Python Introduction


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Why Python?

Why study Python in Principles of Programming Languages?

  • Multi-paradigm
    • Object-oriented
    • Functional
    • Procedural
  • Dynamically typed
  • Relatively simple with little feature multiplicity
  • Readability focused
  • No specialized IDE required
  • Fast, relative to other dynamically typed languages
    • And when it’s not fast enough, you can rewrite that performance-critical section in C. Python is natural to interop with C.
  • Highly General Purpose!
    • Web programming, machine learning, GUI programming, Email processing, education, simulations, web scraping…

Installing Python

For this course, we will be using Python 3.6 or 3.7.

  • ALAMODE machines: already have Python 3.7
  • Arch Linux: install python for 3.7
  • Ubuntu 18.04: install the python3 package for 3.6
  • Ubuntu 16.04 or 14.04: setup the ppa:deadsnakes/ppa then install python3.7
  • Fedora 28: ships with Python 3.6
  • Other distros: ask on Piazza if you need help


You are required to develop on Linux. I am unable to provide help for you setting up the projects on other systems.

Style Basics

Python is one of the few languages with an official style guide (PEP 8). Here’s a quick summary:

  • Use 4-spaces for each level of indentation. Never use hard tabs!
  • Use snake_case for function and variable names.
  • Use CapWords for class names.
  • Never ever use camelCase in Python.

Basic Input and Output

  • The print function takes any amount of arguments, and prints them separated by spaces on the same line.
  • The input function takes an optional prompt string, prompts the user for input, and returns the string they typed.
name = input("What is your name? ")
print("Nice to meet you", name)

When you need more control…

Use sys.stdout and sys.stdin which behave like file buffers (similar to cout and cin in C++).

A Simple Example

for i in range(1, 101):
    if i % 3 == 0 and i % 5 == 0:
        print("Fizz Buzz")
    elif i % 3 == 0:
    elif i % 5 == 0:

Indentation Denotes Scope

Any time Python sees a :, it expects an indented section to follow. The indented section denotes the scope of the operation.

Builtin Types

bool:True or False
int:integers, not size-bound
float:double-precision floating point numbers
complex:complex numbers
str:for Unicode strings, immutable
bytes:for a sequence of bytes, immutable
list:mutable ordered storage
tuple:immutable ordered storage
set:mutable unordered storage
frozenset:immutable unordered storage
dict:mutable key-value relation
Functions:yup, they’re first class!
Classes:they’re first class too (of type type)


# List literals
[1, 2, 3]

# Tuple literals
(1, 2, 3)
# ... 1 element tuples are special
(1, )

# Dictionary literals
{'Ada': 'Lovelace', 'Alan': 'Turing'}

# Set literals
{1, 2, 3}
# ...empty set is:

String Formatting

To format elements into a string, you could convert each element to a string then add them all together:

print("Time " + str(hours) + ":" + str(minutes) + ".")

Ow… my fingers hurt, and that was not too easy to read either. As an alternative, try .format on a string:

print("Time {}:{}.".format(hours, minutes))

Or, since Python 3.6, you can use an f-string:

print(f"Time {hours}:{minutes}.")

See the Python documentation for more information. There’s plenty to this formatting language.


Do not use old-style (printf-style) string formatting in this course.

Selection (if statements)

Python’s primary structure for selection is if:

if i == 0 and j == 1:
    print(i, j)
elif i > 10 or j < 0:
    print("all is fine")

Notice you do not need parentheses surrounding the condition like in C or C++.

There’s also a ternary operator (good for simple conditionals):

def foo(bar, baz):
    return bar if bar else baz

Why no switch or case?

Most switch or case statements over-complicate what could be done in a single line using a dictionary. Where this is not the case, you really shouldn’t be using a switch anyway.

An Example switch in C

switch (c) {
    case 'q':
    case 'x':
    case 'z':
        a += 4;

Python Equivalent

diff = {'q': 1, 'x': -1, 'z': 4}
a += diff[c]


Python provides your traditional while loop, the syntax is similar to if:

while n < 100:
    j /= n
    n += j

But under most cases, the range-based for loop is preferred:

for x in mylist:  # also works on any iterable


Python’s for loop is a range-based for loop, unlike C’s for loop which is really just a fancy while loop.

