10. Introduction to Python¶

Python in Linux
Conda environment
Python programming environment: Jupyter notebook
Variabls
Data types
Operators
Data collections: lists, tuples, dictionariees
Loops
Conditionals
Functions
Executable python scripts
Files

10.1. Python on Linux¶

Python comes with Linux distro, however, the version maybe too old.

which python3

/usr/bin/python3

Python modules can be installed with apt, for example

sudo apt install python3-numpy

Alternatively, modules can be installed with pip3 command in the user’s home directory:

sudo apt install python3-pip

See installed modules:

pip3 list

Install module numpy:

pip3 install numpy

Check out the package description:

pip3 show numpy

Uninstall module numpy:

pip3 uninstall numpy

10.2. Conda environment (Exercise)¶

To get the latest python in the user home directory with all needed modules, use Conda.
Miniconda installation instructions

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh

After installing, initialize your newly-installed Miniconda:

~/miniconda3/bin/conda init bash

Activate the Conda environment:

source .bashrc

See what Python is used now:

which python3

It should be in th Conda environment now.

To deactivate the Conda environment, run:

conda deactivate

To activate it again:

conda activate

Search Python modules:

conda search jupyter

10.3. Python programming environment: Jupyter notebook (Exercise)¶

Install Jupyter notebook on your desktop as user hostadm:

conda install jupyter

Assign the password to jupyter notes by running command:

jupyter notebook password

Create directory for python projects, and step into the directory:

mkdir Python
cd Python

Start jupyter notes by command below:

jupyter notebook &

Access jupyter notebook through the browser on your virtual desktop by navigating to URL below:

jupyter

http://localhost:8888

Start a new python3 project in the jupyter notebook.

This is a Jupyter Notebook.

This computational tool allows for Python programming in a web browser without having to use a multi-window environment. You can write and run your code all in one sitting.

print("Hello, World")

print('Hello, World')

#Press `<shift>-<Enter>` keys to execute the script in the jupyter cell.

Hello, World
Hello, World

Coding SYNTAX in critical. 4, 4.0, and ‘4’ all mean the something different.

VARIABLES are used to stored information, such as numbers, integers, strings, lists, arrays, and databases. Be careful not to overuse the same variable- you can overwrite stored data.

Use three variables on the list of 4’s mentioned above.

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

a = 4
b = 4.0
c = "4"
print(c)

10.4. Python built-in data types¶

In programming, data type is a critical concept.

Variables can store data of different types, and different types can do different things.

Python has the following data types built-in by default, in these categories:

Text Type: str
Numeric Types: int, float, complex
Sequence Types: list, tuple, range
Mapping Type: dict
Set Types: set, frozenset
Boolean Type: bool
Binary Types: bytes, bytearray, memoryview

Revisit the multiple 4’s used earlier to see those data types.

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

print(a)
type(a)

int

print(c)
type(c)

str

print(b)
type(b)

4.0

float

There are three numeric types in Python:

int
float
complex

Variables of numeric types are created when you assign a value to them. You can convert from one type to another with the int(), float(), and complex() methods:

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

d = 4.50
type(d)

float

d = int(d)
print(d)
type(d)

int

10.5. Python Operators¶

Operators are used to perform operations on variables and values. But pay attention: values used MUST share data types and some cannot work with int types

Operator	Name	Example
+	Addition	x + y
-	Subtraction	x - y
*	Multiplication	x * y
/	Division	x / y
%	Modulus	x % y
**	Exponentiation	x ** y
//	Integer division	x // y

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

14.04 / 5.0

2.808

14.04 % 5.0

4.039999999999999

14.04 // 5.0

2.0

x = 5.00
y = 12.98

A = x + y
B = x - y 
C = x * y

print(A)
print(B)
print(C)

17.98
-7.98
64.9

# You do NOT have to work with only values, you can use variables in your operations!

x = "5"
y = float(12.98)

A = x + y
B = x - y 
C = x * y

print(A)
print(B)
print(C)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-6-308c42a7557f> in <module>
      4 y = float(12.98)
      5 
----> 6 A = x + y
      7 B = x - y
      8 C = x * y

TypeError: can only concatenate str (not "float") to str

# The type matching fixes it:
x = "5"
y = float(12.98)

A = x + str(y)

print(A)
type(A)

512.98

str

10.6. String concatenation¶

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

A = 'This'
B = 'is'
C = 'a string'

D = A + ' ' + B + ' ' + C + ' indeed'

print(D)

This is a string indeed

10.6.1. Better way is to use the f-string operator¶

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

D = f'{A} {B} {C} indeed'

print(D)

