Wednesday, January 26, 2005
Useful wxPython info
In an old blog, that I just stumbled upon, Golden spud gives some interesting information about wxPython. Perhaps it is possible to use his technique to change the language used in a GUI without having to restart the application under Windows.
Tuesday, January 11, 2005
Teaching an old Python keyword new tricks
In my last post, I provided some additional thoughts about maintaining Python's pseudocode appearance while adding static typing information. The notation I suggested also allowed for easy inclusion of pre-conditions and post-conditions. However, this came as a cost of adding where as a new keyword to Python. After giving some more thoughts to this idea I realise that a new keyword was not needed at all. This can be seen starting from the following example using the keyword where as introduced before:
01 def gcd(a, b):If we remove the line with where: and change the indentation level, we have essentially valid (today!) Python syntax, but with many (two in this case) lines starting with the keyword assert. If we allow this keyword to introduce the beginning of a bloc of statements, we could then write:
02 where:
03 assert isinstance(a, int)
04 assert isinstance(b, int)
05 '''Returns the Greatest Common Divisor,
06 implementing Euclid's algorithm.
07 Input arguments must be integers.'''
08 while a:
09 a, b = b%a, a
10 return b
01 def gcd(a, b):The idea of a keyword that allows both a bloc structure with a colon, as well as a single line expression is not new: it has been introduced in Python with the addition of list comprehensions. For example, we can have
02 assert:
03 isinstance(a, int)
04 isinstance(b, int)
05 '''Returns the Greatest Common Divisor,
06 implementing Euclid's algorithm.
07 Input arguments must be integers.'''
08 while a:
09 a, b = b%a, a
10 return b
01 for i in range(10):as well as
02 ...
03 ...
a = [i for i in range(10)]With this suggested syntax, pre-conditions can easily be added.
01 def gcd(a, b):Keeping this block structure in mind, we can add type information on return values as follows:
02 assert:
03 isinstance(a, int)
04 isinstance(b, int)
05 a != 0 and b != 0 # fake pre-condition
06 '''Returns the Greatest Common Divisor,
07 implementing Euclid's algorithm.
08 Input arguments must be integers.'''
09 while a:
10 a, b = b%a, a
11 return b
01 def gcd(a, b):as well as adding pre- and post-conditions:
02 assert:
03 isinstance(a, int)
04 isinstance(b, int)
05 return c assert:
06 isinstance(c, int)
07 '''Returns the Greatest Common Divisor,
08 implementing Euclid's algorithm.
09 Input arguments must be integers;
10 return value is an integer.'''
11 while a:
12 a, b = b%a, a
13 return b
01 def gcd(a, b):To move further towards something similar to what I suggested in my previous post, we need to identify, as Guido van Rossum had himself suggested, the statement
02 assert:
03 isinstance(a, int)
04 isinstance(b, int)
05 a != 0 and b != 0 # fake pre-condition
06 return c assert:
07 isinstance(c, int)
08 c != 0 # fake post-condition
09 '''Returns the Greatest Common Divisor,
10 implementing Euclid's algorithm.
11 Input arguments must be integers;
12 return value is an integer.'''
13 while a:
14 a, b = b%a, a
15 return b
isinstance(object, class-or-type-or-tuple)with
object: class-or-type-or-tupleDoing so allows us to rewrite the last example as
01 def gcd(a, b):which is essentially what was written in the previous post, but with the replacement of a new keyword (where) by an old one (assert). The general form would be:
02 assert:
03 a: int
04 b: int
05 a != 0 and b != 0 # fake pre-condition
06 return c assert:
07 c: int
08 c != 0 # fake post-condition
09 '''Returns the Greatest Common Divisor,
10 implementing Euclid's algorithm.
11 Input arguments must be integers;
12 return value is an integer.'''
13 while a:
14 a, b = b%a, a
15 return b
01 def foo(...):As this post is already long enough, I will not discuss the interface issue here; the ideas introduced in the previous two posts are easily translated by replacing where by assert everywhere.
