Strings

Variabelen met meerdere elementen

tuple, (13, 71, 22, 15, 37, 12)
elementen zijn niet te wijzigen en niet te verwijderen en niet toe te voegen
aanduiding elementen met volgnummer, beginnend bij 0

dictionary, {'jan':13, 'feb':71, 'maa':22, 'apr':15, 'mei':37, 'jun':12}
elementen zijn te wijzigen, te verwijderen en toe te voegen
aanduiding element met 'sleutel'/key

Basis data-types

Blockstructuren in Python

Indentatie is enige aanwijzing (ook voor compiler)
Gebruik 4 spaties voor indentatie (liever geen TABS)

Conditionele herhaling

while conditie:
statement(s)

minfactor = 1
maxfactor = 10
basis = 7

factor = minfactor
while factor <= maxfaxtor:
     print (factor, 'x', basis, '=', factor*basis)
     factor += 1

Indexering met while

namen = ['jan', 'piet', 'klaas']

i = 0

while i < len(namen):
     print ('hoi', namen[i]
     i += 1

Herhaling met het for statement

for eenelem in reeks::
    statement(s)

a = 'string'
b = [1, 3, 5 ,7]
c = (2, 4, 6,8)
d = {'piet':1961, 'anja':1984}

for val in a:
     print (val, end=' - ')        s - t - r - i - n - g -

for val in b:
     print (val, end=' - ')        1 - 3 - 5 - 7 -

for val in c:
     print (val, end=' - ')        2 - 4 - 6 - 8 -

for val in d:
     print (val, end=' - ')        piet - anja -

for val in d:
     print (d[val], end=' - ')     1961 - 1984 -

Functie range():

for n in range(10):
    print(n, end=' - ')    0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 - 9 -

Functie enumerate():

name = ['jan', 'piet', 'klaas']

for nummer, persoon in enumerate(namen):
    print(nummer, persoon)

Exception afvangen

i = 0
j = 0

try:
    print(i/j)
except Exception:
    print("Oei! dat moht niet"
else:
    print("Het ging goed!")

print("Hier komen we altijd")

In eigen code exception forceren

if i < 0:
    raise Exception("i is negatief")
else:
    print("met deze i kunnen we wat ...")

try:
    ....... # dit gaat mogelijk fout
exception Exception:
    pass    # maar zorg dat programma verder loopt

# hier gaan we altijd verder

break

continue

pass

Variabelen nemen dynamisch type aan

Toekenning bindt naam aan object

• oude binding ongedaan maken

• echter binding gaat ver

• nog verder zelfs

• echte kopie nodig?

Method: functie bij specifiek datatype

Lijst van methoden voor bepaalde datatype

• opvragen met dir(type)

• methods genaamd __iets__ zijm interne methoden

• type kan zijn: str,list, tuple, dict, int, float, .....

Meer info over gebruik van methodes

• opvragen met help(type) of help(type.method)

sequences

Dataypes string, list en tuple veel gemeen: gezamelijk "sequences"

Veel-gebruikte sequence operators

String methods

String heeft - naast sequence methods - nog extra methods

Merk op: string immutable, dus methods geven nieuwe string terug!

Veel gebruikte string methods:

String formateren - klassiek

Voorbeelden

String formattering methode str.format())

Als je een dictionary gebruikt, mag je zelfs de keys meegeven om te refereren aan bepaalde elementen van de dictionary, zoals aangegeven in dit voorbeeld:

voorbeelden:

Als je een enkele waarde wilt formaterem, kun je gebruik maken van de format functie:

List:

In plaats van de notatie:

b = a[:]

mag ook:

b = a.copy()

Maar ook de .copy() methode maakt slechts een top-level kopie!

• methodssort() en reverse() werken in-place (geven geen waarde terug)
• functies sorted(list)en reversed(list) geven waarde terug

Het tussenvoegen of vervangen van één f meerdere elementen is (ook) mogelijk met de slice-notatie:

>>> v = [3, 2, 1, 4]

>>> v[1:1] = 6

>>> v

[3, 6, 2, 1, 4]

>>> v[2:3] = [7, 8, 9]

v

[3, 6, 7, 8, 9, 1, 4]

List comprehension

list comprehension versus element vermenigvuldiging

Little endian versus big endian

Bte-volgorde in geheugen - endianess

• afhankelijk van type CPU
• stel: opslag van waarde 0x00301a7c als 4 byte
twee implementaties:
• little endian: minst-significante byte op beginadress van variabele (bijvoorbeeld x86 CPU)
• big endian: meest-significante byte op beginadres van variabele (mest andere CPU-types)
• consequenties bij inlezen/wegschrijven van integer waarden (byte-swap)
• van/naar binair bestand
• van/naar netwerk

Data in bestanden

Twee soorten bestanden
• binaire bestanden
• bytes in bepaald (gestandaardiseerd) formaat
• geen verschil tussen diverse besturingssystemen
• voorbeelden: .jpg .gif .png .pdf

• tekstuele bestanden
• tekst voor weergave op beeldscherm/printer/...
• encoding/decoding
• regeleinde kan verschillen per besturingssysteem

Binaire files - open mode

f = open(filenaam [,mode])

for the User

#!/usr/bin/python
raw_input("\n\nPress the enter key to exit.")

