Summer of code 2017: Python, Pretty printing with pprint in Python

As explained in my Summer of code 2017: Python post I decided to pick up Python

This post is about using pprint to pretty print.


The pprint module provides a capability to “pretty-print” arbitrary Python data structures in a form which can be used as input to the interpreter. The formatted representation keeps objects on a single line if it can, and breaks them onto multiple lines if they don’t fit within the allowed width. Construct PrettyPrinter objects explicitly if you need to adjust the width constraint.

Let's take a look at a dictionary

First we do a regular print

>>> stocks ={
'TGT' :  '51.33', 
'AAPL': '147.48',
'MSFT':  '71.49',
'F'   :  '11.12', 
'INTC':  '34.37'}
>>> print(stocks)
{'TGT': '51.33', 'AAPL': '147.48', 'MSFT': '71.49', 'F': '11.12', 'INTC': '34.37'}

As you can see everything is printed on one line

You can print on multiple lines by using a loop and format

stocks ={
'TGT' :  '51.33', 
'AAPL': '147.48',
'MSFT':  '71.49',
'F'   :  '11.12', 
'INTC':  '34.37'}
>>> for key in stocks:
    print("{key} = {value}".format(key=key, value=stocks[key]))

    
TGT = 51.33
AAPL = 147.48
MSFT = 71.49
F = 11.12
INTC = 34.37

Finally let's take a look at what pprint does

>>> stocks ={
'TGT' :  '51.33', 
'AAPL': '147.48',
'MSFT':  '71.49',
'F'   :  '11.12', 
'INTC':  '34.37'}
>>> from pprint import pprint as pp
>>> pp(stocks)
{'AAPL': '147.48',
 'F': '11.12',
 'INTC': '34.37',
 'MSFT': '71.49',
 'TGT': '51.33'}

As you can see, each key value pair is on one line

What about lists?

A list of integers looks pretty much the same

>>> a =  [ [2],[4], [1]]
>>> print(a)
[[2], [4], [1]]
>>> pp(a)
[[2], [4], [1]]

A list of strings is a different story

>>> l ="SpaceX successfully launches and recovers second Falcon 9 in 48 hours".split()
>>> print(l)
['SpaceX', 'successfully', 'launches', 'and', 'recovers', 'second', 'Falcon', '9',
 'in', '48', 'hours']
>>> pp(l)
['SpaceX',
 'successfully',
 'launches',
 'and',
 'recovers',
 'second',
 'Falcon',
 '9',
 'in',
 '48',
 'hours']
>>> 

As you can see that prints the elements on a separate line

The pprint module also supports some keyword parameters like indent, width, depth, let's take a look at indent

>>> import pprint
>>> l ="SpaceX successfully launches and recovers second Falcon 9 in 48 hours".split()
>>> pp = pprint.PrettyPrinter(indent=6)
>>> 
>>> pp.pprint(l)
[     'SpaceX',
      'successfully',
      'launches',
      'and',
      'recovers',
      'second',
      'Falcon',
      '9',
      'in',
      '48',
      'hours']
>>> 

As you can see the values are moved to the right by 6 spaces

Make sure to look at the examples in the docs online to see what other things pprint supports

 

Summer of code 2017: Python, Day 7 Collections: tuple, str and range

As explained in my Summer of code 2017: Python post I decided to pick up Python

This is officially day 7, today, I looked at Collections in Python, here are my notes

Tuples

 A tuple is a heterogeneous immutable sequence

• A tuple is delimited by parentheses
• Items in a tuple are separated by commas
• Element access in a tuple is done with square brackets and zero-based index t[index]
• To get the number of elements in a tuple, use len(t)
• Iterate over a tuple by using a for loop

Here is an example of what I described above

>>> t = ("Denis", "looks", "at", "tuples", 1, 66.100,5)
>>> len(t)
7
>>> t[2]
'at'
>>> t[6]
5
>>> for item in t:
 print(item)

 
Denis
looks
at
tuples
1
66.1
5
>>> 

• Concatenation of tuples with + operator
• Repetition of tuples with * operator

Here is an example of the  + operator as well as the * operator

>>> t = ("Denis", 1, 66.100)
>>> t + (3,2)
('Denis', 1, 66.1, 3, 2)
>>> t * 5
('Denis', 1, 66.1, 'Denis', 1, 66.1, 'Denis',
 1, 66.1, 'Denis', 1, 66.1, 'Denis', 1, 66.1)
>>> 