02 assert:
. type information and/or
. pre-conditions
. return [...] assert:
. type information and/or
. post-conditions
. '''docstring'''
. ...body...
Sunday, January 09, 2005
Python as pseudo-code and Optional Static Typing
In my last post, I gave a series of examples intended to show how Python's pseudocode syntax could be preserved while adding optional static typing. While I felt that the syntax was self-explanatory (as pseudocode should be), I thought it might be useful to examine in more details the why's and the how's of my suggestion.
Before proceeding further, it might be argued that this is a case of premature optimization: Python does not currently have (optional) static typing so the concept should be discussed first, before implementation details and syntax can be looked at objectively. Yet, one of the strength of Python is its syntax, and many objections (NIMPY as GvR described it) to the proposed addition(s) to the language came from an unease with the suggested syntax.
1. Functions and optional typing information
I will use GvR's version of a Greatest Common Divisor finding function as an example and build from it; the complexity of the examples will increase as we go in an attempt to fully illustrate the suggested syntax. This function is defined as follows:
the function body.
The docstring is between the typing information and the actual code, allowing to better separate visually the two of them. The docstring has been updated as well to inform a potential user
reading the documention as to the particular of this function. I have given some thoughts about including the typing information within the docstring (à la doctest) in order to avoid writing about the type information twice, as in the following:
of the docstring); 3) it doesn't "scale" well with added features like pre-conditions and post-conditions.
2. Pre- and post-conditions
Building on the previous examples, here is how pre- and post-conditions might might be added within the suggested new syntax with, in this case, somewhat artificial conditions (not required by this algorithm).
The post-condition assertion
is an internal verification that the code is correct. It is irrelevant to the documentation which is one more reason to separate it from the docstring, even though such information is sometimes including in docstring. This notation, using the standard assert statement is different from what I suggested in my previous post and respects Python's current syntax.
One can easily imagine that such typing information and conditions might be shared by many functions. Rather than replicating code, it might be possible to define abstract functions, which are functions that have no body, only type information and/or conditions. For example, we could have
I realise that this might be starting to look like a return to past suggestions during the decorator debate. However, given that the optional static typing proposal is new, it should be looked at objectively, without rejecting off-hand proposals that were rejected in a different context.
3. Interfaces
Instead of dealing with functions, in oop we have classes and methods. Classes can implement interfaces, which share some similarities with what we called abstract functions above. Here is how, using the notation we have suggested, we might introduce interfaces in the language. Once again I am using examples suggested by Python's BDFL in his blog.
I suggest using a semi-colon to separate based classes from interfaces for clarity. Thus we could have:
Classes that do not derived from a base class (aka 'old-style') might still be accommodated via
Before proceeding further, it might be argued that this is a case of premature optimization: Python does not currently have (optional) static typing so the concept should be discussed first, before implementation details and syntax can be looked at objectively. Yet, one of the strength of Python is its syntax, and many objections (NIMPY as GvR described it) to the proposed addition(s) to the language came from an unease with the suggested syntax.
1. Functions and optional typing information
I will use GvR's version of a Greatest Common Divisor finding function as an example and build from it; the complexity of the examples will increase as we go in an attempt to fully illustrate the suggested syntax. This function is defined as follows:
I have included an optional docstring which, following Python's normal syntax, is indented at the same level as the function's body. The docstring is intended to be easily extractable for documentation purpose and is intended for human readers only. Suppose that it is required to provide static typing information. Using the notation I used in my previous post, here's how one might write additional syntax information.
01 def gcd(a, b):
02 '''Returns the Greatest Common Divisor,
03 implementing Euclid's algorithm.'''
04 while a:
05 a, b = b%a, a
06 return b
01 def gcd(a, b):The suggested where keyword, followed by a mandatory colon, follows the usual Python syntax of introducing a bloc of code identified by its indentation level. So we now have three structural items at the same indentation level: the static typing information, the docstring, and
02 where:
03 a: int, b: int
04 return c where:
05 c: int
06 '''Returns the Greatest Common Divisor,
07 implementing Euclid's algorithm.
08 Input arguments must be integers;
09 return value is an integer.'''
