These are all examples of different kinds of Python Statements:
- x = 3.14159
- mean_price = 12.35/4
- import turtle
- for _ in range(7):
    billy.forward(5)
- print("This line will execute once")

Examples of Statements in Python 

The use of a for loop can allow for the programmer to make repetitive outputs or actions. The for loop will search through an iterable in order to do something with each element in it.

```python
for _ in range(5):
    print("This will print 5 times.")
```
Result:
```
This will print 5 times.
This will print 5 times.
This will print 5 times. 
This will print 5 times. 
This will print 5 times. 
```


For Loops

Modules are files which can be thought of as packages containing functions and definitions meant for use in Python programming. Importing can be done through the use of import statements.
```
import turtle
import random
import aifc 
```
^The above statements import the turtle module, random module, and aifc module, respectively.

Importing Modules 


- If statement evaluates a boolean expression and  then executes a set of statements based on the output of the boolean expression.
 
- if ,elif and else are keywords that help to achieve conditional execution of statements.


Syntax


if boolean expression:

         statements

elif boolean expression:

        statements

else:

        statements



If Statements

While loops can allow a programmer to execute the same block of code repeatedly while a condition evaluates to true. The condition may be a result of a comparison, or the value of a variable. Non-zero variables and non-empty collections will evaluate to true, while the opposite will evaluate to false.

```python
x = 5
while x > 0:
   print(f"{x} seconds to launch")
   x = x - 1
print("Take Off!")
```
Result:
```
5 seconds to launch
4 seconds to launch
3 seconds to launch
2 seconds to launch
1 second to launch
Take Off!
```

While Loops

With the break statement we can stop or break out of the loop before it has looped through all the items:
```python
tasks = ["Eat", "Sleep", "Repeat"]
for x in tasks:
  print(x)
  if x == "Sleep":
    break
```
In the example above, the code will print ```Eat```  ```Sleep``` then the loop will ```break``` and ```Repeat``` will not be printed.


Break Statement

Comments are used to explain python code and make the code easier to read. They aren't considered actual code and are essentially ignored during compilation. We can write a single line comment using # symbol
```python
#this function takes two integers and prints the sum
def sum(x,y):
    print(x+y)
```
The comment explains the purpose of the function ```sum```

For a multiline comment, we can just put the comment inside triple quotes.
```python
"""
these lines
are
ignored
"""
print("Hello World")
```

Python Comments

The continue statement is used to ignore specific iterations of a loop and go onto the next iteration instead. Once the statement is reached and its conditions are met, control jumps back to the top of the loop, ignoring any remaining code in the loop body. In this example, the number 3 won't be printed.

```python
x = 0
while x < 5:
    x = x + 1
    if x == 3:
        continue
    print(f"{x}")
```
Continue statements work similarly to break statements, but they only end a single iteration of the loop, not the entire loop itself.

Continue Statement

A statement is any line of instruction that the Python interpreter can potentially execute. 

Types of statements include but are not limited to:
- Variable assignment statements 
- while statements
- for statements
- if statements
- import statements 

University of Michigan - Ann Arbor

- Values 
- Operators & Operands
- Functions
- Statements
- Expressions
- Debugging
- Classes and Objects
- Data Structures

Python Programming Language Foundational Concepts 

https://runestone.academy/runestone/books/published/fopp/index.html

Runestone: Foundations of Python Programming

A value is any thing in the form of a number, string, character, etc. that can be manipulated. Values can also be referred to as objects. 

Values in Python

Operators are things that represent computational processes in Python. These include +, -, *, **, //, %, and /. 
- "+" = Addition
- "-" = Subtraction
- "*" = Multiplication

- "**" = Exponent
- "//" = Divide, but only include whole number in result
- "%" = Modulo, which only displays remainder of operands 

Operands are the values being acted on by the operator. 

Operators & Operands in Python

Function can be thought of as devices that take in material, perform a specified operation on the taken-in material, then output a resulting object. 

Inputs are referred to as arguments 
End result is referred to as output or return value. 

Functions in Python

Statements in Python 

- Expressions are any combination of data types to be evaluated. Evaluating an expression results in values/objects. Expressions can also be evaluated into or set to values. 
- Asking Python to print an expression will result in the interpreter attempting to evaluate the expression and display the result

Expressions in Python 

- General Tips & Tricks
- Common Syntax Errors
- Error types
- Error Messages

Debugging in Python

A Class allows us to group together data and functions. It provides a template which can be instantiated to create objects. Classes and Objects help improve readability and allow code reuse. 

Classes are most often used in Object Oriented Programming, as they allow programmers to bundle sets of functions and data together. 

Python Classes and Objects

Data structures facilitate the organization of data in computer memory in an efficient manner which further support faster and more flexible data manipulations.


The python interpreter offers the following built-in data structures:


- List
- Set
- Tuple
- Dictionary


Data Structures in Python

https://www.geeksforgeeks.org/vectorization-in-python/

Vectorization in python

Vectorization is a computational technique used to replace explicit, element-by-element loops (such as Python for-loops) with optimized operations on entire data structures simultaneously. In machine learning, vectorization leverages highly optimized linear algebra libraries to perform mathematical operations—like calculating the elementwise sum of vectors or processing whole minibatches of examples—at once. This approach dramatically reduces execution time by yielding order-of-magnitude speedups, simplifies code, reduces the potential for bugs, and increases portability by offloading mathematics to underlying libraries.

Learn Before

Related

Learn After