not
enough space. Defaults to `None`.
* `rounded_corners` - Draw bounding box with round corners. Defaults to `False.
* `x_as_log` - Plot the x axis as logarithmic scale. Defaults to `False`.
* `x_gridlines` - A list of x values that have a vertical line for better
orientation. Defaults to `[0]`, or to `[]` if `x_as_log` is enabled.
* `x_gridlines_color` - A boolean or a list of colors for the vertical
gridlines, as specified above for the `color` option. Defaults to `False`.
* `x_labels` - Enable axis labels for the x axis. Defaults to `True`.
* `y_as_log` - Plot the y axis as logarithmic scale. Defaults to `False`.
* `y_gridlines` - A list of y values that have a horizontal line for better
orientation. Defaults to `[0]`, or to `[]` if `y_as_log` is enabled.
* `y_gridlines_color` - A boolean or a list of colors for the horizontal
gridlines, as specified above for the `color` option. Defaults to `False`.
* `y_labels` - Enable axis labels for the y axis. Defaults to `True`.
### Changing default parameters
uniplot does not store a state of the configuration parameters. However, you
can define a new plot funtion with new defaults by defining a `partial`. See
the following example:
```python
from functools import partial
from uniplot import plot as default_plot
plot = partial(default_plot, height=25, width=80)
```
This defines a new `plot` function that is identical to the original, except
the default values for `width` and `height` are now different.
## Experimental features
### Plotting histograms
For convenience there is also a `histogram` function that accepts one or more
series and plots bar-chart like histograms. It will automatically discretize
the series into a number of bins given by the `bins` option and display the
result.
Additional options, in alphabetical order:
* `bins` - Number of bins to use. Defaults to `20`.
* `bins_min` - Lower limit of the first bin. Defaults to the minimum of the
series.
* `bins_max` - Upper limit of the last bin. Defaults to the maximum of the
series.
When calling the `histogram` function, the `lines` option is `True` by default.
Example:
```python
import numpy as np
x = np.sin(np.linspace(1, 1000))
from uniplot import histogram
histogram(x)
```
Result:
```
┌────────────────────────────────────────────────────────────┐
│ ▛▀▀▌ │ ▐▀▀▜ │ 5
│ ▌ ▌ │ ▐ ▐ │
│ ▌ ▌ │ ▐ ▐ │
│ ▌ ▀▀▀▌ │ ▐▀▀▀ ▝▀▀▜ │
│ ▌ ▌ │ ▐ ▐ │
│ ▌ ▌ │ ▐ ▐ │
│ ▌ ▙▄▄▄▄▄▖ │ ▗▄▄▄ ▐ ▐ │
│ ▌ ▌ │ ▐ ▐ ▐ ▐ │
│ ▌ ▌ │ ▐ ▐ ▐ ▐ │
│ ▌ ▌ │ ▐ ▐ ▐ ▐ │
│ ▌ ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▜ ▐▀▀▀ ▝▀▀▀ ▐ │
│ ▌ │ ▐ ▐ ▐ │
│ ▌ │ ▐ ▐ ▐ │
│ ▌ │ ▐▄▄▟ ▐ │
│ ▌ │ ▐ │
│ ▌ │ ▐ │
│▄▄▄▌▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁│▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▐▄▄▄│ 0
└────────────────────────────────────────────────────────────┘
-1 0 1
```
### Arrow keys and FPS-style keys
In interactive mode, we now also support wasd or FPS-style keyboard layout and
the arrow keys. Arrows should work on most platforms like Mac, Linux or Windows. We might make the keyboard layout fully configurable, to change the current Vim-inspired one, at a later date. For now, you have 3 ways to move the view:
* Vim-style: `h` left, `j` down, `k` up, `l` right, `u` zoom in, `n` zoom out.
* FPS-style: `a` left, `s` down, `w` up, `d` right, `]` zoom in, `[` zoom out.
* Arrow keys: movement obvious, `]` zoom in, `[` zoom out.
### Streaming
There is initial support for streaming using the `plot_gen` function. The idea
is have a class that wraps the plot function and the state of plotting, such
that we can `update` the state of the plot.
Example, assuming we had a function called `get_new_data` to get new data from
some source:
```python3
from uniplot import plot_gen
plt = plot_gen()
ys = []
while True:
ys.append(get_new_data())
plt.update(ys=ys, title=f"Streaming: {len(ys)} data point(s) ...")
```
See `examples/5-streaming.py` for a more complete example.
## Installation
Install via pip using:
```shell
pip install uniplot
```
## Contributing
Clone this repository, and make sure you
[have uv installed](https://docs.astral.sh/uv/getting-started/installation/).
On most Linux-like systems like MacOS you can run:
```shell
make
```
See the `Makefile` for details and more granular commands.
Alternatively, on systems like Windows that do not have `make` installed, you can run:
```shell
uv run scripts/run_tests.sh
```
Then proceed with issues, PRs etc. the usual way.
## Projects that use uniplot
* The [Photovoltaic Geographic Information System (PVGIS)](https://code.europa.eu/pvgis/pvgis)
uses uniplot to [generate horizon plots](https://asciinema.org/a/pynlwepKNRE6gqKqwPr6JmzTP).
* The [FlexMeasures] CLI uses uniplot to [plot beliefs in sensors](https://github.com/FlexMeasures/flexmeasures/blob/2e3680cb35c1a4f2b94c7f77f9eb2ff70760755e/flexmeasures/cli/data_show.py#L754) for smart power control.
You can find many more in the [Dependency Graph](https://github.com/olavolav/uniplot/network/dependents).