Outlines

• Writing Basic Python functions
• Some built-in Python functions
• Load Python modules
• Function arguments
• Lambda function
• Scope of a function
• Multiple return value
• Prepare your own function module
• Install Python modules
• Python environment (optional)

Writing Basic Python functions

• function without argument

def hello():
    print('Hello World!')

hello()

## Hello World!

• function with an argument

def hello(name):
    print('Hello, ' + name + "!")

hello("Lucas")

## Hello, Lucas!

Function Descriptions and Helps

def inc(x): 
  """Increase by one
  
  Keyword arguments:
  x -- the base number to be increased
  """
  return x + 1

inc(3)

## 4

inc.__doc__ ## check docstring

## 'Increase by one\n  \n  Keyword arguments:\n  x -- the base number to be increased\n  '

• get help page

?inc
help(inc)

Function structure

• Keyword "“def”" that marks the start of the function
• (optional) Parameters (arguments) to pass values to a function.
• A colon (:) to mark the end of the function header.
• (Optional) Documentation string (docstring) to describe what the function does.
• The function body must have same indentation for the same level of code.
• (Optional) Return statement to return a value from the function.

Recursive function

• \(f(n) = n! = n(n-1)\ldots 1\)

def factorial(n):
    result = n
    for i in range(1,n):
        result *= i
    return result

factorial(5)

## 120

• recursive function

def factorial(n):
    if n==1: return 1
    return n*factorial(n-1)

factorial(5)

## 120

In class exercise

• Write a recursive function to calculate the Fibonacci number
  • f(0) = 1
  • f(1) = 1
  • f(2) = f(1) + f(0) = 2
  • f(3) = f(2) + f(1) = 3
  • f(4) = f(3) + f(2) = 5
  • …
  • f(n) = f(n-1) + f(n-2)

def fibonacci(n):
    if(n<=1):
        return(1)
    else:
        return(fibonacci(n-1) + fibonacci(n-2))

fibonacci(4)

## 5

fibonacci(5)

## 8

Some built-in Python functions

abs(-4)

## 4

pow(2,3)

## 8

round(3.14)

## 3

max(6,9)

## 9

min([1,2,3,7])

## 1

sum(range(10))

## 45

help(sum)

## Help on built-in function sum in module builtins:
## 
## sum(iterable, /, start=0)
##     Return the sum of a 'start' value (default: 0) plus an iterable of numbers
##     
##     When the iterable is empty, return the start value.
##     This function is intended specifically for use with numeric values and may
##     reject non-numeric types.

?sum ## this way only works for Jupyter Notebook

Module

• A Python module is similar to an R package
  • contains a set of functions.
• Create a module
  • put the following function in a file mymod.py

def hello(name):
    print('Hello ' + name + '!')

def myadd(a, b):
    return(a + b)

• In python

import mymod

mymod.hello("Lucas")

## Hello Lucas!

mymod.myadd(1, 10)

## 11

Module

• in addition to functions, a module can also contain data variables.
  • put the following code in the file mymod.py

Student1 = {
  "name": "Amy",
  "age": "23",
  "country": "Canada"
}

• In python

import mymod

astudent = mymod.Student1
print(astudent)

## {'name': 'Amy', 'age': '23', 'country': 'Canada'}

for akey in astudent:
        print(akey + ": " + astudent[akey])

## name: Amy
## age: 23
## country: Canada

math modules

After import module, all the objects in the module are available via module.object

import math

math.sqrt(3)

## 1.7320508075688772

math.floor(10.4)

## 10

math.ceil(10.4)

## 11

math.log(16,2)

## 4.0

math.log2(16)

## 4.0

math.pi

## 3.141592653589793

math modules

• create a shortcut name for the module

import math as m
m.pi

## 3.141592653589793

• import a specific object from a module

from math import pi
pi

## 3.141592653589793

• import multiple objects from a module

from math import pi, log2
log2(pi)

