Python 1-3

Functions, documentaion, strings, files

Functions

• def to create your function

• calling your function (arguments)

• docstrings

• named arguments

What are functions?

• A Function is a named sequence of statements which accomplish a task. They promote modularity, making our code less complex, easier to understand and encourage code-reuse.

• When you “run” a defined function it’s known as a function call. Functions are designed to be written once, but called many times.

• We’ve seen functions before:

# We call functions all the time
# input(). random.randint(), and int() are all functions!
import random
x = input("Enter Name: ")  
y = random.randint(1,10)  #random is the module, randint() is the function
z = int("9")
print(x,y,z)

tony 4 9

Function Definitions

• Functions are like their own little programs. They take input, which we call the function arguments (or parameters) and give us back output that we refer to as return values.

INPUT      -=> PROCESS     ==> OUTPUT
Function   ==> Function    ==> Function 
Arguments      Definition       Return

# Example Function
def area_of_triangle(base, height): # <== INPUTs
    area = 0.5 * base *height
    return area # <== OUTPUT

# Function call: using your function
a = area_of_triangle(10,5)
print(a)

25.0

# When you call a function you can name your arguments:
# This allows you to override the order of the arguments

# These are the same order as defined
area1 = area_of_triangle(base=10, height=5)
# Different order than defined
area2 = area_of_triangle(height=5, base=10)
print(area1, area2)

25.0 25.0

Challenge 1-3-1

Write a function called average which takes a list of numbers as input then outputs the average of the numbers sum / count

Call your function with an arbitrary list of numbers you create.

Type Hints

Types can be added to the def statement to help the caller understand what type of data the function expects. These are known as type hints

In this example the expected arguments are float and the return is float

def area_of_triangle(base: float, height: float) -> float: 
    area = 0.5 * base *height
    return area

You can see type hints in action by calling the function

Run the cell above to create the function.
In the code below, start a left paren ( to see the type hints

area_of_triangle

Docstrings

A Docstring is a multi-line comment which explains what the function does to the function caller.

The same function with type hints and docstring:

def area_of_triangle(base: float, height: float) -> float: 
    '''
    Calculates the area of a triangle given base and height
    returns the area defined as 1/2 the base times height
    '''
    area = 0.5 * base *height
    return area

You can see doc strings in action by calling the function

Run the cell above to create the function.
In the code below, start a left paren ( to see the doc string

area_of_triangle

Strings

• string slices

• string methods

• text processing

String are sequence types

You can use slice notation like with lists.

These are zero based.

var[start:stop]

Takes stop - start characters from var starting at position start

x = "fudge"
print(x[0:2]) # fu
print(x[2:5]) # dge
print(x[:4]) # fudg
print(x[:]) # fudge
print(x[:-1]) # fudg

fu
dge
fudg
fudge
fudg

String Methods

https://docs.python.org/3/library/stdtypes.html#text-sequence-type-str

Method functions attach to the string x.strip()

Common methods

strip()
upper()
lower()
find()
count()
split()
join()
replace()

# Samples
s = "this is a test"
print(s.count("is")) # 2
print(s.count("t"))  # 3
print(s.upper()[:4]) # TEST
print(s.find(" a ")) # 7
print(s.find("this")) # 9
print("   x   ".strip()) # x
print(s.replace("this","that")) # that is a test

2
3
THIS
7
0
x
that is a test

Challenge 1-3-2

Write a function called cleanup which takes a string as input and returns a “cleaned string” meaning:

• remove any ? , . or !

• strip off the whitespace from the ends

• return text in lower case

write code to call your function and test it

String Tokenization and Parsing

• Tokenization is the process of breaking up a string into words, phrases, or symbols.

  • Tokenize a sentence into words.

  • "mike is here" becomes the iterable ['mike','is','here']

• Parsing is the process of extracting meaning from a string.

  • Parse text to a numerical value or date.

  • int('45') becomes 45

# tokeniize with split()
# parse with int(), or float()

text = "30 40 90 10"
tokens = text.split()
numbers = [int(t) for t in tokens]
total = sum(numbers)
print(total)

170

# What you split on is called the delimiter:
text = "name, age, phone, gpa"
items = [ x.upper().strip() for x in text.split(',') ]
print(items)

['NAME', 'AGE', 'PHONE', 'GPA']

Files

• with statement / context manager

• reading / writing text files (all at once, line at a time)

• JSON serialization / de-serialization

Files == Persistence

• Files add a Persistence Layer to our computing environment where we can store our data after the program completes.

• Think: Saving a game’s progress or saving your work!

• When our program Stores data, we open the file for writing.

• When our program Reads data, we open the file for reading.

• To read or write a file we must first open it, which gives us a special variable called a file handle.

• We then use the file handle to read or write from the file.

• The read() function reads from the write() function writes to the file through the file handle.

# Reading From a file...
filename = "data/sample.txt"
print("=== All at once ===")
with open(filename, 'r') as handle:
    contents = handle.read()
    print(contents)

print("=== A Line at a time ===")
i = 1
with open(filename, 'r') as handle:
    for line in handle.readlines():
        print(i, line.strip())
        i += 1

=== All at once ===
This
Is
A
Sample
=== A Line at a time ===
1 This
2 Is
3 A
4 Sample

# Writing to a file
filename = "data/demo.txt"
print("=== Create file and write to it ===")
with open(filename, "w") as f:
    f.write("message!\n")

print("=== Append (add to end) of existing file ===")
with open(filename, "a") as f:
    f.write("message # 2!\n")
    

=== Create file and write to it ===
=== Append (add to end) of existing file ===

!cat demo.txt

message!
message # 2!

# Try / Except to handle FileNotFound
try:
    file = 'data/data.txt'
    with open(file,'r') as f:
        print( f.read() )
except FileNotFoundError:
    print(f"{file} was not found!")

data/data.txt was not found!

JSON and Python Dictionaries

• JSON (JavaScript Object Notation) is a standard, human-readable data format. It’s a popular format for data on the web.

• JSON Can be easily converted to lists of dictionaries using Python’s json module.

• Transferring a JSON string to Python is known as de-serializing.

• Transferring Python to a JSON string is known as serializing.

• This is easy to do in Python but challenging to do in most other languages.

# Serialize a python object as json
import json
grades = { 'CHE101' : [100,80,70], 'IST195' : [100,80,100] }
with open("data/grades.json", "w") as f:
    json.dump(grades, f, indent=4) # write grades to file as JSON

!cat data/grades.json

{
    "CHE101": [
        100,
        80,
        70
    ],
    "IST195": [
        100,
        80,
        100
    ]
}

# de-serialize some json
file = "data/stocks.json"
with open(file, "r") as f:
    stocks = json.load(f)
    
# stocks is a python object
# Deserialized from text!
for stock in stocks:
    print(stock['symbol'])

AAPL
AMZN
FB
GOOG
IBM
MSFT
NET
NFLX
TSLA
TWTR

Challenge 1-3-3

write a program to read in a string of students and gpas in one input statement like this:

mike 3.4, noel 3.2, obby 3.5, peta 3.4

and write out JSON like this:

[
    { "name" : "mike", "gpa" : 3.4 },
    { "name" : "noel", "gpa" : 3.2 },
    { "name" : "obby", "gpa" : 3.5 },
    { "name" : "peta", "gpa" : 3.4 }
]

Suggested approach:

1. input text
2. for each student split on "," from the text
3.    split the student into name and gpa 
4.    parse the gpa so its a float
5.    add the name and gpa to the list
6. write the list to students.json as JSON