Simple python api to visualize the plots in a script.
Project description
LocalVisualizer |Build Status|
------------------------------
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/
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
~~~~~
.. code:: 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)
Output
~~~~~~
This starts a HTTPServer and creates a html file which is dynamically
updated each time ``lviz`` is called.
.. figure:: https://i.imgur.com/jjwvAX2.png
:alt: The output of the above commands
Output image
Support and Requirements
~~~~~~~~~~~~~~~~~~~~~~~~
Python 2.7 (requires only std libraries).
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``: 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
.. |Build Status| image:: https://travis-ci.org/psvishnu91/local_visualizer.svg?branch=master
:target: https://travis-ci.org/psvishnu91/local_visualizer
=======
History
=======
0.1.0 (2017-11-05)
------------------
* First release on PyPI.
------------------------------
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/
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
~~~~~
.. code:: 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)
Output
~~~~~~
This starts a HTTPServer and creates a html file which is dynamically
updated each time ``lviz`` is called.
.. figure:: https://i.imgur.com/jjwvAX2.png
:alt: The output of the above commands
Output image
Support and Requirements
~~~~~~~~~~~~~~~~~~~~~~~~
Python 2.7 (requires only std libraries).
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``: 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
.. |Build Status| image:: https://travis-ci.org/psvishnu91/local_visualizer.svg?branch=master
:target: https://travis-ci.org/psvishnu91/local_visualizer
=======
History
=======
0.1.0 (2017-11-05)
------------------
* First release on PyPI.
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