Multiple Statements on a Single Line

import sys; x = 'foo'; sys.stdout.write(x + '\n')

Data Types

Python has five standard data types −

• Numbers
• String
• List
• Tuple
• Dictionary

Python Numbers

Number data types store numeric values. Number objects are created when you assign a value to them. For example −

var1 = 1
var2 = 10

You can also delete the reference to a number object by using the del statement. The syntax of the del statement is −

del var1[,var2[,var3[....,varN]]]]

You can delete a single object or multiple objects by using the del statement. For example −

del var del var_a, var_b

Python supports four different numerical types −

• int (signed integers)
• long (long integers, they can also be represented in octal and hexadecimal)
• float (floating point real values)
• complex (complex numbers)

Examples

• Python allows you to use a lowercase L with long, but it is recommended that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L.
• A complex number consists of an ordered pair of real floating-point numbers denoted by x + yj, where x is the real part and b is the imaginary part of the complex number.

Strings

Strings in Python are identified as a contiguous set of characters represented in the quotation marks. Python allows for either pairs of single or double quotes. Subsets of strings can be taken using the slice operator ([ ] and [:] ) with indexes starting at 0 in the beginning of the string and working their way from -1 at the end.

The plus (+) sign is the string concatenation operator and the asterisk (*) is the repetition operator. For example −

#!/usr/bin/python

str = 'Hello World!'

print str # Prints complete string
print str[0] # Prints first character of the string
print str[2:5] # Prints characters starting from 3rd to 5th
print str[2:] # Prints string starting from 3rd character
print str * 2 # Prints string two times
print str + "TEST" # Prints concatenated string

Hello World!
H
llo
llo World!
Hello World!Hello World!
Hello World!TEST

Python Lists

Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). To some extent, lists are similar to arrays in C. One difference between them is that all the items belonging to a list can be of different data type.

The values stored in a list can be accessed using the slice operator ([ ] and [:]) with indexes starting at 0 in the beginning of the list and working their way to end -1. The plus (+) sign is the list concatenation operator, and the asterisk (*) is the repetition operator. For example −

#!/usr/bin/python

list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tinylist = [123, 'john']

print list # Prints complete list
print list[0] # Prints first element of the list
print list[1:3] # Prints elements starting from 2nd till 3rd
print list[2:] # Prints elements starting from 3rd element
print tinylist * 2 # Prints list two times
print list + tinylist # Prints concatenated lists

['abcd', 786, 2.23, 'john', 70.200000000000003]
abcd
[786, 2.23]
[2.23, 'john', 70.200000000000003]
[123, 'john', 123, 'john']
['abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john']

Python Tuples

A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parentheses.

#!/usr/bin/python

tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 )
tinytuple = (123, 'john')

print tuple # Prints complete list
print tuple[0] # Prints first element of the list
print tuple[1:3] # Prints elements starting from 2nd till 3rd
print tuple[2:] # Prints elements starting from 3rd element
print tinytuple * 2 # Prints list two times
print tuple + tinytuple # Prints concatenated lists

('abcd', 786, 2.23, 'john', 70.200000000000003)
abcd
(786, 2.23)
(2.23, 'john', 70.200000000000003)
(123, 'john', 123, 'john')
('abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john')

#!/usr/bin/python

tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 )
list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tuple[2] = 1000 # Invalid syntax with tuple
list[2] = 1000 # Valid syntax with list

Python Dictionary

Python's dictionaries are kind of hash table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. A dictionary key can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object.

Dictionaries are enclosed by curly braces ({ }) and values can be assigned and accessed using square braces ([]). For example −

#!/usr/bin/python

dict = {}
dict['one'] = "This is one"
dict[2] = "This is two"

tinydict = {'name': 'john','code':6734, 'dept': 'sales'}


print dict['one'] # Prints value for 'one' key
print dict[2] # Prints value for 2 key
print tinydict # Prints complete dictionary
print tinydict.keys() # Prints all the keys
print tinydict.values() # Prints all the values

This produce the following result −

This is one
This is two
{'dept': 'sales', 'code': 6734, 'name': 'john'}
['dept', 'code', 'name']
['sales', 6734, 'john']

Dictionaries have no concept of order among elements. It is incorrect to say that the elements are "out of order"; they are simply unordered.

Data Type Conversion

Sometimes, you may need to perform conversions between the built-in types. To convert between types, you simply use the type name as a function.

There are several built-in functions to perform conversion from one data type to another. These functions return a new object representing the converted value.

CBT Nuggets

Python Program Flow .py

• Programs --> module(s) std library imports
• modules --> statements
• statements --> expressions
• expressions --> objects

Objects + types

object: everything in python data entity/attr methods entity passed to fx/assigned to var
Python is: dynamically typed strongly typed data type: data classification characteristics

operators:

Phyton core data types

Python Comparison Operators

These operators compare the values on either sides of them and decide the relation among them. They are also called Relational operators.

Assume variable a holds 10 and variable b holds 20, then −

[ Show Example ]

Python Assignment Operators

Assume variable a holds 10 and variable b holds 20, then −

[ Show Example ]

Python Bitwise Operators

Bitwise operator works on bits and performs bit by bit operation. Assume if a = 60; and b = 13; Now in binary format they will be as follows −

a = 0011 1100

b = 0000 1101

-----------------

a&b = 0000 1100

a|b = 0011 1101

a^b = 0011 0001

~a  = 1100 0011

Pyhton's built-in function bin() can be used to obtain binary representation of integer number.

There are following Bitwise operators supported by Python language

[ Show Example ]

Python Logical Operators

There are following logical operators supported by Python language. Assume variable a holds True and variable b holds False then

[ Show Example ]

Python Membership Operators

Python’s membership operators test for membership in a sequence, such as strings, lists, or tuples. There are two membership operators as explained below

[ Show Example ]

Python Identity Operators

Identity operators compare the memory locations of two objects. There are two Identity operators explained below:

[ Show Example ]

Python Operators Precedence

The following table lists all operators from highest precedence to lowest.

[ Show Example ]