## 1.6514961294723187

os module

• os module contains functions to interacting with the operation system

import os

• get current working directory

cwd = os.getcwd() ## get current working directory
print("Current working directory is " + cwd)

## Current working directory is /Users/zhuo/Dropbox (UFL)/teaching/2022FALL/lectures/Week10_functions/functions

• list all files

os.listdir() 
## os.listdir(cwd)  same as this one

## ['.Rhistory', 'functions.py', 'functions.rmd', 'my_file.txt', 'new_file.txt', 'functions.html', '__pycache__', 'foo', 'functions', '.ipynb_checkpoints', 'mymod.py', 'tmp']

• set working directory

os.chdir('..') ## go back one folder
os.getcwd()

## '/Users/zhuo/Dropbox (UFL)/teaching/2022FALL/lectures/Week10_functions'

os.chdir(cwd) ## go back to cwd
os.getcwd()

## '/Users/zhuo/Dropbox (UFL)/teaching/2022FALL/lectures/Week10_functions/functions'

• create folders

os.mkdir("tmp") ## create a single folder
os.makedirs("foo/bar")  ## create a recursive folder

• remove files/folders

os.remove(afile) ## remove afile
os.rmdir(afolder) ## remove a folder

• join path

file = 'Untitled.ipynb'
      
# File location 
location = "/Users/zhuo/Desktop/" ## change this to your own directory
os.listdir(location)
      
# Path 

## ['.Rhistory', 's41592-021-01252-x.pdf', '.DS_Store', '.localized', 'sellingPoints.txt', 'shiny-examples', 'others', 'circadianWebsite', 'reference.pdf', 'env', 'bbaa257.pdf', 'test2022', 'update_20220401.txt']

path = os.path.join(location, file) 
print(path)

## /Users/zhuo/Desktop/Untitled.ipynb

• file/folder exists

os.path.exists(location) 

## True

os.path.exists(path) 

## False

os.path.isfile(path) 

## False

os.path.isdir(location) 

## True

random module

• the random module allows to generate random numbers
  • random(): random number between 0 and 1

import random

print(random.random())

## 0.5228940589963078

• same random seed will allow reproducible results

random.seed(10)
print(random.random())

## 0.5714025946899135

random.seed(10)
print(random.random())

## 0.5714025946899135

random integer

• randomint(a,b): random integer between a (inclusive) and b(inclusive)

print(random.randint(1, 3))

## 2

• randomrange(a,b): random integer between a (inclusive) and b(exclusive)

print(random.randrange(1, 3))

## 2

random choices and shuffle

• random.choice: choose one from a list

mylist = ["apple", "banana", "cherry"]
random.choice(mylist)

## 'cherry'

• random.choices: choose k from a list

random.choices(mylist, k = 2)

## ['apple', 'banana']

• random.shuffle: shuffle the order (inplace operator)

random.shuffle(mylist)
mylist

## ['apple', 'cherry', 'banana']

Default arguments

def add(arg1 = 1, arg2 = 2):   
    return(arg1 + arg2)

add(arg1 = 3, arg2 = 4)

## 7

add(arg1 = 3)

## 5

add()

## 3

Function arguments matching rule

def parrot(voltage, state='a stiff', action='voom'):
    print("-- This parrot wouldn't", action, end=' ') ## end will switch from a new line to a whitespace
    print("if you put", voltage, "volts through it.")
    print("-- It's", state, "!")

parrot(1000)                                          # 1 positional argument

## -- This parrot wouldn't voom if you put 1000 volts through it.
## -- It's a stiff !

parrot(voltage=1000)                                  # 1 keyword argument

## -- This parrot wouldn't voom if you put 1000 volts through it.
## -- It's a stiff !

parrot(voltage=1000000, action='VOOOOOM')             # 2 keyword arguments

## -- This parrot wouldn't VOOOOOM if you put 1000000 volts through it.
## -- It's a stiff !

additional matching rules

def parrot(voltage, state='a stiff', action='voom'):
    print("-- This parrot wouldn't", action, end=' ') ## end will switch from a new line to a whitespace
    print("if you put", voltage, "volts through it.")
    print("-- It's", state, "!")

