How to parse multiple nested sub-commands using python argparse?
I am implementing a command line program which has interface like this:
I am implementing a command line program which has interface like this:
I am trying to write a paper in IPython notebook, but encountered some issues with display format. Say I have following dataframe df, is there any way to format var1 and var2 into 2 digit decimals and var3 into percentages.
I’ve been working on a new dev platform using nginx/gunicorn and Flask for my application.
I have a very large data set and I can’t afford to read the entire data set in. So, I’m thinking of reading only one chunk of it to train but I have no idea how to do it. Any thought will be appreciated.
Is there a way to install python 3 over an installation of python 2 without ruining anything? The main issue is that I have code that runs by “python xxxxx.py abc123”. Is there a way to change python 3 to be “python3 xxxx.py abc123”? The same command python is the conflict Answers: Thank you for … Read more
I’m trying to establish a secure socket connection in Python, and i’m having a hard time with the SSL bit of it. I’ve found some code examples of how to establish a connection with SSL, but they all involve key files. The server i’m trying to connect with doesn’t need to receive any keys or certificates. My question is how do I essentially wrap a python socket connection with SSL. I know for a fact that the cipher i’m suppose to use is ADH-AES256-SHA, and the protocol is TLSv1. This is what i’ve been trying:
I’m writing a recipe organizer as a sample project for a class. I’m not very experienced with DRF other than using some very basic functionality. Here’s the objective:
I have a 2D matrix and I want to take norm of each row. But when I use numpy.linalg.norm(X) directly, it takes the norm of the whole matrix.
I am running Linux (2.6.18-164.15.1.el5.centos.plus) and trying to install pyodbc. I am doing pip install pyodbc and get a very long list of errors, which end in
After Training, I saved Both Keras whole Model and Only Weights using