This document serves as an introductory guide to Python programming, aimed at beginners. It covers fundamental concepts such as variables, data types, functions, loops, and conditional statements using practical examples and code snippets. Additionally, it provides resources for further learning, including a link to a Coursera course on interactive programming in Python.

1. Python 101:
Python for Absolute Beginners
PyTexas 2014

2. What is programming?

3. A computer is a machine that stores
pieces of information.
A computer also moves, arranges, and
controls that information (or data).
A program is a detailed set of
instructions that tells a computer
what to do with that data.

4. CodeSkulptor!

5. CodeSkulptor
 Developed by Scott Rixner of Rice
University to use for COMP 200.
 Based on CodeMirror and Skulpt.
 www.codeskulptor.org
 If you want to learn more about
using Python with CodeSkulptor
after this class, check out the
Coursera course “An Introduction
to Interactive Programming in
Python”! (9/15 – 11/16)
 https://www.coursera.org/course/
interactivepython

6. Interacting with CodeSkulptor
 Run
 Save
 Fresh URL
 Open Local
 Reset

7. Additional Resources
 Docs (documentation)
 Demos
 Viz Mode

8. Let’s see what this thing can do…

9. Recap:
Explore! Makes changes, see how they
impact the program as a whole.
When in doubt, check the
documentation.
When super in doubt, Google it.

10. Math

11. Math
Try typing this into CodeSkuptor:
>>> print 3 + 12
>>> print 12 - 3
>>> print 9 + 5 – 15 + 12
Operators:
add: +
subtract: -
Note: don’t type the arrows >>> !

12. Math
Rule: If you want Python to answer in floats, you have to talk to it in floats.
More operators:
divide: /
multiply: *
>>> print 3 * 12
>>> print 12 / 3
>>> print 11 // 3
>>> print 12.0 / 3.0
>>> print 11.0 / 3.0
>>> print 11.0 // 3.0

13. Math
Comparison operators:
== Equal to
!= Not equal to
< Less than
> Greater than
<= Less than or equal to
>= Greater than or equal to

14. Math
Practice:
>>> print 2 < 3 True
>>> print 2 <= 2 False
>>> print 3 > 2 True
>>> print 2 != 3 True
>>> print False < True True

15. Strings

16. Strings
Examples:
Try typing one without quotes:
What’s the result?
>>> “It’s a beautiful day!”
>>> “Goodbye, cruel world.”
>>> Aggies
>>> “Aggies”
>>> “Rice fight, never die!”
>>> “3 + 2”

17. Strings
String operators:
concatenation: +
multiplication: *
Try concatenating:
Try multiplying:
>>> print “Hello” + “ “ + “world!”
>>> print “HAHA” * 250

18. Variables

19. Variables
Calculate a value:
How can you save
that value?
Give the value a name:
>>> print 21 + 21
42
>>> ultimate_answer = 42
>>> ultimate_answer
42

20. Variables
Create a variable
and give it a value:
Now assign a
new value:
>>> headmaster = “Dumbledore”
>>> print headmaster
‘Dumbledore’
>>> headmaster = “Hardcastle”
>>> print headmaster
‘Hardcastle’
>>> color = “Brad Neely”
>>> color = 12

21. Variables
 You can calculate a variable once, but keep the result to use later.
 You can keep the same name for a variable, but change the value.
Some other things that we can do with variables:
Get an index from a string:
Do some math:
>>> headmaster = “Dumbledore”
>>> print headmaster[2]
>>> number = 3
>>> print headmaster[number - 2]

22. Types of data

23. Data Types
We already know about three types of data:
“Whoop!” string
42 integer
3.14159 float
Python can tell us about types using the type() function:
>>> print type(“Whoop!”)
<type ‘str’>
How would we get Python to output int and float types?

24. Data Type: Lists

25. Lists
List: a sequence of objects
>>> Beatles = [“John”, “Paul”, “George”, “Ringo”]
>>> grades = [82, 93, 67, 99, 100]
Guess what this will output:
>>> type(Beatles)
>>> type(grades)

26. Lists
List: a sequence of objects
>>> Beatles = [“John”, “Paul”, “George”, “Ringo”]
>>> grades = [82, 93, 67, 99, 100]
Guess what this will output:
>>> type(Beatles)
<type ‘list’>
>>> type(grades)
<type ‘list’>

27. Lists
Index: Where an item is in the list
>>> Beatles = [“John”, “Paul”, “George”, “Ringo”]
>>> Beatles[0]
‘John‘
[“John”, “Paul”, “George”, “Ringo”]
0 1 2 3
Python always starts at zero!

