Currently showing entries with the tag: love
|
page 1 of 1
|
10 Things This Skeptic Loves About Python's Syntax
August 15, 2007 • 9:38AM • permalink
First, a note...
Anyone that has worked with me in the past will know what a skeptic I am about new programming languages. I use a lot of different languages (new and old) and operating systems (mostly to fit the constraints of my client's environments) but I prefer to work in C++/C# and in Microsoft Visual Studio. I am always reading one tech book or another, so as a change of pace I started doing some random reading about Python.
While I still prefer C++/C#, the seamless integration of Python with C is very appealing. There is no question that Python is a RAD programming language, especially when looking over the syntax. I wanted to mention ten of my favorites, although there are many more than this - and I've just started learning it! I'm going to give very simple explanations to save space, but I suggest if you find the below interesting that you consider learning Python.
(Please note that the below are in no specific order.)
Divide-and-Floor Operator //
This is an additional divide operator that is used to truncate the entire decimal portion. This is a full truncation of the number with no rounding involved. Since this is a fairly common operation when dealing with floating-point numbers, it's nice to have a simple operator to handle it.
print 10.0 / 3
print 10.0 // 3
x = 10.0
x //= 3
print x
Multiple Assignments In One Statement
Why waste space and time when you need to get things done? Python allows you to perform multiple actions in one statement through use of a comma. Items on either end of the equals sign are indexed in order, as seen here:
x, y = 1, 2
print x + y
increment, decrement = x + y, x - y
print increment, decrement
Scope Delimiters
Python takes a very unique way of delimiting blocks of code: by using whitespace. Lines of code with the same indentations (after the start of a conditional block of code or other scoped construct) are considered part of the same block.
if x > 3:
print 'this is inside the if-statement'
print 'this is too!'
print 'this is executed regardless of whether x is greater than 3'
sprintf Operator %
StringBuilder.AppendFormat is probably one of the .NET functions that I use the most. At 26 letters, even with Intellisense, it's a handful.
Python has a much simpler way of doing the same thing:
print "I eat about %0.2f times every %d days" % (123.456789, 10)
Use of the else Keyword with Loops
Python allows you to append an else clause to both while and for loops that always execute when a break clause is not executed inside the conditional block.
In many situations this allows for the elimination of some branching logic, in addition to allowing developers to remove an additional variable, in many cases, that would only serve to act as a flag for whether or not the intended case executed.
A common example is to implement simple search functionality:
search_number = 699
for i in range(1, 1000):
if (i == search_number):
print 'your number was found'
break
else:
print 'your number was not found'
search_number = 10000
for i in range(1, 1000):
if (i == search_number):
print 'your number was found'
break
else:
print 'your number was not found'
Slice Operator [:]
Nevermind taking a portion of a string, this technique can also be used to take a subset of a list or a dictionary (Python's version of arrays/vectors and hashtables). The example below uses a list.
L = [1, 2, 3, 4, 5, 6]
print L[2:4]
print L[2:]
print L[:3]
print L[:]
Step Operator [::]
This is really an additional parameter to the Slice Operator, but this determines the direction and quantity of the index increment (or decrement), as if iterating through the list. It's best to show with an example or three:
L = [1, 2, 3, 4, 5, 6]
print L[::-1]
print L[::3]
print L[::-2]
Note that this can (obviously) be combined with the Slice Operator above to change the rate of index through sublists. As a continuation from the example above:
print L[:1:-1]
Optional Function Arguments (* and ** Operators)
The whole reason you can use a different programming language in a given situation is the fundamental rule that you should always use the right tool for the right job. In Python, these are known as Arbitrary Function Arguments.
Python gives developers several options (and several combinations of the options) that can be used when using function overloading with optional arguments.
The first is the * operator which returns the remaining arguments of a function in a Python data type known as a tuple.
def SomeFunction(first_arg, *other_args):
print len(other_args)
SomeFunction('test', 'test2', 'test3', 4)
The other operator is the **operator which performs the same action, only returning a dictionary instead of a tuple. This only works with named arguments and will automatically map the argument name to the requested value.
def SomeFunction(**the_args):
print the_args
SomeFunction(a=1, b=2, c=3, d=4, e=5, f=6)
Multiple Comparison Operators
Unlike C and most other languages, Python allows you to chain the various comparison operations together to form complex expressions, just like in algebra. Note that like other boolean expressions, these are short-circuited to increase performance.
a = 1
b = 3
c = 5
print a < b < c
print c < b < a
Stop Reinventing the Wheel
Finally, Python takes many higher level constructs and implementations that have been propagated into multiple languages over the years.
Three (out of more than I can easily count) are shown below: simple string duplication, (theoretically) infinitely sized numbers and the Complex number type. These are shown very briefly below:
print "*" * 20
print 2 ** 100
x = 1 + 3j
y = 1 - 3j
print x * y
If you've ever programmed in any other language, you can see that Python has an extremely unique syntax. It is very unique, but surprisingly intuitive once you've begun to use it. The above is only a small example of how Python syntax varies from other languages. Now, I finally understand what people mean when they refer to Python code as being very "un-Python-like". Since Python supports most of the basic constructs of other languages, it's very easy to do most actions one of two ways: the normal way and the Python way.
Anyone that has worked with me in the past will know what a skeptic I am about new programming languages. I use a lot of different languages (new and old) and operating systems (mostly to fit the constraints of my client's environments) but I prefer to work in C++/C# and in Microsoft Visual Studio. I am always reading one tech book or another, so as a change of pace I started doing some random reading about Python.
