vispz/local_visualizer

Python LocalViz starts a local http server and creates a html file to which pandas dataframes and matplotlib plots can be streamed to dynamically.

LocalVisualizer

Simple python api to visualize the plots in a script.

• Free software: MIT license
• Documentation: https://local-visualizer.readthedocs.io
• PyPI: https://pypi.python.org/pypi/local-visualizer/

Installation

pip install local-visualizer

Motivation

• When moving from an IPython notebook to a script, we lose the diagnostics of visualizing pandas as tables and matplotlib plots.
• :class:LocalViz starts a local http server and creates a html file to which pandas tables and matplotlib plots can be sent over.
• The html file is dynamically updated for long running scripts.

Usage

import logging, sys, numpy as np, pandas as pd, matplotlib.pyplot as plt
import local_visualizer

plt.style.use('fivethirtyeight')
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)

# Create the local visualizer instance
lviz = local_visualizer.LocalViz(html_file='lviz_test.html', port=9112)
# INFO:root:Starting background server at: http://localhost:9112/.
# INFO:local_visualizer:Click: http://carpediem:9112/lviz_test.html or http://localhost:9112/lviz_test.html

# Create plots which will be streamed to the html file.
lviz.h3('Matplotlib :o')
lviz.p(
    'Wrap your plots in the figure context manager which takes '
    'in the kwargs of plt.figure and returns a plt.figure object.',
)

with lviz.figure(figsize=(10, 8)) as fig:
    x = np.linspace(-10, 10, 1000)
    plt.plot(x, np.sin(x))
    plt.title('Sine test')

lviz.hr()

# Visualize pandas dataframes as tables.
lviz.h3('Pandas dataframes')

df = pd.DataFrame({'A': np.linspace(1, 10, 10)})
df = pd.concat(
    [df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],
    axis=1,
)
lviz.write(df)
lviz.close()

Output

This starts a HTTPServer and creates a html file which is dynamically updated each time lviz is called.

Support and Requirements

Python 2.7

API methods

1. p: paragraph
2. br: line break
3. hr: Horizontal rule with line breaks
4. h1, h2, ..., h6: Headers
5. write: Directly write text to the html document (or pass in a pandas.DataFrame)
6. figure: Context manager which accepts the kwargs of plt.figure and returns a plt.figure object
7. start: Applicable if LocalViz was initialized with lazy=True. Starts the server and creates the html file
8. close: Completes the html file
9. del_html: Deletes the html file

Credits

This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter .. _audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage