local-visualizer 0.2.0

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## 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
``` bash
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
``` python
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


=======
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.