Dinosawer wrote:ARISE THREAD AND REVEL IN YOUR NEW-FOUND USEFULNESS

myself and several other people who regularly hang out on the Limit Theory IRC are Python programmers and are more than willing to help you if you have a problem, so feel free to drop by.

For a long time I've used Spyder, which is not a bad IDE, having a built-in python console and debugging and so on, but is lacking in code collapsing (there is none) and auto-complete (it only completes functions you've already used in that file - I expect auto-complete to at least fill in stuff from the standard library too).

Pycharm (the community edition, which is free)
It has code folding, and does have auto-complete for all your installed python packages, support both 2.7 and 3.* at the same time.

(spyder has 2 separate versions), built-in version control (I tested github and it just works™, cloning, commiting and pushing), extensive code inspecting (errors and warnings), autoformatting, built-in console and debugger and so on.
Have only played with it for a little bit but I like it a lot so far.
Screenshot:

Spoiler:      SHOW

Nikky (Achati) wrote: This is basically a simpler version of pycharm
which is tailored for people learning the language
and also has about everything you will need included
including downloading pip packages iirc
edu is even simpler
maybe a plus if you dont want to know how the build process behind it works or some stuff that needs to be external in community/ full-version isnt working
because as far as i can see its all integrated in edu
also apperently python courses are included

Jason S wrote: I should really add more to it, but it does have a neat example of starting a 2d top down game which you can use as a starting point for your creation.

print ""
Store_IP = '10.25.'

def Create_IP_Address(Store_IP, Third, Fourth):
	print "Here are 3 different ways to display the results"
	print "1: Your IP Address is %s%s.%s" % (Store_IP, Third, Fourth)
	print "2: Your IP Address is " + Store_IP + Third + "." + Fourth
	print "3: " + Store_IP + Third + "." + Fourth

def main():
	Third = raw_input("Enter the 3rd octet: ")
	Fourth = raw_input("Enter the 4th octet: ")
	print ""
	Create_IP_Address(Store_IP, Third, Fourth)
	print ""
	
main()

# Importing os will allow file accessing
import os

slash = '\\'

# The root directory to scan
directoryStart = r'C:\Users\Public'

# Use walk method to transverse a directory tree and files within it
for directoryName, directoryNames, fileNames in os.walk(directoryStart):

    # print sub directory paths
    for subDirectoryName in directoryNames:
        print(directoryName + slash + subDirectoryName)

    # print file name paths to all file names
    for fileName in fileNames:
        print(directoryName + slash + fileName)

Let us prove my point using memory_profiler, a Python add-on module (which depends on the python-psutil package) by Fabian Pedregosa (the module’s github page). This add-on provides the decorator @profile that allows one to monitor one specific function memory usage. It is extremely simple to use. Let us consider the following program:

import copy
import memory_profiler

@profile
def function():
    x = list(range(1000000))  # allocate a big list
    y = copy.deepcopy(x)
    del x
    return y

if __name__ == "__main__":
    function()

invoking

python -m memory_profiler memory-profile-me.py

prints, on a 64-bit computer

Filename: memory-profile-me.py

Line # Mem usage Increment Line Contents
================================================
4 @profile
5 9.11 MB 0.00 MB def function():
6 40.05 MB 30.94 MB x = list(range(1000000)) # allocate a big list
7 89.73 MB 49.68 MB y = copy.deepcopy(x)
8 82.10 MB -7.63 MB del x
9 82.10 MB 0.00 MB return y

from direct.showbase.ShowBase import ShowBase; s = ShowBase(); s.run()

base.disableMouse(); m=loader.loadModel("models/smiley"); m.reparent_to(base.render); base.camera.set_pos(0, -5, 0); base.camera.look_at(0,0,0)

PP is a python module which provides mechanism for parallel execution of python code on SMP (systems with multiple processors or cores) and clusters (computers connected via network).

It is light, easy to install and integrate with other python software.

PP is an open source and cross-platform module written in pure python.

The most simple and common way to write parallel applications for SMP computers is to use threads. Although, it appears that if the application is computation-bound using 'thread' or 'threading' python modules will not allow to run python byte-code in parallel. The reason is that python interpreter uses GIL (Global Interpreter Lock) for internal bookkeeping. This lock allows to execute only one python byte-code instruction at a time even on an SMP computer.

PP module overcomes this limitation and provides a simple way to write parallel python applications. Internally ppsmp uses processes and IPC (Inter Process Communications) to organize parallel computations. All the details and complexity of the latter are completely taken care of, and your application just submits jobs and retrieves their results (the easiest way to write parallel applications).

Silverware wrote:Py (at least non-compiled Py) is slow as balls for anything serious.
It's perfect for short scripts that need to be quickly cross-platform, because almost all Linux flavors install Py2 by default.

Py however is a good tool to learn to program with, as non-compiled languages tend to be, so if you can't write a Hello World you really should give Python a shot.

Dinosawer wrote:Define serious? We often do numerical mathematical analyses in Python - those are pretty calculation intensive and work just fine

davdav wrote:Openstack is fully written in python...
and it's not a short script but a full cloud management system.

Silverware wrote: Work fine, does not mean work fast
I can do the same numerical work in C or C++ much faster.

Silverware wrote:(or in JS at about the same speed, only with more work involved due to Py having the nice SciPy libs)

Dinosawer wrote:

Silverware wrote: Work fine, does not mean work fast
I can do the same numerical work in C or C++ much faster.

Not if you count in the time it takes you to program it.

Silverware wrote:(or in JS at about the same speed, only with more work involved due to Py having the nice SciPy libs)

Scipy uses built in C++ functions, you aint gonna beat that with JS