10 while a:
11 a, b = b%a, a
12 return b
the function body.
The docstring is between the typing information and the actual code, allowing to better separate visually the two of them. The docstring has been updated as well to inform a potential user
reading the documention as to the particular of this function. I have given some thoughts about including the typing information within the docstring (à la doctest) in order to avoid writing about the type information twice, as in the following:
01 def gcd(a, b):However, I find 1) that it is not easier to read; 2) that it would complicate extraction of the docstring for inclusion in a standard documentation (i.e. spaces are significant for only part
02 '''Returns the Greatest Common Divisor,
03 implementing Euclid's algorithm.
04 where:
05 a: int, b: int
06 return c where:
07 c: int'''
08 while a:
09 a, b = b%a, a
10 return b
of the docstring); 3) it doesn't "scale" well with added features like pre-conditions and post-conditions.
2. Pre- and post-conditions
Building on the previous examples, here is how pre- and post-conditions might might be added within the suggested new syntax with, in this case, somewhat artificial conditions (not required by this algorithm).
01 def gcd(a, b):
02 where:
03 a: int, b: int
04 assert a != 0 and b != 0
05 return c where:
06 c: int
07 assert c <= abs(a) and c <= abs(b)
08 '''Returns the Greatest Common Divisor,
09 implementing Euclid's algorithm.
10 Input arguments must be integers,
11 and can not be both zero;
12 return value is an integer.'''
13 while a:
14 a, b = b%a, a
15 return b
The post-condition assertion
07 assert c <= abs(a) and c <= abs(b)
is an internal verification that the code is correct. It is irrelevant to the documentation which is one more reason to separate it from the docstring, even though such information is sometimes including in docstring. This notation, using the standard assert statement is different from what I suggested in my previous post and respects Python's current syntax.
One can easily imagine that such typing information and conditions might be shared by many functions. Rather than replicating code, it might be possible to define abstract functions, which are functions that have no body, only type information and/or conditions. For example, we could have
01 def two_integer_input(i, j): # abstract function: no body
02 where:
03 i: int, j: int
04 '''Accepts only two integers as input.'''
05
06
07 def _gcd_return_info(a, b): # abstract function: no body
08 where:
09 return c where:
10 c: int
11 assert c <= abs(a) and c <= abs(b)
12
13
14 def gcd(a, b):
15 where:
16 two_integer_input(a, b)
17 assert a != 0 and b != 0
18 _gcd_return_info(a, b)
19 '''Returns the Greatest Common Divisor,
20 implementing Euclid's algorithm.
21 Input arguments must be integers,
22 and can not be both zero;
23 return value is an integer.'''
24 while a:
25 a, b = b%a, a
26 return b
I realise that this might be starting to look like a return to past suggestions during the decorator debate. However, given that the optional static typing proposal is new, it should be looked at objectively, without rejecting off-hand proposals that were rejected in a different context.
3. Interfaces
Instead of dealing with functions, in oop we have classes and methods. Classes can implement interfaces, which share some similarities with what we called abstract functions above. Here is how, using the notation we have suggested, we might introduce interfaces in the language. Once again I am using examples suggested by Python's BDFL in his blog.
01 interface I:
02 def foo(x):
03 where:
04 x: int
05 x > 0
06 return r where:
07 r: str
08
09 class C(object; I): # derived from object; implements I
10 def foo(self, x):
11 return str(x)
I suggest using a semi-colon to separate based classes from interfaces for clarity. Thus we could have:
01 interface I1(I2, I3): # derived from I2 and I3, both interfacesFor a class that does not implement interfaces, the following statements would be equivalent
02 def foo(a: t1, b: t2):
03 where:
04 a: t1, b: t2
05 return c where:
06 c: t3
07
08 class C(C1, C2; I1): # derived from C1, C2; implements I1
09 def foo(a, b):
10 return a+b
class C(object): # preferred
# and
class C(object;): # allowed
Classes that do not derived from a base class (aka 'old-style') might still be accommodated via
class C(; I1, I2)although presumably they will have disappeared from the language by the time static typing information will have been implemented.
