/PrettyPrintingPerfected-Python

An extension of the built in pretty printing library in Python. For 'extreme' pretty printers only.

Primary LanguagePython

Pretty Printing Perfected

A tool for classic pretty printing and extreme pretty printing in one. 

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Definitions

For reference in the code and in this file, here is how I define classic pretty printing versus extreme.

Classic

NOTE: All classic pretty printing is handled by the built in python library: pprint.

When I refer to classic pretty printing, it means what is normally accepted as pretty printing; the syntax for the actual data structure is kept but the data is spaced in a neat way. Here is an example:

# Input
groceries_list = ['apples', 'belvita bars', ['hello_one', 'hello_two', 'hello_three'],
                  'donuts', 'milk (organic)', ['hello_four', ['hello_five']],
                  'twinkies', 'yogurt']

# Output
[   'apples',
    'belvita bars',
    ['hello_one', 'hello_two', 'hello_three'],
    'donuts',
    'milk (organic)',
    ['hello_four', ['hello_five']],
    'twinkies',
    'yogurt']
Extreme

This is the unique functionality of the package. It completely converts the data structure to a string that could be presented straight to a user in some way. Here is an example:

# Input
groceries_list = ['apples', 'belvita bars', 'donuts', 'milk (organic)']

# Output
Groceries List
______________

1) Apples
2) Belvita Bars
3) Donuts
4) Milk (organic)

Functions

There are a range of functions to convert specific data structures into pretty strings.

prettify_sequence(data, outputTitle)
# Input
groceries_list = ['apples', 'belvita bars', 'donuts', 'milk (organic)']

# Output
Groceries List
______________

1) Apples
2) Belvita Bars
3) Donuts
4) Milk (organic)
prettify_dict(data, outputTitle)
# Input
user_data = {'id': '8472883', 'name': 'UserName', 'password': 'Password'}

# Output
User Data
_________

Id -> 8472883
Name -> UserName
Password -> Password
peachy_print(data, outputTitle)

There is also the option to use this method, which automatically detects which of the above functions to use in order to prettify the input data structure.

Defaults

The user can modify a few defaults.

  1. regular_print This determines whether or not to convert to a normal pretty print string or to an extreme version which only this package offers. It defaults to False, resulting in use of the extreme functions.
  2. return_string This determines whether to return a string or print the output automatically. It defaults to False, resulting in automatic printing.
  3. iterate_nested This determines whether or not the printer will iterate through each nested data structure it finds or completely ignore it and continue.
  4. capitalize This determines whether or not to the printer will automatically capitalize strings when printed.
  5. indent Changing this only effects the output of a regular print action. It determines the indent of the classic pretty printed data structure. It defaults to 0, resulting in no indent.

Nested Data Structures (same type)

If iterate_nested is set to True(see above), nested data structures of the same type are treated as if they are not nested at all; the output will closely resemble the same data structure with no nesting. Here is an example:

# Input
groceries_list = ['apples', 'belvita bars', ['hello_one', 'hello_two', 'hello_three'],
                  'donuts', 'milk (organic)', ['hello_four', ['hello_five']],
                  'twinkies', 'yogurt']

# Output
Groceries List
______________

1) Apples
2) Belvita bars
3) Hello_one
4) Hello_two
5) Hello_three
6) Donuts
7) Milk (organic)
8) Hello_four
9) Hello_five
10) Twinkies
11) Yogurt

Nested Data Structures (different type)

If iterate_nested is set to True(see above), nested data structures of different types automatically separate themselves from each other and are printed in their own blocks. Here is an example:

# Input
user_data = ['apples', 'belvita bars', ['hello_one', 'hello_two', 'hello_three'],
             {'id': '8472883', 'name': 'UserName', 'password': 'Password'}, 'milk (organic)',
             ['hello_four', ['hello_five']],
             'twinkies', 'yogurt', {'id': '456', 'name': ['item one', 'item two', 'item three'], 'password': 'yo'}]
# Output
Name
____

1) Item one
2) Item two
3) Item three

User data
_________

1) Apples
2) Belvita bars
3) Hello_one
4) Hello_two
5) Hello_three
6) Milk (organic)
7) Hello_four
8) Hello_five
9) Twinkies
10) Yogurt

Id -> 8472883
Name -> UserName
Password -> Password

Id -> 456
Password -> yo

Since sets are unordered, the extremely pretty version of them also are not ordered. Here is another example showing nested tuples and sets:

# Input
data = {5: [3, 4, 5, 6, 7], 'hi': [34, 345, 4], '4': '4', 'tuple': ('in tuple one', 'in tuple two'),
        'my set': {'one', 'two', 'three', 'one', 5}}
# Output
5
_

1) 3
2) 4
3) 5
4) 6
5) 7

Hi
__

1) 34
2) 345
3) 4

Tuple
_____

1) In tuple one
2) In tuple two

My set
______

- Three
- One
- 5
- Two

User data
_________

4 -> 4

Full Example

The following is how this tool is intended to be used:

from peachy-print import PeachyPrinter

if __name__ == '__main__':
    peachyPrinter = PeachyPrinter()
    data = [('item one', ('in nested tuple', ('hello',), 'yeah'), 'item two',
             'item three'), 70, 90, 'String', True, None,
            {'set item one', 'set item two', ('tuple set one', 'tuple set two'), 'set item three'},
            {'dict list': ['in dict one', 'in dict two', 'in dict three'], 'mighty': 'SEVEN',
             'username': 'USERNAME'}]

    output = peachyPrinter.peachy_print(data, 'all the data in the world')

This would print the data provided with the heading 'All The Data In The World' in a the peachy way.