Tags: python project structure recommended
Dec. 8, 2011, 8:53 a.m.

• >>> foo = [2, 18, 9, 22, 17, 24, 8, 12, 27]
 >>> 
 >>> print filter(lambda x: x % 3 == 0, foo)
   

  [18, 9, 24, 12, 27]

   >>> 
 >>> print map(lambda x: x * 2 + 10, foo)
   

  [14, 46, 28, 54, 44, 58, 26, 34, 64]

   >>> 
 >>> print reduce(lambda x, y: x + y, foo)
   

  139

• import commands
 >>> 
 >>> mount = commands.getoutput('mount -v')

Tags: lambda python filter map reduce
Dec. 8, 2011, 8:35 a.m.

Tags: checking spell python
Dec. 8, 2011, 8:32 a.m.

Tags: ebooks programming Free books javascript python perl haskell erlang
Dec. 8, 2011, 8:25 a.m.

"Pyjon.Reports is a module bridging z3c.rml, genshi and pypdf together to provide a simple mean of creating templated pdf documents in python."

Tags: opensource python reports pdf templates programming development libraries
Dec. 8, 2011, 8:24 a.m.

WF, single SW

Tags: xxxswf flash malicious analysis tool python
Dec. 8, 2011, 8:17 a.m.

Tags: python
Dec. 8, 2011, 8:05 a.m.

Tags: mathematics python math science scipy code tutorial
Dec. 8, 2011, 8 a.m.

Tags: python tutorials decorator
Dec. 8, 2011, 7:27 a.m.

Tags: espeak python
Nov. 20, 2011, 3:59 a.m.

I have a Python extension written in C and I wonder if I should use the file extension DLL or PYD under Windows. (And what would I use in Linux?)

Are there any differences (besides the filename)?

I found an unofficial article. Is this the secret of pyc? Why can't I find any official article on this topic?

From what I could figure out, it is not very easy to assign default values to properties in the bulkloader.yaml file. I learned that one way to set default values is to write your own function:

 - property: status
      external_name: status
      import_transform: extrabulkloadfunctions.staticvalue(int)

So I modified the transform.none_if_empty(int) function so that it returns the string 'in queue' instead of None.

def staticvalue(fn):

  def wrapper(value):
    if value == '' or value is None:
      return 'in queue'
    return fn(value)

  return wrapper

I was wondering though, since input_transform only accepts a function, whether it would be possible to pass in a default value so that I don't have to write a new function for every single kind of default value I want to pass in. I.E:

import_transform: extrabulkloadfunctions.staticvalue("default A")
import_transform: extrabulkloadfunctions.staticvalue("default B")

etc.

Thanks!

my troubles with ConfigParser continue. It seems it doesn't support Unicode very well. The config file is indeed saved as UTF-8, but when ConfigParser reads it it seems to be encoded into something else. I assumed it was latin-1 and I thougt overriding optionxform could help:

-- configfile.cfg -- 
[rules]
Häjsan = 3
☃ = my snowman

-- myapp.py --
# -*- coding: utf-8 -*-  
import ConfigParser

def _optionxform(s):
    try:
        newstr = s.decode('latin-1')
        newstr = newstr.encode('utf-8')
        return newstr
    except Exception, e:
        print e

cfg = ConfigParser.ConfigParser()
cfg.optionxform = _optionxform    
cfg.read("myconfig")

Of course, when I read the config I get:

'ascii' codec can't decode byte 0xc3 in position 0: ordinal not in range(128)

I've tried a couple of different variations of decoding 's' but the point seems moot, since it really should be a unicode object from the beginning. After all, the config file is UTF-8? I have confirmed that's something is wrong in the way ConfigParser reads the file by stubbing it out with this DummyConfig class. If I use that then everything is nice unicode, fine and dandy.

-- config.py --
# -*- coding: utf-8 -*-                
apa = {'rules': [(u'Häjsan', 3), (u'☃', u'my snowman')]}

class DummyConfig(object):
    def sections(self):
        return apa.keys()
    def items(self, section):
       return apa[section]
    def add_section(self, apa):
        pass  
    def set(self, *args):
        pass

Any ideas what could be causing this or suggestions of other config modules that supports Unicode better are most welcome. I don't want to use sys.setdefaultencoding()!