parrot(action='VOOOOOM', voltage=1000000)             # 2 keyword arguments

## -- This parrot wouldn't VOOOOOM if you put 1000000 volts through it.
## -- It's a stiff !

parrot('a million', 'bereft of life', 'jump')         # 3 positional arguments

## -- This parrot wouldn't jump if you put a million volts through it.
## -- It's bereft of life !

parrot('a thousand', state='pushing up the daisies')  # 1 positional, 1 keyword

## -- This parrot wouldn't voom if you put a thousand volts through it.
## -- It's pushing up the daisies !

Extra arguments

• a motivting example

• two input

def add(a,b):
  return(a + b)

• four input

def add(a,b,c,d):
  return(a + b + c + d)

• how about the number of input is unknown?

Extra arguments

• *params: any extra arguments for the function
  • pass as tuple

def print_args(*args):
    print(args)

print_args('Testing') ## tuple of length 1

## ('Testing',)

print_args(1,2,3)

## (1, 2, 3)

def print_args_2(title, *args):
    print(title)
    print(args)

print_args_2("Args:", 1,2,3)

## Args:
## (1, 2, 3)

print_args_2("Nothing:")

## Nothing:
## ()

In class exercise

• Write a function add(), which can take an arbitrary number of argument input,
• The function will return the sum of these argument
• The result we would expect:

add(1,2,3,4,5) # 15
add(1,2,3,4,5,6,7,8,9,10) # 55

def add(*args):
    print(type(args)) ## the input args forms a tuple
    sum = 0
    for n in args:
        sum += n
    return sum

add(1,2,3,4,5) # 15

## <class 'tuple'>
## 15

add(1,2,3,4,5,6,7,8,9,10) # 55

## <class 'tuple'>
## 55

Extra keywords

• must specify the name of the keywords (e.g., x=1)
  • pass as dict

def print_keywords_3(**keywords):
    print(keywords)

print_keywords_3(x=1,y=2,z=3)

## {'x': 1, 'y': 2, 'z': 3}

def print_keywords_4(**keywords):
    for kw in keywords:
        print(kw, ":", keywords[kw])
print_keywords_4(x=1,y=2,z=3)

## x : 1
## y : 2
## z : 3

def print_params_4(x,y,z=3,*pospar, **keypar):
    print(x,y,z)
    print(pospar)
    print(keypar)

print_params_4(x=1,y=2)

## 1 2 3
## ()
## {}

print_params_4(1,2,3,5,6,7,foo=1)

## 1 2 3
## (5, 6, 7)
## {'foo': 1}

Assertion

• assertion:
  • the assert keyword
  • the expression/condition to test
  • an optional message
  • put assertion at the beginning of a function to verify arguments

assert expression[, assertion_message]

number = 1 ## try -1 as well
assert number > 0
assert number > 0, f"number greater than 0 expected, got: {number}"

• can also integrate with try-expect statement to capture “AssertionError”

Lambda function

• a small anonymous function.
• can take any number of arguments, but with only one expression.

def f1(x):
    return(x + 10)

f1(5)

## 15

f2 = lambda x : x + 10

f2(5)

## 15

(lambda x : x + 10)(5)

## 15

Lambda function with more than 1 argument

def f3(a,b):
  return(a*b)

f3(5,6)

## 30

f4 = lambda a, b : a * b
print(f4(5, 6))

## 30

Function scopes

• Global Scope
  • A variable created in the main Python code belongs to the global scope.
  • Global variables are available for both global and local.

x = 300

def afun():
  print(x)

afun()

## 300

print(x)

## 300

Function scopes

• Same variable names
  • If you have the same variable name inside and outside of a function,
    • one available in the global scope (outside the function)
    • one available in the local scope (inside the function):

x = 300

def afun():
  x = 200
  print(x)

afun()

## 200

print(x)

