Package: local-visualizer
[![Documentation Status](https://readthedocs.org/projects/local-visualizer/badge/?version=latest)](http://local-visualizer.readthedocs.io/en/latest/?badge=latest)[![Build Status](https://travis-ci.org/psvishnu91/local_visualizer.svg?branch=master)](https://travis-ci.org/psvishnu91/local_visualizer)[![PyPI version](https://badge.fury.io/py/local-visualizer.svg)](https://badge.fury.io/py/local-visualizer)## LocalVisualizerSimple 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``` bashpip install local-visualizer```### Motivation* When moving from an IPython notebook to a script, we lose the diagnosticsof visualizing pandas as tables and matplotlib plots.* :class:`LocalViz` starts a local http server and creates a html file towhich pandas tables and matplotlib plots can be sent over.* The html file is dynamically updated for long running scripts.### Usage``` pythonimport logging, sys, numpy as np, pandas as pd, matplotlib.pyplot as pltimport local_visualizerplt.style.use('fivethirtyeight')logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)# Create the local visualizer instancelviz = 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()```### OutputThis starts a HTTPServer and creates a html file which is dynamically updatedeach time ``lviz`` is called.![Output image]( https://i.imgur.com/jjwvAX2.png "The output of the above commands")### Support and RequirementsPython 2.7### API methods1. `p`: paragraph2. `br`: line break3. `hr`: Horizontal rule with line breaks4. `h1`, `h2`, ..., `h6`: Headers5. `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` object7. `start`: Applicable if `LocalViz` was initialized with `lazy=True`. Starts the server and creates the html file8. `close`: Completes the html file9. `del_html`: Deletes the html file### CreditsThis 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=======History=======0.2.0 (2017-11-06)------------------The close method no more deletes the html but only makes the html valid.0.1.0 (2017-11-05)------------------* First release on PyPI.