While I still prefer C++/C#, the seamless integration of Python with C is very appealing. There is no question that Python is a RAD programming language, especially when looking over the syntax. I wanted to mention ten of my favorites, although there are many more than this - and I've just started learning it! I'm going to give very simple explanations to save space, but I suggest if you find the below interesting that you consider learning Python.
(Please note that the below are in no specific order.)
Divide-and-Floor Operator //
This is an additional divide operator that is used to truncate the entire decimal portion. This is a full truncation of the number with no rounding involved. Since this is a fairly common operation when dealing with floating-point numbers, it's nice to have a simple operator to handle it.
print 10.0 / 3
#prints 3.3333333333333335
print 10.0 // 3
#prints 3.0
x = 10.0
x //= 3
print x
#prints 3.0
Multiple Assignments In One Statement
Why waste space and time when you need to get things done? Python allows you to perform multiple actions in one statement through use of a comma. Items on either end of the equals sign are indexed in order, as seen here:
x, y = 1, 2
print x + y
#prints 3
increment, decrement = x + y, x - y
print increment, decrement
#prints 3, -1
Scope Delimiters
Python takes a very unique way of delimiting blocks of code: by using whitespace. Lines of code with the same indentations (after the start of a conditional block of code or other scoped construct) are considered part of the same block.
if x > 3:
print 'this is inside the if-statement'
print 'this is too!'
print 'this is executed regardless of whether x is greater than 3'
sprintf Operator %
StringBuilder.AppendFormat is probably one of the .NET functions that I use the most. At 26 letters, even with Intellisense, it's a handful.
Python has a much simpler way of doing the same thing:
print "I eat about %0.2f times every %d days" % (123.456789, 10)
#prints I eat about 123.46 times every 10 days
Use of the else Keyword with Loops
Python allows you to append an else clause to both while and for loops that always execute when a break clause is not executed inside the conditional block.
In many situations this allows for the elimination of some branching logic, in addition to allowing developers to remove an additional variable, in many cases, that would only serve to act as a flag for whether or not the intended case executed.
A common example is to implement simple search functionality:
search_number = 699
for i in range(1, 1000):
if (i == search_number):
print 'your number was found'
break
else:
print 'your number was not found'
#prints your number was found
search_number = 10000
for i in range(1, 1000):
if (i == search_number):
print 'your number was found'
break
else:
print 'your number was not found'
#prints your number was not found
Slice Operator [:]
Nevermind taking a portion of a string, this technique can also be used to take a subset of a list or a dictionary (Python's version of arrays/vectors and hashtables). The example below uses a list.
L = [1, 2, 3, 4, 5, 6]
#a (0-based) list
print L[2:4]
#prints [3, 4]
print L[2:]
#prints [3, 4, 5, 6]
print L[:3]
#prints [1, 2, 3]
print L[:]
#prints [1, 2, 3, 4, 5, 6]
Step Operator [::]
This is really an additional parameter to the Slice Operator, but this determines the direction and quantity of the index increment (or decrement), as if iterating through the list. It's best to show with an example or three:
L = [1, 2, 3, 4, 5, 6]
#a (0-based) list
print L[::-1]
#prints [6, 5, 4, 3, 2, 1]
print L[::3]
#prints [1, 4]
print L[::-2]
#prints [6, 4, 2]
Note that this can (obviously) be combined with the Slice Operator above to change the rate of index through sublists. As a continuation from the example above:
print L[:1:-1]
#prints [6, 5, 4, 3]
Optional Function Arguments (* and ** Operators)
The whole reason you can use a different programming language in a given situation is the fundamental rule that you should always use the right tool for the right job. In Python, these are known as Arbitrary Function Arguments.
Python gives developers several options (and several combinations of the options) that can be used when using function overloading with optional arguments.
The first is the * operator which returns the remaining arguments of a function in a Python data type known as a tuple.
def SomeFunction(first_arg, *other_args):
print len(other_args)
SomeFunction('test', 'test2', 'test3', 4)
#prints 3
The other operator is the **operator which performs the same action, only returning a dictionary instead of a tuple. This only works with named arguments and will automatically map the argument name to the requested value.
def SomeFunction(**the_args):
print the_args
SomeFunction(a=1, b=2, c=3, d=4, e=5, f=6)
#prints {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5, 'f': 6}
Multiple Comparison Operators
Unlike C and most other languages, Python allows you to chain the various comparison operations together to form complex expressions, just like in algebra. Note that like other boolean expressions, these are short-circuited to increase performance.
a = 1
b = 3
c = 5
print a < b < c
#prints True
print c < b < a
#prints False
Stop Reinventing the Wheel
Finally, Python takes many higher level constructs and implementations that have been propagated into multiple languages over the years.
Three (out of more than I can easily count) are shown below: simple string duplication, (theoretically) infinitely sized numbers and the Complex number type. These are shown very briefly below:
#1) Simple String Extension
print "*" * 20
#prints ********************
#2) Infinitely Sized Numbers (based on Memory Limits)
#Note that ** is the exponent operator in Python.
#Normally 2 ** 64 is the long type limit in most systems.
print 2 ** 100
#prints 1267650600228229401496703205376L
#3) Complex Number Type
x = 1 + 3j
y = 1 - 3j
print x * y
#prints (10+0j)
If you've ever programmed in any other language, you can see that Python has an extremely unique syntax. It is very unique, but surprisingly intuitive once you've begun to use it. The above is only a small example of how Python syntax varies from other languages. Now, I finally understand what people mean when they refer to Python code as being very "un-Python-like". Since Python supports most of the basic constructs of other languages, it's very easy to do most actions one of two ways: the normal way and the Python way.
1 comment
|
page 1 of 1
|