Generating Ranges

The generator function range creates an iterable for looping over a sequence of numbers. The syntax is range(start, stop, step).

  • start is the number to start on
  • stop is the number to stop before
  • step is the amount to increment each time
for i in range(0, 5, 1):

Optional Parameters

Both start and step are optional, and if omitted, will be assumed to be 0 and 1 respectively.

Iterating Works on Many Types of Objects

These range based for loops are supported by a wide variety of objects.

for k, v in my_dictionary.items():  # dictionaries
    print(k, v)

for line in files:  # files

for i, element in enumerate(my_list):  # when you need the index too
    print(i, element)

Pairing Iteration Structures with else

In Python, you can pair an else block with for and while. The block will be executed only if the loop finishes without encountering a break statement.

An example of this can be seen below:

for i in range(10):
    x = input("Enter your guess: ")
    if i == x:
        print("You win!")
    print("Truly incompetent!")


mylist = [1, 2, 3, 4]

# syntax is [start:stop:step], step optional
mylist[1:3] # => [2, 3]

# unused parameters can be ommited
mylist[::-1] # => [4, 3, 2, 1]

# without the first element
mylist[1:] # => [2, 3, 4]

# without the last element
mylist[:-1] # => [1, 2, 3]

Tuple Expansion & Collection

Multiple assignments work like so:

names = ("R. Stallman", "L. Torvalds", "E. Dijkstra")
a, b, c = names

* can be used to collect a tuple:

# drop the lowest and highest grade
grades = (79, 81, 93, 95, 99)
lowest, *grades, highest = grades

The same can be done to expand a tuple in a function call:

# Each grade becomes a separate argument


To define a function in Python, use the def syntax:

def myfun(arg1, arg2, arg3):
    if arg1 == 'hello':
        return arg2
    return arg3

Even if your function does not take arguments, you still need the parentheses:

def noargs():
    print("I'm all lonely without arguments...")

Keyword Arguments

When we define a function in Python we may define keyword arguments. Keyword arguments differ from positional arguments in that keyword arguments:

  • Take a default value if unspecified
  • Can be placed either in order or out of order:
    • In order: arguments are assigned in the order of the function definition
    • Out of order: the argument name is written in the call
  • Positional and keyword arguments can be mixed, so as long as the positional arguments go first.

Keyword Arguments: Example

def point_twister(x, y=1, z=0):
    return x + 2*z - y

# all of these are valid calls
print(point_twister(1, 2, 3))       # x=1, y=2, z=3
print(point_twister(1, 2))          # x=1, y=2, z=0
print(point_twister(1))             # x=1, y=1, z=0
print(point_twister(1, z=2, y=0))   # x=1, y=0, z=2
print(point_twister(1, z=2))        # x=1, y=1, z=2

Style Note

PEP 8 says that we should place spaces around our “=” in assignments, but these are not assignments, and should be written without spaces around the “=”.

Passing a Dictionary as the Keyword Arguments

Just like a tuple or list can be expanded to the positional arguments of a function call using *some_tuple, a dictionary can be expanded to the keyword arguments of a function using **some_dict. For example:

my_point = {'x': 10, 'y': 15, 'z': 20}

*args and **kwargs

Python allows you to define functions that take an arbitrary number of positional arguments (*args) or keyword arguments (**kwargs). In principle, this really just works like tuple expansion/collection.

def crazyprinter(*args, **kwargs):
    for arg in args:
    for k, v in kwargs.items():
        print("{}={}".format(k, v))

crazyprinter("hello", "cheese", bar="foo")
# hello
# cheese
# bar=foo

The names args and kwargs are merely a convention. For example, you could use the names rest and kwds instead if you wanted.

*args and **kwargs: Another Example

def fancy_args(a, b, *args, c=10, **kwargs):
    print("a is", a)
    print("b is", b)
    print("c is", c)
    print("args is", args)
    print("kwargs is", kwargs)

fancy_args(1, 2, 3, 4, c=15, d=16, e=17)
# a is 1
# b is 2
# c is 15
# args is (3, 4)
# kwargs is {'d': 16, 'e': 17}