28. Data Type: Booleans

29. Booleans
A boolean value can be:
Is 1 equal to 1?
Is 15 less than 5?
True or False.
>>> print 1 == 1
True
>>> print 15 < 5
False

30. Booleans
What happens when we type
Boolean values in the
interpreter?
When the words ‘True’ and
‘False’ begin with upper case
letters, Python knows to
treat them like Booleans
instead of strings or integers.
>>> True
>>> False
>>> true
>>> false
>>> type(True)
>>> type(“True”)

31. Booleans
and
If both comparisons are True:
If only one of the
comparisons is True:
If both of the
comparisons are False:
>>> 1==1 and 2==2
True
>>> 1==1 and 2==3
False
>>> 1==2 and 2==3
False

32. Booleans
or
If both comparisons are True:
If only one of the
comparisons is True:
If both of the
comparisons are False:
>>> 1==1 or 2==2
True
>>> 1==1 or 2!=2
True
>>> 1==2 or 2==3
False

33. Booleans
not
You can use the word not to
reverse the answer that
Python gives:
Any expression that is True
can become False:
>>> 1==1
True
>>> not 1==1
False
>>> not True
False

34. Booleans
You can also use Booleans in their own expressions:
>>> True and True
>>> True and False
>>> False and False
>>> True or True
>>> False or True
>>> False or False
>>> not True and True
>>> not True or True

35. Logic

36. if Statements

37. if Statements
Making decisions:
If a condition is met,
perform an action:
“If you’re hungry, let’s eat lunch.”
“If you like Frisbee, let’s play!”
>>> state = “Texas”
>>> if state == “Texas”:
print “TX”
TX

38. if Statements
Adding a choice:
Adding a choice in our code
with the else clause:
“If you’re hungry, let’s eat lunch. Or else we
can eat in an hour.”
“If you like Frisbee, let’s play! Or else we can
play rugby.”
>>> if state == “Texas”
print “TX”
else:
print “[inferior state]”

39. if Statements
Adding many choices:
Adding more choices in our code
with the elif clause:
“If you like Frisbee, let’s play! Or else we
can play rugby. Or else we can play
Bioshock, or Half-Life, or Portal…”
>>> if name == “Paige”
print “Hi Paige!”
elif name == “Walker”:
print “Hi Walker!”
else:
print “Imposter!”

40. Loops

41. Loops
Loops are chunks of code that repeat a task over and over again.
 Counting loops repeat a certain number of times.
 Conditional loops keep going until a certain thing happens
(or as long as some condition is True).

42. Loops
Counting loops repeat a certain number of times – they keep going until they get
to the end of a count.
>>> for mynum in [1, 2, 3, 4, 5]:
print "Hello", mynum
Hello 1
Hello 2
Hello 3
Hello 4
Hello 5
The for keyword is used to create this kind of loop, so it is usually just called a
for loop.

43. Loops
Conditional loops repeat until something happens
(or as long as some condition is True).
>>> count = 0
>>> while (count < 4):
print 'The count is:', count
count = count + 1
The count is: 0
The count is: 1
The count is: 2
The count is: 3
The while keyword is used to create this kind of loop, so it is usually just called a
while loop.

44. Algorithms

45. Algorithms
Really just means “set of instructions”
Secret: computers
aren’t very smart.

46. How would I make a pot of coffee?
1. Get a flavor of ground coffee.
2. Get a coffee maker.
3. Get filter paper.
4. Get a pot of water.
5. Make sure the coffee maker is plugged in…
…and on, and on, and on.
But to us, it’s just “make a pot of coffee”.

47. Functions

48. Remember how Algorithms are just instructions?
 Functions are just a concise way to group instructions into a bundle.
What it's like in our minds:
“Make a pot of coffee.”  bundle
In Python, you could say it like this:
make_coffee(coffee_grounds, coffee_pot, water, filter_paper)
^ ^-----------------^---------------^-----------------^
function name function parameters

49. Functions
Let’s define a function in CodeSkulptor:
>>> def beverage():
print ‘Have you had a cup of coffee today?’
Now we’ll call the function:
>>> beverage()
Have you had a cup of coffee today?

50. Functions
But what if not everyone wants a cup of coffee?
Let’s define a function with parameters:
>>> def beverage(drink):
print “Have you had a cup of ” + drink + “ today?’
Now we’ll call the function:
>>> beverage(“Monster Zero”)
Have you had a cup of Monster Zero today?

51. Functions
 Functions are defined using def.
 Functions are called using parentheses ().
 Functions take parameters and return outputs.
 print displays information, but does not give a value.
 return gives a value to the caller.

52. Thanks so much!
Any questions?