## 300

Function scopes

• Global Keyword
  • If you want a local variable to be in the global scope, you may want to use the global keyword

def bfun():
  global x
  x = 50

bfun()
print(x)

## 50

x = 50

def bfun():
  global x
  x = 60

bfun()
print(x)

## 60

Multiple return values

def f23(x):
    x_square = x**2
    x_cubic = x**3
    res_tuple = (x_square, x_cubic)
    return(res_tuple)

f23(3)

## (9, 27)

a, b = f23(5)
print(a)

## 25

print(b)

## 125

Other looping technique

• parallel iteration

d = ["a", "b", "c"]
e = [1, 2, 3]

zip(d,e)

## <zip object at 0x110958980>

list(zip(d,e))

## [('a', 1), ('b', 2), ('c', 3)]

for i, j in zip(d,e):
    print(i + str(j))

## a1
## b2
## c3

• enumerated iteration

for index, string in enumerate(d):
    print(string + str(index))

## a0
## b1
## c2

list comprehension

• List comprehension provides a short syntax to create a new list based on an existing list

squares = []
for x in range(10):
    squares.append(x**2)

squares

## [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

• put everything in one line

[x**2 for x in range(10)]

## [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

list comprehension

• two variable list comprehension

[(i,j) for i in range(3) for j in range(3)]

## [(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)]

• print even number only

[i for i in range(10) if i%2==0 ]

## [0, 2, 4, 6, 8]

• subsetting

names = ["Amy", "Beth", "Carl"]
[aname[0] for aname in names]

## ['A', 'B', 'C']

list comprehension for dictionary

• list comprehension for dictionary

names = ["Amy", "Beth", "Carl", "Dan", "Emily", "Frank"]

import random

students_scores = {name: random.randint(0, 100) for name in names}

students_scores

## {'Amy': 83, 'Beth': 20, 'Carl': 4, 'Dan': 66, 'Emily': 62, 'Frank': 41}

Install new packages

• pip
  • it is included by default with the Python binary installers.
• conda
  • alternative way to install packages, Conda lets you easily switch between environment on your local computer

pip install packages

• macOS or linux user
  • in the terminal
  • pip == python -m pip
  • python (default python), python3 (default version for python3), python 3.9 (python version 3.9)

python -m pip install numpy
>>> import numpy as np ## test if the package has been installed in python
python3 -m pip install numpy==1.23 ## specifying a package version
python3.9 -m pip install --upgrade numpy ## upgrade a package
pip install numpy --user ## if you are not a admin

• windows user
  • in the terminal

py -3 -m pip install numpy
>>> import numpy as np ## test if the package has been installed in python
py -3 -m pip install numpy==1.23 ## specifying a package version
py -3 -m pip install --upgrade numpy ## upgrade a package
py -3 -m pip install numpy --user ## if you are not a admin

• you could change numpy to other Python package name

conda install packages

• Anaconda
  • with over 1500 scientific packages automatically installed at once
• Miniconda (recommended in this class)
  • need to install individual packages
• install conda:
  • https://docs.conda.io/en/latest/miniconda.html
• after installation

conda install numpy
conda install numpy=1.16
conda list --name numpy conda ## check current installed version
conda update numpy

Python environment (using conda)

• With environment,
  • you can install different version of Python packages independent of the admin user.
• how to create an environment
  • in the terminal

conda create -n myenv
## conda create -n myenv python=3.9 ## create an environment with a specific Python version.
conda activate myenv ## activate the environment
conda info --envs ## list all environment
conda install -n myenv scipy=0.17.3
python ## open python with this environment
conda deactivate

Python environment (using pip)

• https://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/26/python-virtual-env/

Reference

• https://docs.python.org/3/index.html
• https://github.com/Apress/beginning-python-3ed
• https://www.programiz.com/python-programming/function
• https://www.geeksforgeeks.org/os-module-python-examples/
• https://www.w3schools.com/python/python_modules.asp
• https://docs.python.org/3/installing/index.html
• https://towardsdatascience.com/manage-your-python-virtual-environment-with-conda-a0d2934d5195