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Links on all kinds of things

Posted: Sunday, 2020-02-02 17:41 | Tags: Programming, Python, MachineLearning

Some more links in particular about ML & Python topics

Source: rosiejuliet

CourseDuck has a really nice overview of free Machine Learning tutorials with ratings & pros/cons; spanning YouTube, Coursera and so forth. Definetely worth checking out!

Codi looks like the "iPython Notebook in VIM" I always wanted, did not yet take the time to install it but its number one of my list of things to try.

Altair is yet another Python data visualazition lib (think Matplot and the like). What positively sets it apart though is that it has a really nice declarative language which is particularly interesting for more explorative work.

Broot gives you an overview of a directory tree in your shell, offering search (similar to fzf & thelike), cd'ing, moving files around, and seeing what takes space. Some overlap/competation to ranger it seems?

Some random-ish Python Links

Posted: Saturday, 2019-06-08 22:58 | Tags: Programming, Python

Quick notes of some Python-related links of various topics I thought I share!

Source: aoifecahill

Random stuff

Awesome collection of all kinds of robotic / driving related algorithms incl. Python implementations:


These days there are some damn cool things out there to build up your Unixoid (development) environment. This is a medium-sized elaboration on the stuff I like.

Spoilers: Including an editor that can be considered better than VIM in some regards and the single most awesome shell there is (no, not ZSH). I structured it a bit though so you can skip through the parts that are boring to you :-).


Python notes

Posted: Sunday, 2017-01-22 11:02 | Tags: Programming, Python

I've been watching some PyCon talks online lately and stumbled across a few interesting things, these are mostly notes for myself but feel free to consider them useful ;-)


What kind of GUI-Editor for grail?

Posted: Friday, 2009-11-27 14:13 | Tags: Grail, Atlantis, Python, Programming

I'm currently thinking about how the future GUI for grail will look. Basically there are 2 approaches that I would say are worth considering at the moment:

  • Step-by-step fix Atlantis to become the new grail editor. The first step would be to have it generate lua code instead of D code, in the future it would be extended with a lua editor component etc...
  • As grail is basically starting from scratch this would be the perfect opportunity to include some editor capabilities directly into grail.
    • (-) There would never be a code-editing component, I would keep the additional GUI elements to a bare minimum. I guess the control would be over a one-line shell-like command line at the bottom where you enter commands like "create polygon" or something. No checkboxes, no dialogs.
    • (+) Having the editor directly combined with the engine allows some interesting things like running parts of the game while working on it. Although I must confess this point is very weak: Due to the lua scripting engine one could realise similar behaviour by sending lua commands to the runtime via a network socket or similar approaches.
    • (+) Another good thing would be: Having a command line and the capabilities for displaying polygons etc... inside the engine allows for advanced debugging utilities, that could be really cool.
    • (-) Probably this approach would mean more work :(

Comments welcome!

I guess this is a common trap. I personally am python coder for years now and still, from time to time I run into it. As the syntax for it is very concise you might sometimes be tempted to give default values for members in a classes definition. Code says more then thousand words. This works fine:

class Foo(object):
  x = 7

f1 = Foo()
f2 = Foo()

f2.x = 42

print f1.x # prints 7
print f2.x # prints 42

Now say we have something else for x, say it will contain a list most of the time and thus by default it should be the empty list:

class Foo(object):
  x = []

  def append(self, y): self.x.append(y)

f1 = Foo()
f2 = Foo()

f1.append("Take evasive action!")

print f1.x # prints ["Take evasive action!"]
print f2.x # prints ["Take evasive action!"] <- WTF?

The somewhat experienced programmer immediately sees what happens. Let's look at this step by step.

What does python do when you access f1.x?

It first looks if the object has a member x, if it can not find any, it accesses the class member x.

So what exactly happens in the first example?

Directly after construction the objects f1 and f2 point both to Foo.x that is at the same x. Thes with f2.x = 42 we add a member x to the object f2 so that we have a situation like the following:

  • Foo.x points to the value 7
  • f1 does not have a member x, so access to f1.x will be redirected to Foo.x
  • f2.x points to the value 42

Note that you never "change" an integer in python, you can only reference a different integer, ie integers are immutable.

What exactly happens in the second example?

As in the first example, after construction, both f1 and f2 don't even have a member x, they just redirect to Foo.x. Whats different here is that in this example we don't ever create an x-member in one of the objects!

Instead of integers, lists are mutable. In our append call, we actually change Foo.x instead of creating a new member. As both f1 and f2 still pass through to Foo.x, we see the change on both objects.

Yet another trap!

Now you might think "Okay, then I do it like this:"

class Foo(object):
  def __init__(self, x=[]):
    self.x = x

f1 = Foo()
f2 = Foo()

But this is basically the same problem, with a slightly different background. The default value for x you type there is only created once. So what you do here would be creating members f1.x and f2.x but still having them point to the same object which leads to the same unwanted result.

So what should I do?

Don't use this as a way for giving default values for object members. Instead do something like:

class Foo(object):
  def __init__(self, **kwargs):
    self.x = kwargs.get('x', [])

This way you have the default value defined inside __init__, which guarantees that each defaultly-initialized object gets a different "[]".

Depending on your actual needs you might also do something like:

class Foo(object):
  def __init__(self, x=None):
    self.x = x
    if self.x is None: self.x = []

Or you could copy every received value:

class Foo(object):
  def __init__(self, x=[]):
    self.x = x[:] # assumes, passed x is always a list!

For those of you that are still very new to python: Try to always keep one eye on what references what. Be aware that everything in python has reference semantics although for immutable values that can't lead to this problem (and in lots of situations this "feels" like value semantic). Also note that my approaches are far from perfect too. And: Don't use any of that code if you do not fully understand it, play around with everything in the python interpreter, you can learn a lot of things there.