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
A colon (:) to mark the end of the function header.
The function body must have same indentation for the same level of code.
(Optional)
- Documentation string (docstring) to describe what the function does.
- Parameters (arguments) to pass values to a function.
- 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) ## 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/2023FALL/lectures/Week10_functions/functions

list all files

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

## ['.Rhistory', 'functions.py', 'functions.rmd', '.DS_Store', 'functions.html', '__pycache__', '.ipynb_checkpoints', 'mymod.py', 'tmp']

set working directory

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

## '/Users/zhuo/Dropbox (UFL)/teaching/2023FALL/lectures/Week10_functions'

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

## '/Users/zhuo/Dropbox (UFL)/teaching/2023FALL/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', 'fdgth-03-727504.pdf', 'Screen Shot 2023-09-28 at 8.55.01 AM.png', '~$deed.docx', 'BayesianCircadianSlides.pptx', 'GatorPKG', 'drugs and insurance.txt', '.DS_Store', 'Jupyter_note.PNG', 'PIIS0092867421003792.pdf', 'LOI.pdf', 'NFWF_Data_Management_and_Access_Plan.pdf', 'GrantApplication.pdf', '.localized', 'Untitled.ipynb', 'Gator2022', 'example', 'Screen Shot 2023-10-18 at 11.22.40 AM.png', 'Screen Shot 2023-10-02 at 3.55.26 PM.png', 'Ding_GA-Work-Schedule.pdf', 'shiny-examples', 'Screen Shot 2023-10-10 at 11.36.11 AM.png', 'others', 'circadianWebsite', 'wga.pdf', '2024_Dental_Monthly_Premium_Chart.pdf', 'This manuscript studies the potential causal relationship between sleep behavior and renal outcomes.docx', 'budget_justification_SOMOA_Huo 051823.pdf', 'Screen Shot 2023-09-21 at 1.38.12 PM.png', 'chatGPT.txt', 'budget_justification_SOMOA_Huo 051823 (1).pdf', 'YCR-2021-2022-AcademicSalaryReport.pdf', 'Auto-GPT', 'JEV template (1).pdf', 'Action Required_ Proposal SFI Certification Requested PI_ Esser.eml', 'openAI_key.txt', 'Committee_Change_Form_Dongyuan.pdf', 'Personalized glucose respoinses Naef Cell Reports 08042023.pdf', 'eamm', 'bbaa257.pdf', '.ipynb_checkpoints', 'Screen Shot 2023-10-04 at 12.50.24 PM.png', 'J American Geriatrics Society - 2018 - Rogers‐Soeder - Rest‐Activity Rhythms and Cognitive Decline in Older Men  The.pdf', 'Mail - Huo,Zhiguang - Outlook_files', '2024_Dental_Plan_Comparison_(Final).pdf', 'Screen Shot 2023-10-05 at 10.23.28 AM.png', 'Screen Shot 2023-09-21 at 1.38.20 PM.png', 'Screen Shot 2023-10-10 at 11.35.17 AM.png', 'thumbnail_image.png']

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)

## True

os.path.isfile(path)

## True

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())

## 0.16687382761630964

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(arg, brg=["a", "b"], crg='python'):
    print("arg: " + str(arg))
    print("brg: " + str(brg))
    print("crg: " + str(crg))

parrot(1000)                             # 1 positional argument

## arg: 1000
## brg: ['a', 'b']
## crg: python

parrot(arg=1000)                         # 1 keyword argument

## arg: 1000
## brg: ['a', 'b']
## crg: python

parrot(arg=1000000, crg='R')             # 2 keyword arguments

## arg: 1000000
## brg: ['a', 'b']
## crg: R

additional matching rules

parrot(crg='JAVA', arg=1000000)             # 2 keyword arguments

## arg: 1000000
## brg: ['a', 'b']
## crg: JAVA

parrot(32611, [1,2,3], "C++")         # 3 positional arguments

## arg: 32611
## brg: [1, 2, 3]
## crg: C++

parrot(567, brg=list("abc"))  # 1 positional, 1 keyword
# parrot(brg=list("abc"), 567)  # 1 positional, 1 keyword, doesn't work

## arg: 567
## brg: ['a', 'b', 'c']
## crg: python

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) ## to receive multiple return values
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 0x119aa1e40>

list(zip(d,e))

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

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

## a1
## b2
## c3

iterable object

a = zip(d,e)
next(a)

enumerated iteration: a tuple of index and the original object

d = ["a", "b", "c"]
for index, string in enumerate(d):
    print(string + str(index))

## a0
## b1
## c2

list(enumerate(d))

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

x = enumerate(d) ## iterable object
next(x)

## (0, 'a')

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

Install in jupyter notebook (best practice to avoid confusion)

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

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

How to prepare your own package, and make it installable using pip

https://packaging.python.org/en/latest/tutorials/packaging-projects/

Python environment

With environment,
- you can install different version of Python packages independent of the admin user.
how to create an environment
- using anaconda software (user friendly interface)
- in the terminal using conda

## source ~/opt/miniconda3/bin/activate ## need this for macOS Catalina or later
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

Programming basics for Biostatistics 6099

functions and modules

Outlines

Writing Basic Python functions

Function Descriptions and Helps

Function structure

Recursive function

In class exercise

Some built-in Python functions

Module

Module

math modules

math modules

os module

random module

random integer

random choices and shuffle

Default arguments

Function arguments matching rule

Extra arguments

Extra arguments

In class exercise

Extra keywords

Assertion

Lambda function

Lambda function with more than 1 argument

Function scopes

Function scopes

Function scopes

Multiple return values

Other looping technique

list comprehension

list comprehension

list comprehension for dictionary

Install new packages

pip install packages

conda install packages

How to prepare your own package, and make it installable using pip

Python environment

Python environment (using pip)

Reference