---

Feel free to give a star to my new repo, great thanks Awesome-FinTech

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Hi, there

I'm so glad that this repo still draws you guys' attention until today. but actually I won't spend any time on it and I've got a much better way to draw dynamic plots in ipython notebook, and I've just post a blog about how to make it in notebooks (including source code and demo notebook).

which looks like bellow:

Please check it here: http://litaotao.github.io/dynamic-charts-matplotlib-alternative-ipython-notebook-python-drawing-js

Thank you guys again, and if possible, please don't cancel your stars, ha~ha, any problems and questions when using the new method will get answered as long as you put it under that post.

thanks again, taotao~

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Inspired by IPython, built with love

IPython-Dashboard

A stand alone, light-weight web server for building, sharing graphs created in IPython. Build for data science, data analysis guys. Aiming at building an interactive visualization, collaborated dashboard, and real-time streaming graph.

Screenshot and Demo

Demo on Youtube
Demo on Youku

Usage

• Install prerequisite

  • install the latest stable IPython-Dashboard: pip install ipython-dashboard --upgrade
  • install redis 2.6+ : install guide
  • [option, if you need run sql]install mysql : brew install mysql or apt-get install mysql
  • install IPython-Dashboard requirements [unneeded sometimes]:
    • cd ~/your python package path/IPython-Dashboard
    • pip install -r requirements.txt

• [option, if you need run sql]Config mysql

  • start mysql server : mysql.server start

  • login in mysql using root : mysql -u root

  • create a user and grant privileges;

    • take a look at current database user

    mysql> SELECT User,Host FROM mysql.user;
    +------+-----------+
    | User | Host      |
    +------+-----------+
    | root | 127.0.0.1 |
    | root | ::1       |
    |      | localhost |
    | root | localhost |
    |      | mac007    |
    | root | mac007    |
    +------+-----------+
    6 rows in set (0.00 sec)
    

    • create a user for IPython-Dashboard

    mysql> create user 'ipd'@'localhost' identified by 'thanks';
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> grant all privileges on *.* to ipd@localhost;
    Query OK, 0 rows affected (0.00 sec)
    
    mysql> SELECT User,Host FROM mysql.user;
    +------+-----------+
    | User | Host      |
    +------+-----------+
    | root | 127.0.0.1 |
    | root | ::1       |
    |      | localhost |
    | ipd  | localhost |
    | root | localhost |
    |      | mac007    |
    | root | mac007    |
    +------+-----------+
    7 rows in set (0.00 sec)
    
    mysql> flush privileges;
    Query OK, 0 rows affected (0.00 sec)
    

  • create tables;

    nosetests -s dashboard.tests.testCreateData:test_create_mysql_data
    

• Create logging path

  • create a folder to store log files. I put it under mnt currently: /mnt/ipython-dashboard/logs
  • make sure the log folder is write-able, using chmod and ls -l to confirm.

  chenshan@mac007:/mnt/ipython-dashboard$ls -l
  total 0
  drwxrwxrwx  9 root  wheel  306 Dec 15 22:09 logs
  

• Config IPython-Dashboard server : IPython-Dashboard/dashboard/config.py

  • app_host='ip_address:port'

• Start redis and IPython-Dashboard server

  chenshan@mac007:~/Desktop/github/IPython-Dashboard$redis-server &
  
  chenshan@mac007:~/Desktop/github/IPython-Dashboard$dash-server --help
  usage: dash-server [-h] [-H HOST] [-p PORT] [-d DEBUG]
  
  Start your IPython-Dashboard server ...
  
  optional arguments:
    -h, --help            show this help message and exit
    -H HOST, --host HOST  server host, default localhost
    -p PORT, --port PORT  server port, default 9090
    -d DEBUG, --debug DEBUG
                          server port, default true
  
  chenshan@mac007:~/Desktop/github/IPython-Dashboard$dash-server
  Namespace(debug=True, host='0.0.0.0', port=9090)
   * Running on http://0.0.0.0:9090/
   * Restarting with reloader
  Namespace(debug=True, host='0.0.0.0', port=9090)
  