This is a string indeed

10.7. Additional Python Operators¶

10.7.1. Assignments:¶

Operator	Example	Same as…
=	x = 5	x = 5
+=	x += 3	x = x + 3
-=	x -= 3	x = x - 3
*=	x *= 3	x = x * 3
/=	x /= 3	x = x / 3
%=	x %= 3	x = x % 3
//=	x //= 3	x = x // 3
**=	x **= 3	x = x ** 3

10.7.2. Comparisons:¶

Operator	Name	Example
==	Equal	x == y
!=	Not equal	x != y
>	Greater than	x > y
<	Less than	x < y
>=	Greater than or equal to	x >= y
<=	Less than or equal to	x <= y

10.7.3. Logical:¶

Operator	Example	Same as…
and	Returns True if both statements are true	x < 5 and x < 10
or	Returns True if one of the statements is true	x < 5 or x < 4
not	Reverse the result, returns False if the result is true	not(x < 5 and x < 10)

Press <shift>-<Enter> keys to execute the script in the jupyter cell.

x = 5.0
print(x)

x += 5.0
print(x)

x -= 4.5
print(x)

0
0
5

x = 5
y = "5"

x == y

False

x = 5
y = 16

not(x < 10 or y < 10)

False

d = x<10
print(d)

True

10.8. Python Collections¶

There are four collection data types in the Python programming language:

List is a collection which is ordered and changeable. Allows duplicate members.

Tuple is a collection which is ordered and unchangeable. Allows duplicate members.

Set is a collection which is unordered and unindexed. No duplicate members.

Dictionary is a collection which is unordered, changeable and indexed. No duplicate members.
When choosing a collection type, it is useful to understand the properties of that type. Choosing the right type for a particular data set could mean retention of meaning, and, it could mean an increase in efficiency or security.

10.8.1. List¶

A list is a collection which is ordered and changeable. In Python lists are written with square brackets. A list can contain different data types. A list can be made by either setting up array with the square brackets or by using the list() constructor.

test_list = [4, 4.0, "4"]

print(test_list)

[4, 4.0, '4']

List items can be accessed through indexing. The list’s index is the numbered placement an element is within the list.

NOTE: Indexing in python starts at 0, not 1. This means that the first item of a list is the 0th index.

You can access items of a list at specific index values, both positive or negative and can even access a range of entries by slicing the list.

test_list[0]

thislist = ["apple", "banana", "cherry", "orange", "kiwi", "melon", "mango"]

print(thislist[3]) # this is the FOURTH item in our list

orange

Some great list methods to work with:

Method	Description
append()	Adds an element at the end of the list
clear()	Removes all the elements from the list
copy()	Returns a copy of the list
count()	Returns the number of elements with the specified value
extend()	Add the elements of a list (or any iterable), to the end of the current list
index()	Returns the index of the first element with the specified value
insert()	Adds an element at the specified position
pop()	Removes the element at the specified position
remove()	Removes the item with the specified value
reverse()	Reverses the order of the list
sort()	Sorts the list

# To change the value of a specific item, refer to the index number:
thislist[1] = "pineapple"
print(thislist)
print()

['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango']

# To add an item to the end of the list, use the append() method:
thislist.append("banana")
print(thislist)
print()

['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango', 'banana']

# To add an item at the specified index, use the insert() method:
thislist.insert(1, "tomato")
print(thislist)
print()

['apple', 'tomato', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango', 'banana']

# The remove() method removes the specified item:
thislist.remove("tomato")
print(thislist)
print()

['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango', 'banana']

# The del keyword removes the specified index:
del thislist[7]
print(thislist)
print()

['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango']

# You can JOIN two lists by using either '+' or append()

list1 = ["a", "b" , "c"]

list2 = [1, 2, 3]

list3 = list1 + list2

list4 = list2 + list1

print(list3)
print()
print(list4)

['a', 'b', 'c', 1, 2, 3]

[1, 2, 3, 'a', 'b', 'c']

list1 = list1 + ["d"]

print(list1)

['a', 'b', 'c', 'd']

10.9. Dictionaries¶

A list stores items, but if you want to store items based on specific indicators, you can use a dictionary. A dictionary is accessed based on the “key” and once it finds that key, it will access and use the “value” associated with it. This of the key as the word you want to learn about in an actual dictionary and its definition is its value.

Dictionary items are ordered, changeable, can be of any data type, and does not allow duplicate keys (one can, however, have duplicated values).

Dictionary items are presented in key:value pairs, and can be referred to by using the key name.

