Skip to main content

termplotlib

PyPi Version PyPI pyversions GitHub stars PyPi downloads

gh-actions codecov LGTM Code style: black

termplotlib is a Python library for all your terminal plotting needs. It aims to work like matplotlib.

Line plots

For line plots, termplotlib relies on gnuplot. With that installed, the code

import termplotlib as tpl
import numpy as np

x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)

fig = tpl.figure()
fig.plot(x, y, label="data", width=50, height=15)
fig.show()

produces

    1 +---------------------------------------+
  0.8 |    **     **                          |
  0.6 |   *         **           data ******* |
  0.4 | **                                    |
  0.2 |*              **                      |
    0 |                 **                    |
      |                                   *   |
 -0.2 |                   **            **    |
 -0.4 |                     **         *      |
 -0.6 |                              **       |
 -0.8 |                       **** **         |
   -1 +---------------------------------------+
      0     1    2     3     4     5    6     7

Horizontal histograms

import termplotlib as tpl
import numpy as np

rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample)

fig = tpl.figure()
fig.hist(counts, bin_edges, orientation="horizontal", force_ascii=False)
fig.show()

produces

hist1

Horizontal bar charts are covered as well. This

import termplotlib as tpl

fig = tpl.figure()
fig.barh([3, 10, 5, 2], ["Cats", "Dogs", "Cows", "Geese"], force_ascii=True)
fig.show()

produces

Cats   [ 3]  ************
Dogs   [10]  ****************************************
Cows   [ 5]  ********************
Geese  [ 2]  ********

Vertical histograms

import termplotlib as tpl
import numpy as np

rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample, bins=40)
fig = tpl.figure()
fig.hist(counts, bin_edges, grid=[15, 25], force_ascii=False)
fig.show()

produces

hist2

Tables

Support for tables has moved over to termtables.

Installation

termplotlib is available from the Python Package Index, so simply do

pip install termplotlib

to install.

Testing

To run the termplotlib unit tests, check out this repository and type

pytest

Similar projects

Release files for termplotlib 0.3.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for termplotlib 0.3.9
File Size Uploaded
termplotlib-0.3.9.tar.gz 24.5 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for termplotlib 0.3.9
File Interpreter ABI Platform
termplotlib-0.3.9-py3-none-any.whl Python 3 none any Details

Total release size: 46.1 kB

Release files / termplotlib-0.3.9.tar.gz

Download URL termplotlib-0.3.9.tar.gz
Size 24.5 kB
Tags Source
SHA-256 checksum
How to use checksums
c04cbd67ac61753eac9162a99cbe87c379d4c5daf720af1df55f4423c094203e
BLAKE2b-256 checksum
How to use checksums
b4608a74d2503dd64975402c7b8d00f6e201e8cbba5348282433fa5fb8d41b67
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

Release files / termplotlib-0.3.9-py3-none-any.whl

Download URL termplotlib-0.3.9-py3-none-any.whl
Size 21.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
827bec59e0de24dfe265b9d9a4adc4df8335aa98f49c1122bd53ced9b72c5206
BLAKE2b-256 checksum
How to use checksums
69d0ea24907a6d1e3c5e40ff5b58920552c3e1e4e73181a8583d5bd9d5217305
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

Release history Release notifications | RSS feed

This release

0.3.9 This release

2 release files

0.3.8

2 release files

0.3.7

2 release files

0.3.6

2 release files

0.3.5

2 release files

0.3.4

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.4

2 release files

0.2.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page