The use of __main__.py to create executables
myprojectfolder/
|_ __main__.py
|_ __init__.py
Being __main__.py:
print("Hello")
| border: no | |
| height: 960 | |
| license: gpl-3.0 |
| export HISTSIZE="" | |
| HIST_FILE=~/.bash_history | |
| BACK_FILE=~/.bash_history_backup | |
| if [ ! -f $BACK_FILE ];then touch -d "2 hours ago" $BACK_FILE;fi | |
| if test $(find $BACK_FILE -mmin +60); then | |
| HIST_SIZE=$(cat $HIST_FILE|wc -l) | |
| BACK_SIZE=$(cat $BACK_FILE|wc -l) | |
| GROWTH=$(($HIST_SIZE - $BACK_SIZE)) |
The use of __main__.py to create executables
myprojectfolder/
|_ __main__.py
|_ __init__.py
Being __main__.py:
print("Hello")
| Go to Bitbucket and create a new repository (its better to have an empty repo) | |
| git clone [email protected]:abc/myforkedrepo.git | |
| cd myforkedrepo | |
| Now add Github repo as a new remote in Bitbucket called "sync" | |
| git remote add sync [email protected]:def/originalrepo.git | |
| Verify what are the remotes currently being setup for "myforkedrepo". This following command should show "fetch" and "push" for two remotes i.e. "origin" and "sync" | |
| git remote -v |
| """making a dataframe""" | |
| df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB')) | |
| """quick way to create an interesting data frame to try things out""" | |
| df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd']) | |
| """convert a dictionary into a DataFrame""" | |
| """make the keys into columns""" | |
| df = pd.DataFrame(dic, index=[0]) |
| #!/usr/bin/env python | |
| #-*- coding:utf-8 -*- | |
| from matplotlib import pyplot | |
| import numpy as np | |
| class ClickPlot: | |
| """ | |
| A clickable matplotlib figure |