Doxygen get me docs similarly to

http://www.stack.nl/~dimitri/doxygen/examples/pyexample/html/classpyexample_1_1PyClass.html

But I want to see Functions with parameters similarly to c/c++.

Is there some settings for that?

I have a numpy array that I would like to share between a bunch of python processes in a way that doesn't involve copies. I create a shared numpy array from an existing numpy array using the sharedmem package.

import sharedmem as shm
def convert_to_shared_array(A):
    shared_array = shm.shared_empty(A.shape, A.dtype, order="C")
    shared_array[...] = A
    return shared_array

My problem is that each subprocess needs to access rows that are randomly distributed in the array. Currently I create a shared numpy array using the sharedmem package and pass it to each subprocess. Each process also has a list, idx, of rows that it needs to access. The problem is in the subprocess when I do:

#idx = list of randomly distributed integers

local_array = shared_array[idx,:]

# Do stuff with local array

It creates a copy of the array instead of just another view. The array is quite large and manipulating it first before shareing it so that each process accesses a contiguous range of rows like

local_array = shared_array[start:stop,:]

takes too long.

Question: What are good solutions for sharing random access to a numpy array between python processes that don't involve copying the array?

The subprocesses need readonly access (so no need for locking on access).

I am working on creating a full mesh as per user inputs with weights, other parameters associated to each edge. As of now, I have a naive implementation of it.

import sys
weit = input("Enter Number of Weights: ")
int(weit)
for i in range(0,weit):
    print "Enter details for weit ",i+1
    source=int(input("Enter source:"))
    destination=int(input("Enter Destination:"))
    weight=int(input("Enter Weight:"))
    param=int(input("Enter Param:"))

With the graph data I have collected, I will design a bin packing algorithm. Is there a better way to create the Full Mesh as per user inputs in Python.

EDIT 1:

import sys
import networkx as nx
i_nodes=input("Enter number of nodes")
print "Graph Creation"
G=nx.complete_graph(i_nodes)

Any idea, about how to add user input weights and other parameter values to each bidirectional edge to a complete graph in Networkx?

I'm pretty new to Python, and what makes me mad about my problem is that I feel like it's really simple.I keep getting an error in line 8. I just want this program to take the numbers the user entered and print the largest and smallest, and I want it to cancel the loop if they enter negative 1.

"'int' object is not iterable" is the error.

print "Welcome to The Number Input Program."

number = int(raw_input("Please enter a number: "))

while (number != int(-1)):
    number = int(raw_input("Please enter a number: "))

high = max(number)
low = min(number)

print "The highest number entered was ", high, ".\n"
print "The lowest number entered was ", low, ".\n"

raw_input("\n\nPress the enter key to exit.")

It seems like you can use both '''comments...''' and """comments...""" for multi-line comments. Is there any substantive difference between the two, or is it just a matter of preference?

given the > 4gb file myfile.gz, I need to zcat it into a pipe for consumption by Teradata's fastload. I also need to count the number of lines in the file. Ideally, I only want to make a single pass through the file. I use awk to output the entire line ($0) to stdout and through using awk's END clause, writes the number of rows (awk's NR variable) to another file descriptor (outfile).

I've managed to do this using awk but I'd like to know if a more pythonic way exists.

#!/usr/bin/env python
from subprocess import Popen, PIPE
from os import path

the_file = "/path/to/file/myfile.gz"

outfile = "/tmp/%s.count" % path.basename(the_file)
cmd = ["-c",'zcat %s | awk \'{print $0} END {print NR > "%s"} \' ' % (the_file, outfile)]
zcat_proc = Popen(cmd, stdout = PIPE, shell=True)

The pipe is later consumed by a call to teradata's fastload, which reads from

"/dev/fd/" + str(zcat_proc.stdout.fileno())

This works but I'd like to know if its possible to skip awk and take better advantage of python. I'm also open to other methods. I have multiple large files that I need to process in this manner.

How can i migrate complete App engine python appliaction to appscale which is installed on Amazon EC2.?

i need to migrate All datastore records, Cron Job, taskqueue and index. The Appengine is currently running now.