jupyter notebook

Scenario 1: Getting a customized kernel
I have a question about getting a customized kernel on the company sponsored JupyterHub, and the answers are as following:

Open a Terminal within JupyterHub: 
Select the “New” pulldown and select “Terminal”
conda create --name 36env python=3.6
conda activate 36env
pip install numpy --user
conda deactivate
python3 -m ipykernel install --user --name 36env
Refresh the JupyterHub browser window.
Your new conda environment is now available

Python programming architecture

I need to give credit to Kenneth Reitz, who gives great instruction on this top.

Lesson 1: reproduce what Ken suggested

	
  • Fork Ken's github repository and make my own
  • When I am in ./sample/ folder, and try "make", it fails. Error was "OSError: [Errno 13] Permission denied: '/ddn/gs1/biotools/python/lib/python2.7/site-packages/nose'"
  • When I am in ./sample/ folder, and try "python setup.py install", it fails also. Error was " [Errno 13] Permission denied: '/ddn/gs1/biotools/python/lib/python2.7/site-packages/test-easy-install-147300.write-test'"
  • Topic 1: how can I solve this problem

    Getting all the bolts and nuts ready

    I am trying to create a workable environment for data analysis. Now on my list I have the following to be installed on my windows machine

    Anaconda (maybe conda also)

    I installed the Anoconda(v1.4.0) on the user level
    

    Jupyter

    I followed the link and installed jupyter
    I can launch "jupyter notebook" and see the web on localhost:8888,
    But, I do not see the coding environment available
    


    Zipline

    It is a little bit into it to get zipline installed. So, I tested using conda with “sub-environment”. zipline only works with python2.7!!

    C:\Users\li11>conda create -n ForZipline python=2.7 biopython
    (ForZipline) C:\Users\li11>conda intall -c Quantopian zipline
    


    Using jupyter

    Thank goes to our system admin and Anaconda. Both Python2 and Python3 have been installed on my windows machines. Now I can launch the “jupyter” directly. From now on, I will stick with the jupyter IDE (Interactive Development Environment).