• Do your exploring

  • IPython-Dashboard-Tutorial.ipynb : On nbviewer or On github

Goal

• support raw html visualization
• support python object visualization
• Editable
• Real-time fresh when rendering a variable python object
• Can be shared, both public and private [ need password ]
• In the notebook, can share an object to a dashboard [ that's visualize that object in that dashboard ]

Use Case

• exploring in notebook, share/send the result/summary to people, without the details.
• share some data in a private notebook.
• disappointed with the complicated code when drawing a graceful/staic graph using matplotlib/seaborn/mpld3 etc.
• want an interactive graph, allow people to zoom in/out, resize, get hover tips, change graph type easily.
• want a real-time graph.
• want an collaborated graph/dashboard.

Run tests

just run sudo nosetests --with-coverage --cover-package=dashboard under this repo

taotao@mac007:~/Desktop/github/IPython-Dashboard$sudo nosetests --with-coverage --cover-package=dashboard
Password:
../Users/chenshan/Desktop/github/IPython-Dashboard/dashboard/tests/testCreateData.py:69: Warning: Can't create database 'IPD_data'; database exists
  conn.cursor().execute('CREATE DATABASE IF NOT EXISTS {};'.format(config.sql_db))
/Users/chenshan/Desktop/github/IPython-Dashboard/dashboard/server/utils.py:135: Warning: Unknown table 'ipd_data.businesses'
  cursor.execute(sql)
/Library/Python/2.7/site-packages/pandas/io/sql.py:599: FutureWarning: The 'mysql' flavor with DBAPI connection is deprecated and will be removed in future versions. MySQL will be further supported with SQLAlchemy engines.
  warnings.warn(_MYSQL_WARNING, FutureWarning)
...
Name                                    Stmts   Miss  Cover   Missing
---------------------------------------------------------------------
dashboard.py                               13      0   100%
dashboard/client.py                         1      0   100%
dashboard/client/sender.py                 11      3    73%   26-27, 33
dashboard/conf.py                           0      0   100%
dashboard/conf/config.py                   29      0   100%
dashboard/server.py                         0      0   100%
dashboard/server/resources.py               0      0   100%
dashboard/server/resources/dash.py         35     10    71%   36, 55-56, 67-69, 86-89
dashboard/server/resources/home.py         40     12    70%   25, 28-30, 83-91
dashboard/server/resources/sql.py          27     11    59%   30, 52-75
dashboard/server/resources/status.py        8      1    88%   19
dashboard/server/resources/storage.py      13      5    62%   26-28, 43-47
dashboard/server/utils.py                  79     18    77%   20-24, 78-80, 82-83, 86, 96, 99-100, 126-127, 140-142
dashboard/server/views.py                  21      1    95%   16
---------------------------------------------------------------------
TOTAL                                     277     61    78%
----------------------------------------------------------------------
Ran 5 tests in 9.885s

OK
taotao@mac007:~/Desktop/github/IPython-Dashboard$

Change Log

• future

  • front side, databricks style
  • pep 8, code clean up & restructure
  • hover tips
  • edit modal can be resized
  • Share one graph
  • Share one dashboard
  • Presentation mode
  • footer
  • unified message display center
  • SQL Editor
  • login management
  • unified logger and exception report
  • server side log
  • client side log
  • support python3
  • create examples
  • render sql in dashboard
  • chart optimize

• V 0.1.6 : optimize-chart [ current develop version ]

  • Dashboard

    • re-structure code, follow pep8 style
    • create 1 example
    • optimize chart

  • SQL Editor

    • optimize page
    • render sql result as graph

• V 0.1.5 : sql-server-log [ current stable version ]

  • Dashboard

    • create 1 example
    • server side log
    • support x-axis as date format
    • research on real-time updated dataframe

  • SQL Editor

    • sql server develop : render sql result as table view

Related Projects & Products

• mpld3
• lighting
• bokeh
• matplotlib
• zeppelin
• yhat
• hue
• plotly
• datadog
• databricks
• nvd3
• c3js
• periscope
• folium
• metabase
• gridstack
• gridster
• dashboards
• js, css, html code style
• www.creative-tim.com
• creative-tim dashboard