Friday, January 07, 2005
"where" keyword and Python as pseudo-code
There has been much discussion lately about what is now a series of blogs by Guido van Rossum (see Optional Static Typing -- Stop the Flames! for the latest discussion) about optional static typing in Python and related extensions to the language. A recent post
comp.lang.python by Andrey Tatarinov about using where as a new keyword in the absence of anonymous functions gave me some ideas about how such a new keyword could be useful in rendering pythonic the addition of optional static typing. However, I do not use where in the same context as Tatarinov.
Python is often described as executable pseudo-code. Therefore, rather than explaining in words my ideas, I will let the code (examples taken from Python's BDFL blogs) speak for itself. Note that the amount of code versus type declarations is not really representative of real life in the following examples. I also deliberately did not add blank lines, which could have made this more readable.
1. Optional typing.
2. Optional typing with pre- and post- conditions.
3. Interfaces
4. More interfaces
5. Formerly anonymous functions.
6. Formerly anonymous functions with typing information
7. Other optional typing style, meant to be equivalent to above
If you "grok" the above, I have made my point. If not, feel free to comment!
comp.lang.python by Andrey Tatarinov about using where as a new keyword in the absence of anonymous functions gave me some ideas about how such a new keyword could be useful in rendering pythonic the addition of optional static typing. However, I do not use where in the same context as Tatarinov.
Python is often described as executable pseudo-code. Therefore, rather than explaining in words my ideas, I will let the code (examples taken from Python's BDFL blogs) speak for itself. Note that the amount of code versus type declarations is not really representative of real life in the following examples. I also deliberately did not add blank lines, which could have made this more readable.
1. Optional typing.
def gcd(a, b):
where:
a: int, b: int
return c where:
c: int
while a:
a, b = b%a, a
return b
2. Optional typing with pre- and post- conditions.
def gcd(a, b):
where:
a: int, b: int
a > 0, b > 0
return c where:
c: int
c > 0
c <= a and c <= b
while a:
a, b = b%a, a
return b
3. Interfaces
interface I:
def foo(x):
where:
x: int
x > 0
return r where:
r: str
class C(object; I): # derived from object; implements I
def foo(self, x):
return str(x)
4. More interfaces
interface I1(I2, I3):
def foo(a: t1, b: t2):
where:
a: t1, b: t2
return c where:
c: t3
class C(C1, C2; I1): # derived from C1, C2; implements I1
def foo(a, b):
return a+b
5. Formerly anonymous functions.
list_of_powers = [ powers(x) for x in my_list]:
def powers(x):
return (x, x*x, x*x*x)
6. Formerly anonymous functions with typing information
list_of_powers = [ powers(x) for x in my_list]:
def powers(x):
where:
x: int
return (a, b, c) where:
a: int, b: int, c: int
return (x, x*x, x*x*x)
7. Other optional typing style, meant to be equivalent to above
def type_safe_gcd(a, b):
where:
a: int, b: int
return c where:
c: int
def gcd(a, b):
where type_safe_gcd(a, b);
while a:
a, b = b%a, a
return b
If you "grok" the above, I have made my point. If not, feel free to comment!
Sunday, January 02, 2005
Avoiding spaghetti code
Note to myself:
functions/methods should either
1) change some internal attributes;
2) return a value/object
3) change some attribute of an object created by their parent class.
They should not directly change the state of some objects that calls them. I had the following situation:
X created Y.
X created Z.
A method of X called a method of Z which was then changing the state of an attribute of Y through a pointer reference created for that purpose. Ugly.... and difficult to maintain.
functions/methods should either
1) change some internal attributes;
2) return a value/object
3) change some attribute of an object created by their parent class.
They should not directly change the state of some objects that calls them. I had the following situation:
X created Y.
X created Z.
A method of X called a method of Z which was then changing the state of an attribute of Y through a pointer reference created for that purpose. Ugly.... and difficult to maintain.
wxPython problem solved
Well, I did manage (with some help) to solve my wxPython problems. I'll update this post to indicate the solution soon.