Created by Tâm Lại Thị Thúy
filter() is a function to return a subset of a sequence under certain condition.
filter(function, iterable)
* Where function can be pre-defined using def or under lambda
Generators is a way of generate a small bit of information at a time to preserve the computation power instead of returning massive amount of information at the same time (iterators)
yield is used insteal of return
global variable is the way to use the globally declared variable inside of each functions
Example:
balance = 0
def deposit(n):
global balance
balance -=n
map() is a function allows you to implement some kind of function mapped to a sequence of value.
Example:
...
uppercased.append(word.upper())
…
map can be used to map the upper function to each of the word from the words[] list as follow:
uppercased = map(str.upper, words)
unpacking is a way of unpack values in a list or a dictionary without having to access to the index (of the list) or the key (of the dict)
*name_of_list**name_of_dict1.1 set() is a class that help create a list with no duplicates value
set is actually a class in python that can be accessed via set()
Example:
house = set()
house.add(student["house"])
1.2 enumerate(): is a way of getting the index value of a list
ex: range(len(students)) can be written as enumerate(students)
*args is positional argument. In a function, *args indicate that it can take any number of arguments and parse all of them to the function being used.
**kwargs is named argument or key word argument. This quite similar to *args but **kwargs require any arguments that are keyworded (i.e. a dict)
argparse is a library which comes with different functions:
add_argument()parse_args()this help to parsing all command-line arguments with specified condition. Instead of using if condition and manually iterate user args
This lecture covers many kinds of topic which are practical but have not yet been covered in previous ones.
Object Oriented Programming is a fundamental concept in Python, empowering developers to build modular, maintainable, and scalable applications
docstrings is a way of commenting your function's purpose very clearly so that it can be extracted into another file and used as documentation of your code.
Tools such as Sphinx can be use for those extraction
list is a set of values that are presented in [] and seperated by comma ","
example:
students = ["Hermione", "Harry", "Ron"]
The list() constructor can also be used to convert any type of iteratable data like string, tuples, set, dictionary into a list
list/ dict comprehension is a way of creating a list/dict on the fly without having to seperately writing a loop and append value into a list or a dict.
Example:
name = [student["name"] for student in students
if student["house"] == "Gryffindor"]
house = {student: "Gryffindor" for student in students}
dictionary is a data type that comes with keys and their values
example:
students ={
"Harry" : "Gryffindor",
"Draco" : "Slytherin",
}match = re.search(pattern, string)
if match:
process(match)
re. match() searches for matches from the beginning of a string while re.search() searches for matches anywhere in the string.
Match can be utilized to return certain specified/named groups in strings. A group can be named using
(?P<name>group_of_patterns)
Regular expressions or “regexes” will enable us to examine patterns within our code
Regex can be implemented via re library
set is a collection with no duplicates element
open function allows you to open a file to read or write to it
file = open("names.txt", "a")
Mode of open:
with open allows you to open file to read and write and handle the closing file without losing your data.
csv is a built-in Python library where it helps to handle the CSV file with functions like:
reader() or DictReader()writer() or DictWriter()Quick summary on Numpy: https://www.notion.so/Numpy-2fbe613040bc43e890f83f31cf345869?pvs=4
Pandas quick summary: https://www.notion.so/Pandas-5e6324bddb17481a8f42dd5890da6145?pvs=4
Data analysis with Pandas: https://wesmckinney.com/book/
Assert statements are a convenient way to insert debugging assertions into a program
https://docs.python.org/3/reference/simple_stmts.html#assert
reference Thu Vu Analytics
Quick summary on Matplotlib:
https://www.notion.so/Matplotlib-aa388aaa864e4c91a94c3df8c7484750?pvs=4
the f comes with some special syntax:
f"{n:02}" -> adding 0 before 1 digit number
f"{z:,}" → using comma (,) as thousand seperator
f"{z:.2f}" → rounding the number by 2 decimal points
variables are way to contain value of the program.
ex: name = input("Your name: ") is a variable contains the user's name input
functions are actions that the program performs
Ex: print("Hello, world") → print is a function which prints out the text "Hello, world"
functions take in their parameters to define correct actions
Python tutorials:
https://docs.python.org/3/tutorial/
Unit test means testing your program by each unit.
It is also suggested that your program must be written into units that are testable.
pytest is a third-party library that allows you to unit test your program
Libraries are bits of code written by you or others that can be shared and reused.
A Python module is a file containing Python definitions and statements defining functions, classes, and variables.
A Python library is a collection of related modules
def is a way to create your own function to perform customized action(s)
the def function need to be created and called on the code so that it can performed
return is the key word to get back values from def
Errors and exceptions happens when there are something wrong with the code written.
Python is somewhat a folder that contains related Python files (modules) that work together to provide certain functionality
PyPI is a repository or directory of all available third-party packages currently available.
Some useful packages:
PEP 8 (Python Enhancement Proposal) - writing code with readability and consistency
pylint
the while loops are used to repeat certain actions
example:
i = 1
while i ≤ 3:
print("hello")
i +=1
for loops are used for looping through a list or a range with each element of that list/range get assigned to the variable
ex:
for i in [0,1,2]
or
for i in range(3)
sys is a module allowing to take arguments at the command line.
argv is a function within the sys module that allows us to learn about what the user typed in at the command line.
More about sys
if statement use boolean or bool values (True or False) to decide whether or not to execute
elif, else enable logic flow to check certain conditions in code before excecute and return expected values
or, and are also used alongside to group some conditions
try and except are ways of testing out user input before something goes wrong.
except comes with specific type of errors that need to handled.
else can also be used to improve the flow of code.
raise allows the programmer to force a specified exception to occur
This module provides functions for calculating mathematical statistics of numeric (Real-valued) data
match statements can be used to conditionally run code match certain values
ex:
match variable:
case "var1":
print("value1")
case "var2":
print("value2")
Source from Thu Vu Analytics
import random
https://docs.python.org/3/library/random.html
If package is a part of standard library, it can be imported via:
# import whole package
import random
# import specific functions/ modules
from random import choice
If package is not standard, it need to be installed first via package manager like pip or conda
i.e. pip install panda
Arithmetic operators are used with numeric values to perform common mathematical operations:
Membership operators are used to test if a sequence is presented in an object:
Bitwise operator in Python that acts on bits and performs bit-by-bit operations
Comparison operators are used to compare 2 values:
Indentity operators are used to compare the objects, not if they are equal, but if they are actually the same object, with the same memory location:
Assignment operators are operators used to assign values to variables
Logical operators are used to combine conditional statements