Dictionaries are changeable, meaning that we can change, add or remove items after the dictionary has been created.

food_dictionary = {'mango':4,
                   'banana':2,
                   'apple':19}

print(food_dictionary)

{'mango': 4, 'banana': 2, 'apple': 19}

# Now that a dictionary has been made, how do you access it?

print(food_dictionary['banana'])

10.10. Loops¶

But how can I make a list: You can use a LOOP.

A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string). This is less like the for keyword in other programming languages, and works more like an iterator method as found in other object-orientated programming languages.

With the for loop we can execute a set of statements, once for each item in a list, tuple, set etc.

The types of loops you can work with include:

for loops
if/else loops, where “if” a condition is met, do A; if another condition is met, do B
while loops, where you do A repeatedly until a condition is met

print(list1)
print(list2)

for x in list1:
    list2.append(x)

print(list2)

['a', 'b', 'c', 'd', 'd']
[1, 2, 3]
[1, 2, 3, 'a', 'b', 'c', 'd', 'd']

list2.clear()
print(list2)

[]

# Add some items to a list using a for loop
thislist

grocery_list = []

for item in thislist:
    grocery_list.append(item)
    
print(thislist)
print(grocery_list)

['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango']
['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango']

thislist

grocery_list = []

for item in thislist:
    
    if item != "mango":
    
        grocery_list.append(item)
    
print(thislist)
print(grocery_list)

['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon', 'mango']
['apple', 'pineapple', 'cherry', 'orange', 'kiwi', 'melon']

You can run a loop within a loop
If you want to stop the loop based on a specific condition, use “break”
If you want to keep one loop going even if it runs into an issue with another loop, use “continue”
Unsure how many times you need to iterate over? Try “range()”

for i in range( len(grocery_list) ):
    print(i)
    print(grocery_list[i])

0
apple
1
pineapple
2
cherry
3
orange
4
kiwi
5
melon

A “Pythonic” way to make lists less bulky is to use list comprehension, which offers a shorter syntax when you want to create a new list based on the values of an existing list.

With list comprehension, you are building a loop in a single line

list1 = ['a','b','c','d','e']

list2 = [ list1[i] for i in range(len(list1)) ]
print(list2)

list3 = [ list1[i] for i in range(len(list1)) if i!=2 ]
print(list3)

['a', 'b', 'c', 'd', 'e']
['a', 'b', 'd', 'e']

10.11. Conditionals¶

a = 5
b = 10
a == b
a == 5

True

output = 'False statement'
if a > 5:
    output = 'true statement'
    s =23
    st = 'value'
    
elif b == 11:
    output = 'elseif block'
    print(output)

else:
    output = 'entered false block'
    print(output)

entered false block

10.12. Functions¶

def f():
    print(f'function f')

Use function in the main code:

f()

function f

Positional arguments:

def f(x, y):
    print(f'x = {x}')
    print(f'y = {y}')
    print(f'sum = {x + y}')

a = 14
b = 36
f(a, b)

x = 14
y = 36
sum = 50

10.12.1. Default parameters:¶

def f( x = 10, y = 3 ):
    print(f'x = {x}')
    print(f'y = {y}')
    print(f'sum = {x + y}')
    
a = 14
b = 36
f(a, 2330)

x = 14
y = 2330
sum = 2344

10.12.2. Immutable arguments: int, float, str, tuples:¶

def f(x):
    y = x ** 2
    x = y
    print(f'x in the function: {x}')

x = 5

f(x)

print(f'x in the colling main: {x}')

x in the function: 25
x in the colling main: 5

10.12.3. Mutable arguments:¶

def f(x):
    x[0] = '---'

my_list = ['this', 'one', 'will', 'change']

f(my_list)

print(my_list)

['---', 'one', 'will', 'change']

10.12.4. Return statement:¶

def compute(x, y):
    s = x + y
    return s

a = 20
b = 30
sum = 40
sum = compute(a,b)

print(sum)

10.12.5. Multiple positional argument packing:¶

def f(*args):
    print(args)
    print(type(args), len(args))
    for x in args:
         print(x)

f(4,6,8,10,23,34)

(4, 6, 8, 10, 23, 34)
<class 'tuple'> 6
4
6
8
10
23
34

tp=(1,4,5,6,4,6,7,8,10)
f(*tp)

(1, 4, 5, 6, 4, 6, 7, 8, 10)
<class 'tuple'> 9
1
4
5
6
4
6
7
8
10

10.12.6. Calculate area¶

Shape Rectangle: \(S = a \cdot b\)

