Man, there's too much to do and note. Logging some stuff to investigate later…

• 2011 PyCon tutorials announcement further details at the tutorial list.
• They mention using IPython enhanced shell. Hmm.
• Python Tools for Visual Studio 2010.
• Python Performance Tips at the Python wiki.
• Of course, there's getting Python running under Xampp.
• There's A comparison of CubicWeb, Django, Pyramid, Web.py, Web2py, and Zope 2
• Look into the microframework Flask. Here's a tutorial on making a blog with it. Consider flask with gunicorn and nginx.
• dataset, an abstraction layer above relational databases.
• docopt for a stupidly easy and correct command-line interface description language.
• Best practices by Vladimir Keleshev.
• You can ask a new-style class for its .__subclasses__() It uses weak references. Look at this interesting example with a child class inside a method.
• A Power Point deck by Alex Martelli describing Dependency Injection vs. Template Method (override base method) vs. Monkey Patching.
• Hidden Features of Python at StackOverflow
• Parallelism in one line

Would be nice to create a binary search in text files in Python. Maybe based on an answer deep in Reading Huge File in Python.

This Explanation of Python "Yield" also mentions (at the bottom) explanations for decorators and metaclasses.

Would be good to experiment with least-squares polynomial fitting in Python.

Looks like I should dive into:

• NumPy
• Pandas
• IPython. (As seen above.)

You have some template files in svn:

/Code/python_templates/trunk/make_standalone_application.bat
/Code/python_templates/trunk/setup.py
/Code/python_templates/trunk/template_cron_job.py
/Code/python_templates/trunk/template_gui_app.py
/Code/python_templates/trunk/template_gui_app_with_worker_thread.py

Python has a For/Else keyword that should have been called, “nobreak.”

From an old note-to-self…

import operator
 
rows.sort(key=operator.itemgetter(4))
# or
rows.sort(lambda x, y : x[4] == y[4] and cmp(x[2],y[2]) or cmp(x[4], y[4]))

…not like I could just find the same info at the Python wiki or anything.

Remember when you lost a couple of hours thinking that the following line created a list of objects.

    l = [Obj()] * n

It doesn't. It creates a list of references to one object.

What you meant to write was this:

    l = [Obj() for _ in range(n)]

Newer way, use module fileinput. Older way:

if __name__=='__main__':
    if len(sys.argv) < 2:
        # Process lines coming from stdin.
        while 1:
            line = sys.stdin.readline()
            if not line:
                break
            my_process_line(line.rstrip())
    else:
        # Process lines of the files specified.
        for fname in sys.argv[1:]:
            if not os.path.exists(fname):
                treat_argument_as_literal(fname)
                continue
            with open(fname, 'r') as f:
                while 1:
                    line = f.readline()
                    if not line:
                        break
                    my_process_line(line.rstrip())

Making code more beautiful with "with". (Also mentions yield.)

Raymond Hettinger likes Robert Kern's line_profiler much better than profile and cProfile.

Here it is: line_profiler and kernprof

import timeit
 
def Use_a():
    pass
 
def Use_b():
    pass
 
def Run_all_tests():
    my_setup()
    Use_a()
    Use_b()
 
if __name__ == '__main__':
 
#    t = timeit.timeit( 'Run_all_tests()', 'from __main__ import Run_all_tests', number=1 )
#    print dir( t )
#    print t
 
    t = timeit.Timer( 'Run_all_tests()', 'from __main__ import Run_all_tests' )
    print t.timeit()

When diving in, cProfile may come in handy.

import cProfile
 
def my_function():
    # Complicated stuff
    pass
 
if __name__ == '__main__':
    cProfile.run("my_function()")

Line up columns

data = '''\
234 127 34 23 45567
23 12 4 4 45
23456 2 1 444 567'''
 
# Split input data by row and then on spaces
rows = [line.strip().split(' ') for line in data.split('\n')]
 
# Reorganize data by columns
cols = zip(*rows)
 
# Compute column widths by taking maximum length of values per column
col_widths = [max(len(value) for value in col) for col in cols]
 
# Create a suitable format string
format = ' '.join(['%%%ds' % width for width in col_widths])
 
# Print each row using the computed format
for row in rows:
  print format % tuple(row)

Which outputs:

  234 127 34  23 45567
   23  12  4   4    45
23456   2  1 444   567

Also, here's a nice summary of string formatting in Python.

class A:
    """ Old, obsolete. """
    def __init__(self):
        self.__m_x = 0
 
    def getx(self):
        return self.__m_x
 
    def setx(self, x):
        if x < 0: x = 0
        self.__m_x = x
 
    x = property(getx, setx)
 
class B:
    """ Old; very small, was for for multitudes of objects. """
    __slots__ = ["__m_x"]
    def __init__(self):
        self.__m_x = 0
 
    def getx(self):
        return self.__m_x
 
    def setx(self, x):
        if x < 0: x = 0
        self.__m_x = x
 
    x = property(getx, setx)        
 
class C(object):
    """ New, recommended. """
    def __init__(self):
        self.__x = 0
 
    def getx(self):
        return self.__x
 
    def setx(self, x):
        if x < 0: x = 0
        self.__x = x
 
    x = property(getx, setx)

Evan Fosmark has a filelock module. But here's a quick and dirty implementation of a lock that uses the current file:

import os
import fcntl
import inspect
# Maybe use os.path.abspath(__file__) ?
with open(os.path.abspath inspect.getfile(inspect.currentframe())), 'r') as f:
    try:
        fcntl.flock(f, fcntl.LOCK_EX)
        call_that_cannot_be_concurrent()
    finally:
        fcntl.flock(f, fcntl.LOCK_UN)

• Use Queue and threading's Thread
• Use threading and store results in a pre-allocated list. Then use Queue for lots of URLs.
• Use concurrent.futures' ThreadPoolExecutor and map().
• Or, use the doc's ThreadPoolExecutor Example.
• And, as mentioned in Parallelism in One Line, multiprocessing.dummy's Pool and its own map().

import itertools
 
def fib(n):
    """Print a Fibonacci series up to n."""
    a, b = 0, 1
    while True:
        yield a
        b = a + b
        yield b
        a = a + b
 
if __name__ == '__main__': 
    for x in itertools.islice(fib(), 5):
        print x
 
#    for i in range( 5 ):
#        print i, fib( i )

sudo apt-get install graphviz

    # Read `nm` output
    output = subprocess.check_output(['nm', '--demangle', entry.path]).decode('utf-8')
    for line in output.split('\n'):
        if 'Singleton' in line:
 
    # Make a .dot file
    with open(filename + '.dot', 'w') as file:
        file.write('digraph {\n')
        for f, destinations in self.graph.items():
            for d in destinations:
                file.write(f'  "{f}" -> "{d}"\n')
 
 
def create_png_image(filename):
    with open(filename + '.png', 'wb') as fout:
        p1 = subprocess.run(['dot', filename + '.dot', '-Tpng'], stdout=fout)

TODO Link to my tips from LiveJournal and GMail, and why I chose which timing modules.