Skip to content

Run IPython, Pattern, NLTK, Pandas, NumPy, SciPy, Numba, Biopython and Scikit-learn inside Docker

Notifications You must be signed in to change notification settings

Jacq/docker-ipython

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

37 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

docker-ipython

Run IPython inside Docker

####Includes:

####Instructions

  1. Build Docker image using the using build script. This can take a long time, ~30mins. Luckily this step only has to done once(or whenever you change the Dockerfile).
  2. Create and shell into new Docker container using shell script
  3. Start IPython Notebook in the container using supervisord&
  4. Point your brower to http://<your host name>:8888, default login password is 'password'

To run in background execute ./start [host_path] and host_path will be mounted as the notebook folder of ipython

Background mode

In background or using supervisord the user ipy is used to run the ipython notebook. The /home/ipy/.python contains the configuration options that were copied from the profile_nbserver.

Removing or changing password authentication

In order to remove password authentication, modify the configuration in this file by commenting out the line c.NotebookApp.password = u'sha1:01dc1e3ecfb8:cc539c4fcc2ef3d751e4a20d918f761fd6704798'

To change the password

  1. Get your hashed password by executing in your python client the following:
In [1]: from IPython.lib import passwd
In [2]: passwd()
Enter password:
Verify password:
  1. Replace the line in config file with c.NotebookApp.password = u'sha1:yourhashedpassword'

####Version Detail

>pip freeze

Bottleneck==0.7.0
Cython==0.19.2
Jinja2==2.7.1
MarkupSafe==0.18
Pattern==2.6
PyYAML==3.10
Pygments==1.6
argparse==1.2.1
beautifulsoup4==4.3.2
biopython==1.63
distribute==0.7.3
html5lib==0.99
ipython==1.1.0
llvmmath==0.1.1
llvmpy==0.11.2 # latest version pops a missing versioneer module 
lxml==2.3.2
matplotlib==1.3.1
medusa==0.5.4
meld3==0.6.5
networkx==1.8.1
nltk==2.0.4
nose==1.3.0
numba==0.11.0
numexpr==2.2.2
numpy==1.7.1
pandas==0.12.0
patsy==0.2.1
pymc==2.3
pyparsing==2.0.1
python-dateutil==2.2
pytz==2013.8
pyzmq==14.0.1
scipy==0.13.2
six==1.4.1
statsmodels==0.5.0
supervisor==3.0a8
sympy==0.7.4.1
tornado==3.1.1
wsgiref==0.1.2

Also includes 0MQ 4.0.3 and LLVM 3.2

About

Run IPython, Pattern, NLTK, Pandas, NumPy, SciPy, Numba, Biopython and Scikit-learn inside Docker

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 76.9%
  • Shell 23.1%