Shape Circle: \(S = \pi \cdot r^2\)

def S(shape,a,b,r):
    if shape == 'rectangle':
        return a * b
    elif shape == 'circle':
        return 3.1415 * r * r
    else:
        print('unknown shape')

Area = S('rectangle', 2,3,0)
print(Area)

Area = S('circle', 0, 0, 3)

print(Area)

28.2735

10.12.7. Create a python script¶

Save the cells in file area.py.
Make the file executable and runnable in the bash shell.
To make it runnable by python, put this to the top in the file: #!/usr/bin/env python3
Import area as a module in the new cell.
Eliminate statement execution by using if __name__ == '__main__' directive.
Move area.py into new directory, Modules.
Modify sys.path to include directory Modules.

import area

area.S('circle',0,0,4)

10.13. Reading from and writing in files from Python¶

open() and close() methods
Reading files into variables and lists
Writing variables and lists into files
with statement to read/write and assumed open()/close()

Opening a file for read or write:

f = open(file, mode)

Modes include:

“r” - Read - Default value. Opens a file for reading, error if the file does not exist
“a” - Append - Opens a file for appending, creates the file if it does not exist
“w” - Write - Opens a file for writing, creates the file if it does not exist
“x” - Create - Creates the specified file, returns an error if the file exist

In addition to these modes, there are important white space characters that are paired with an “escape” character. You may need to use them to be very specific in how you read or write your files. Examples include:

’ \’ ’ or ’ " ’ maintains quotation marks within a defined string
’ \t ’ is a tab space, which is four spaces in code language
’ \n ’ is a new line, which moves the next string of text to the next line

10.13.1. Writing a list into a file:¶

grocery_list = ['apples 4', 'pineapple 1', 'cherries 10', 'orange 1', 'kiwi 12', 'melons 3 ', 'mangos 6']

f = open('grocceries.txt', 'w')

for item in grocery_list:
    f.write(item + "\n" )
    
f.close()

10.13.2. Check if file grocceries.txt was created:¶

%ls *.txt

grocceries.txt

10.13.3. Reading from a file:¶

f = open('grocceries.txt', 'r')

data = f.readlines()

f.close()

print(data)

['apples 4\n', 'pineapple 1\n', 'cherries 10\n', 'orange 1\n', 'kiwi 12\n', 'melons 3 \n', 'mangos 6\n']

data = [i.rstrip('\n') for i in data]

print(data)

['apples 4', 'pineapple 1', 'cherries 10', 'orange 1', 'kiwi 12', 'melons 3 ', 'mangos 6']

10.13.4. Opening, reading, and closing a file in one command:¶

with open("grocceries.txt", 'r') as f:
    data = f.readlines()
    
print(data)

['apples 4\n', 'pineapple 1\n', 'cherries 10\n', 'orange 1\n', 'kiwi 12\n', 'melons 3 \n', 'mangos 6\n']

10.13.5. Alternative approach with a loop:¶

lines = []
with open("grocceries.txt", 'r') as f:
    for line in f: 
        line = line.rstrip('\n') 
        lines.append(line) 
        
print(lines)

['apples 4', 'pineapple 1', 'cherries 10', 'orange 1', 'kiwi 12', 'melons 3 ', 'mangos 6']

Computing Environment

Introduction to Python

Contents

10. Introduction to Python¶

10.1. Python on Linux¶

10.2. Conda environment (Exercise)¶

10.3. Python programming environment: Jupyter notebook (Exercise)¶

10.4. Python built-in data types¶

10.5. Python Operators¶

10.6. String concatenation¶

10.6.1. Better way is to use the f-string operator¶

10.7. Additional Python Operators¶

10.7.1. Assignments:¶

10.7.2. Comparisons:¶

10.7.3. Logical:¶

10.8. Python Collections¶

10.8.1. List¶

10.9. Dictionaries¶

10.10. Loops¶

10.11. Conditionals¶

10.12. Functions¶

10.12.1. Default parameters:¶

10.12.2. Immutable arguments: int, float, str, tuples:¶

10.12.3. Mutable arguments:¶

10.12.4. Return statement:¶

10.12.5. Multiple positional argument packing:¶

10.12.6. Calculate area¶

10.12.7. Create a python script¶

10.13. Reading from and writing in files from Python¶

10.13.1. Writing a list into a file:¶

10.13.2. Check if file grocceries.txt was created:¶

10.13.3. Reading from a file:¶

10.13.4. Opening, reading, and closing a file in one command:¶

10.13.5. Alternative approach with a loop:¶