Tuples can contain any type of object
You can nest tuples
You access inner elements by using chain square-brackets indexing

>>> t = (("Denis", "looks") , (1,2), (5.1, 6.1))
>>> t[2][1]
6.1
>>> t[0][1]
'looks'
>>> t[0][0]
'Denis'
>>> 

Min and max functions can be used

>>> z = (1,2,4,7,9)
>>> min(z)
1
>>> max(z)
9

You don't need parentheses when creating tuples, you can ommit them

>>> x =1,4,7,9
>>> min(x)
1
>>> max(x)
9
>>> x
(1, 4, 7, 9)

However when printing the tuple to the console, the parentheses are displayed


Swapping
a, b = b, a is the idiomatic Python swap
Here is what it looks like

>>> x = 'ice'
>>> y = 'cream'
>>> x, y = y, x
>>> x
'cream'
>>> y
'ice'
>>> 

Tuple(iterable) constructor to create tuples from iterable series of objects

>>> tuple("abcdefg")
('a', 'b', 'c', 'd', 'e', 'f', 'g')
>>> 

This can be handy to find the min and max character from a string

>>> x = tuple("abcdefgdddzyyyaaa")
>>> min(x)
'a'
>>> max(x)
'z'
>>> 

To test for membership, you can use in and not in

>>> x = tuple("abcdefgdddzyyyaaa")
>>> "z" in(x)
True
>>> "m" in(x)
False
>>> "m" not in(x)
True
>>> "z" not in(x)
False
>>> 

And that's it for tuples

str

I will use str and string interchangeably in this post
a str is an immutable sequence of Unicode characters

len
Len gives you the number of characters in a str

>>> s = "abc"
>>> len(s)
3
>>> s = "  b  "
>>> len(s)
5
>>> 

As you can see, spaces are counted unlike the LEN function is SQL Server where spaces are trimmed from the end and start of a string

You can concatenate strings by using the + operator but just like in other language this is not efficient because it will create a new object

>>> s ="Den"
>>> s += "is"
>>> s
'Denis'
>>> 

What you should do is use join

Here is an example where we concatenate is to the string y

>>> y ="Den"
>>> ''.join([y,'is'])
'Denis'

As you can see Denis is printed to the console

Partition
The partition() method divides a string into three pieces around a separator: prefix, separator, suffix

In the code below, you can see that firstname and lastname have the values we want after we used partition with the separator

firstname, separator, lastname= "Michael:Jackson".partition(':')
>>> firstname
'Michael'
>>> lastname
'Jackson'

Use an underscore as a dummy name for the separator, this is also used by the many Python tools

>>> firstname, _, lastname= "Michael:Jordan".partition(':')
>>> firstname
'Michael'
>>> lastname
'Jordan'
>>> 

Format
Use format() to insert values into strings, replacement fields are delimited by { and }
Here is an example

>>> 
"My name is {0}, {1} {0}".format("Bond", "James")
'My name is Bond, James Bond'
>>> 

Range

A range is an arithmetic progression of integers, you can specify where to start, where to end and what the step is. A range is half-open, start is included but stop is not

Constructor	Arguments	Result
range(6)	stop	0, 1, 2, 3, 4, 5
range(6, 10)	start, stop	6, 7, 8, 9
range(10, 20, 2)	start, stop, step	10, 12, 14, 16, 18

Here is what it looks like in the console, range(5) will hold numbers between 0 and 4

>>> x = range(5)
>>> x
range(0, 5)
>>> for item in x:
 print(item)

 
0
1
2
3
4
>>> 

Here is what it looks like in the console, range(0, 10) will hold numbers between 0 and 9

>>> x = range(0,10)
>>> for item in x:
 print(item)

 
0
1
2
3
4
5
6
7
8
9

Here is what it looks like in the console, range(0, 10, 2) will hold numbers between 0 and 9, but because step 2 was supplied, it will be on the numbers 0,2,4,6 and 8

>>> x = range(0,10,2)
>>> x
range(0, 10, 2)
>>> for item in x:
 print(item)

 
0
2
4
6
8
>>> 

That it is for today..I will continue with collections and I will look at list, dict and set

Summer of code 2017: Python, Day 5 Objects

As explained in my Summer of code 2017: Python post I decided to pick up Python

Today is officially day 5, today, I looked at objects in Python, here are my notes

if you do something like this

x = 1000

Python creates an int object with a value of 1000, x now points to this object with a value of 1000
if you now do this
x = 500

Python will not change the value of the object from 1000 to 500 but will instead create another object with a value of 500 and z will now point to that object. The garbage collector will destroy the object with a value of 1000. This all happens because in Python objects are immutable, they cannot change


If you assign  1000 to x, then assign 500 to y, then assign x to y, both are pointing to the same object. You can prove that by using the id() function

In this example below, you will see that after we assign x to y, bot x and y point to the same object with id 50127440

>>> x = 1000
>>> y = 500
>>> y =x
>>> y
1000
>>> x
1000
>>> id(x)
50127440
>>> id(y)
50127440
>>> 

What if you have two variables and assign the same value?

