Python Programming Basics
This tutorial is an introduction to Python basics such as how to assign a variable value and change that value. There is also a list of reserved keywords although use of these keywords is explained later.
Python Variable Names
Valid variable names are those that start with a letter (upper or lower case) or underscore. Valid variable names include:
myVar myVariable my4Variable myVariable4 _myVariable __myVariable MYVARIABLE myvariable
Invalid variable names include those that start with a number, have a space in the name, or contain special characters such as:
my Variable 4myVariable myVariable!
Python Reserved Keywords
There are reserved keywords in Python that control the flow of the program and cause unique behavior. Built-in constants include:
True # True logical condition False # False logical condition None # Absense of a value
Note that True, False, and None are capitalized. Common reserved keywords include:
and # logical 'and' (both conditions True)
as # aliasing (e.g. with open(file) as f:)
assert # internal self-check (e.g. assert x=y)
break # break out of a loop
class # define a new class (variables and functions)
continue # advance to next 'for' or 'while' loop
def # define a function
del # set a variable to 'None'
elif # 'else if' condition of 'if' statement
else # 'else' condition of 'if' statement
except # catch errors
finally # 'try' exit code
for # 'for' loop
from # specify package element for loading
global # create a global variable
if # 'if' statement
import # load package
in # membership operator (e.g. x in y)
is # test for equal identification numbers
lambda # create anonymous function
nonlocal # expand variable scope outside function
not # logical 'not'
or # logical 'or'
pass # null operator when statement is required
print # create display output line
raise # error notification (e.g. raise Exception('Error'))
return # return from function
try # 'try'...'except' code structure for error catching
while # loop until condition is not True
with # flow control for automatic clean-up
yield # intermediate return from function
There are also many built-in functions that should also be avoided when creating variable names. Some common functions are listed below.
float # convert number to floating point type id # identification number int # convert number to integer type len # number of elements in a collection max # maximum value min # minimum value pow # power (e.g. pow(x,2) or use x**2) range # sequence generator round # nearest integer value str # convert to string type type # object type
These reserved keywords should be avoided when creating variable names. Most Integrated Development Environments (IDEs) for Python and text editors for Python scripts will automatically highlight the reserved keywords such as the example below where reserved keywords are highlighted in orange and green.
answer = randint(0,10)
correct = False
while not(correct):
guess = int(input("Guess a number (0-10): "))
if guess < answer:
print("Too low")
elif guess > answer:
print("Too high")
else:
print("Correct!")
correct = True
Guess a number (0-10): 5 Too high Guess a number (0-10): 3 Too high Guess a number (0-10): 1 Too low Guess a number (0-10): 2 Correct!
Python Objects
Python is an object-oriented programming language. Each Python object has defining properties including the Identity (a memory address), Type (e.g. string, integer, floating point number), and Value. Below is an example of assigning 'x' as an Integer and printing the object properties.
print(x) # print value => 2
print(id(x)) # print id number => 1737348944
print(type(x)) # print type => <class 'int'>
Python Data Types
Data can be stored a variety of formats. Fundamental Data Types include Numbers (e.g. int and float), Sequences (e.g. str, list, and tuple), and Mappings (dict). Below are a few examples:
y=2.02 # float
z='3' # string
print(str(x)+z) # 23
print(x+int(z)) # 5
a=[x,y,z] # list
print(a[1]) # 2.02
b=(x,y) # tuple
print(b[1]) # 2.02
c={'m':7,'n':8} # dictionary
print(c['m']) # 7
Python Math Expressions
Python has addition (+), subtraction (-), multiplication (*), division (/), and power (**) as standard mathematical operators. The Math module is available by importing the math package. The math module provides a number of common mathematical operators such as shown in the example below.
x=3.1415
print(math.sin(x)) # 9.265e-05
The Numpy module also has many of the mathematical operators. This course uses many NumPy and SciPy built-in values and functions for scientific computing. Below is an example of using a built-in value and a trigonometric function (sine). In this case, the NumPy package is renamed as np to shorten the future references (numpy.pi => np.pi).
x=np.pi
print(math.sin(x)) # 1.225e-16
The result of mathematical expressions may be slightly off the expected value such as the example above that should equal to zero for sin(pi). This is due to finite machine precision (32-bit or 64-bit) calculations that have some round-off error at the last stored digit.
Python Strings
Strings are a list of characters. Strings are combined with the addition (+) symbol and either the single or double quotes are used.
last = "Smith"
name = first + ' ' + last
print(name) # Tom Smith
Comments can are added to Python scripts with the hash (#) symbol. When included inside a string, the comment character becomes part of the text and is no longer a comment.
print(hashtag) # prints: #learnpython
There are also special escape sequences such as newline (\n), tab indent (\t), double quote (\"), single quote (\'), and backslash (\\).
print(flight)
# prints:
# Landing at
# O'Hare International Airport
To avoid using special escape sequences such as newline, a raw string identifier (r) can be used before the string definition.
print(flight)
# prints:
# Landing at\n O\'Hare International Airport
An easy way to convert a number to a string is with the built-in function str or with formatted output. However, this method may produce a number that has too many decimal places. Numbers can be customized in floating point (f), scientific notation (e), or percentage (%) form with format such as:
import numpy as np
x = np.pi
# format pi
print(str(x)) # 3.141592653589793
print('{:.2f}'.format(x)) # 3.14
print('{:.10f}'.format(x)) # 3.1415926536
print('{:.5e}'.format(x)) # 3.14159e+00
print('{:.3%}'.format(x)) # 314.159%