>>> a = 1
>>> b =1
>>> id(a)
499688544
>>> id(b)
499688544
>>> 

As you can see, those also point to the same object

You can also us is to see if 2 objects are the same, so if you do x is y, you will get back True or False

>>> x = 5
>>> y = 5
>>> x is y
True
>>> 

If you do math against a variable, the id will also change

>>> z = 5
>>> id(z)
499688672
>>> z +=2
>>> id(z)
499688736
>>> 

With list it works like this

if you have a list d [1, 2, 3], now you add list e with the values of list d, now both d and e are [1, 2, 3]. If you now modify the list for e to be [1, 1000, 3],  both  e and d are now [1, 1000, 3]. This is because you modified the list object from [1, 2, 3] to [1, 1000, 3] and both d and e point to this list object

Here is what it looks like in IDLE

>>> d = [1, 2, 3]
>>> d
[1, 2, 3]
>>> e = d
>>> e
[1, 2, 3]
>>> e[1] = 1000
>>> e
[1, 1000, 3]
>>> d
[1, 1000, 3]
>>> e is d
True
>>> 

What will happen if we create 2 lists with the same values by assign the values to each list. Now the values are the same

>>> f = [1, 2]
>>> g = [1, 2]
>>> f == g
True
>>> f is g
False
>>> f == f
True

With integers, both is and  == return true

>>> x = 1
>>> y = 1
>>> x == y
True
>>> x  is y
True
>>> 

The is operator determines equality of identity, == determines equivalence


So even though people call these object variables in Python, these are really named references to objects


I also learned about the dir built-in function

Without arguments, return the list of names in the current local scope. With an argument, attempt to return a list of valid attributes for that object.

The default dir() mechanism behaves differently with different types of objects, as it attempts to produce the most relevant, rather than complete, information:

• If the object is a module object, the list contains the names of the module’s attributes.
• If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases.
• Otherwise, the list contains the object’s attributes’ names, the names of its class’s attributes, and recursively of the attributes of its class’s base classes.

So for example if we call dir on the math object, it will return all the functions available

>>> import math
>>> type(math)

>>> dir(math)
['__doc__', '__loader__', '__name__', '__package__', '__spec__', 'acos', 'acosh',
 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'ceil', 'copysign', 'cos', 'cosh', 
'degrees', 'e', 'erf', 'erfc', 'exp', 'expm1', 'fabs', 'factorial', 'floor', 'fmod', 
'frexp', 'fsum', 'gamma', 'gcd', 'hypot', 'inf', 'isclose', 'isfinite', 'isinf', 'isnan', 
'ldexp', 'lgamma', 'log', 'log10', 'log1p', 'log2', 'modf', 'nan', 'pi', 'pow', 'radians', 
'sin', 'sinh', 'sqrt', 'tan', 'tanh', 'tau', 'trunc']
>>> math.pi
3.141592653589793
>>> math.pow(2,4)
16.0
>>> 

So this is a quick way to get all the available methods/functions from a class

Summer of code 2017: Python local help files

As explained in my Summer of code 2017: Python post I decided to pick up Python

I noticed that Python ships with a help file in chm format ( Compiled HTML Help)



Microsoft Compiled HTML Help is a Microsoft proprietary online help format, consisting of a collection of HTML pages, an index and other navigation tools. The files are compressed and deployed in a binary format with the extension .CHM, for Compiled HTML. The format is often used for software documentation.

I haven't used a chm file since SQL Server 2000 within Query Analyzer. I prefer these files over online files for multiple reason

You don't have to be online to access the help file, you can be coding in a cave without connectivity and you can still pull up help

You can bookmark pages you want to get back to over and over again, these will be in the favorites tab

There is an index tab, this is like the back of a book, it is in alphabetical order and you can quickly find stuff

I typed in string, hit enter and saw the following

Then I clicked on method and was presented with the page you see

Do you use the local help file or do you use the online documentation?