Python

Getting started

• About Python

  • The World's Fastest growing programming language
  • Most Popular among Software Engi., Data Analysts, Math, Science, Net Engi., and Kids
  • Google, Facebook, Spotify, DropBox, and etc. use Python
  • Python is simple
  • 
  • Python is a multipurpose Language
  • 
  • Most Desirable language
  • 
  • Python2 and Python3

• Installation Instruction

  • Install python (Download and install)
  • Note "check Add python 3 to PATH"
  • check your installation on windows Command prompt

• Python Interpreter

  • Check some code in it
  • Check errors

• Editors

  • Text Editors Notepad , Atom, Sublime
  • IDEs Pycharm,
  • Use VSCode for this class

• Create Your First Python File

  • Open your folder in VSCode And create .py file
  • Talk about extensions
  • First Built-in Function Print()
  • Execute first code in terminal

• Turn VSCode to a Powerful IDE Using Extensions

  • Install python Extension in VSCode
  • 
  • Install Linter to find Potential errors
  • Select right Python for your Project

• PyLint

  • Check PyLint Functionality
  • Check errors in problems panel
  • Talk about command pallet Shift + ctrl + p
  • Choose Right linter - pylint

• Python Enhancement Proposal

  • PEPs In google
  • PEP8
  • Talk about Python code formats
  • Format Document In command pallet
  • autopep8 Installation
  • Talk about some developer mistake in formatting code
  • Turn auto format on save in Code>Preferences>sittings
  • Search for FormatOnSave and turn it on

• Running Python Code

  • Install Code Runner
  • Running Code by Key or ctrl+alt+n

• Python Implementation

  • Cpython and python interpreter
  • Other Implementations of python Jython, IronPython, PyPy
  • These implementations help us to use other languages code in our python code

• Execution of Python code

  • Cpython and python interpreter
  • C Translation to machine code
  • • 
  • Codes are different in Mac and Windows based on compliers
  • • 
  • Java Solve the problem
  • • 
  • Python use it
  • • 
  • Jython Workflow
  • • 

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Primitive Types

• Variables

  • Core concept of storing data by programming languages
  • Three different built-in primitive types in python
  • Numbers (100, 4.9,...), Booleans (True/False), Strings ("Your Name")
  • All your variables' name should be descriptive and meaningful
  • All letters in your variable's name should be in lower case
  • Set a space before and after your equal sign
  • Use Underline between separate word

• Strings

  • Surround your text with " or '
  • For multiline text (long text) we use """
  • Talk about built-in function for String type
  • len()
  • Calling Functions concept by using ()
  • Indexing concept in Python for strings and []
  • End of the string using [-1]
  • Slicing strings Using [:] (check all options)
  • Using backslash \ to scape special characters (e.g. \", \', \\, \n)
  • Concatenate strings using +
  • Formatted Strings using f and {}

• String Methods

  • Talk about methods and OOP (Dot Notation)
  • upper(), lower(), and title() methods
  • Notice that the original string is not changed after using those methods
  • Use strip() method for users input strings (lstrip() and rstrip())
  • Use find() method to find a special character or series of characters (return an index or -1)
  • Use replace("1", "2") to change one or sequence of characters
  • in and not in expressions for checking the existence of something
  • Different between the find() and in expression is in return value (index, True/False)

• Numbers

  • There is three different number type in python
  • Integer, float, and complex (a + bi)
  • Talk about comments #

• Standard Arithmetic Operations

  • +, -, *, /, //, % and **
  • Augmented Operations +=, -=, *=, /=

• Built-in Functions for Numbers

  • round()
  • abs()
  • Talk about modules (math) and import the library and check . notation
  • Check math modules in Google (Python 3 math modules)

• Type Conversion

  • Use input function to get data from user
  • Check the error and explain the reason
  • Built-in Conversion methods in python
  • int(), float, bool, and str
  • talk about type() method
  • All falsy values in python: "", 0, False, and None
  • Check in interpreter

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Control Flow

• Comparison Operators

  • >, <, <= >=, ==, !=
  • An integer and a string value save differentially in memory 10 == "10" is wrong
  • every character has unique numeric representation ()unicode, so "bag" == "BAG" is wrong
  • Use ord() function to show differences

• Conditional statement

  • if statement (always terminate it with :)
  • Explain about code block and indentation on a simple example temperature
  • Simple example (if statement : pass)
  • Talk about indentation and code block with example of three print under an if statement
  • Explain codes out of if block
  • With elif statement we can add more condition to our code
  • If all our conditions are not True we use else statement to execute last condition (lots of elif and one else)
  • nested if statements

• Ternary Operator

  • Turn 5 line code to one
  • X = elem1 if rule1 else elem2
  • message = "OK" if time >= 10 else "Not OK"

• Logical Operator

  • and, or, and not
  • and operator return True if both conditions are True
  • or operator return True if one of conditions is True
  • not changes the value of a boolean variable
  • Don't use == for check a boolean variable
  • Separate conditions logical comparison to make accurate comparison
  • Avoid short circuit in the process of working with logical operators
  • Chain logical operators instead of using theme in word format
  • Use 18 <= age < 40 instead of age >= 18 and age < 40

• For Loops

  • When we need to repeat a task for number of times `For loop' can do it (Ex: print something for 10 times)
  • Talk about counter(number) and range function (step) and add ... * "."

• For...else

  • else execute when a loop completely was executed and aBreak didn't happen

• Nested Loops

  • Talk about Outer and inner Loops
  • Explain how exactly python interpreter execute nested loops

• Iterables

  • Use type for range() function to explain
  • Range is complex type
  • Iterable of strings or lists
  • You can create a iterable object and use it in For loop

• While Loop

  • We use While loop to repeat something as log as a condition is true
  • Explain While loop in python interpreter as real world example
  • Simulate Terminal using a while loop as extra example
  • Check case sensitive characteristic of python
  • Check a poor way of condition for while loop (A and B)

• Infinite Loop

  • Infinite loop is a loop that runs forever
  • You should always have a way to break the infinite loop
  • it can cause crash for your system

• Exercise/span>

  • A python code that shows even number between 1 to 10 and count them

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Functions

• How to Define a Function

  • In programming we should break our code in small, reusable, and more maintainable chunks of code
  • Use def keyword (short form of define) to declare your function
  • Make sure your function names are meaningful and descriptive
  • Name conventions should apply for functions naming
  • After definition of a function for using it you should call it (Two line break - pep8)

• Arguments

  • Talk about differences between print and our function
  • Define parameters in our function
  • A parameter is the input that you define for your function but an argument is actual value for a given parameter

• Types of Functions

  • There is two type of Functions
  • A: A function that perform a task (say_hello(), print())
  • B: A function that calculate and return a value (round())
  • We use return statement to return a value from a function
  • Write say_hello() function with return and get it in variable
  • Talk about print a function that doesn't return any value
  • By default all functions return a None value (indicator of absence a value)

• Keyword Arguments

  • Talk about temporary argument that python create for us when we pass a function to another function
  • Make your code more readable when you are calling your function by using keyword arguments
  • By adding a default value to a parameter we can make it optional
  • (Important) All optional parameters should come after the required parameters

• xargs

  • To pass a list of parameters to function we can use xargs
  • It returns a Tuple
  • By adding an asterisk (*) at beginning of a parameter it can take a list of values
  • Talk about tuples and lists by return xargs argument

• xxargs

  • To pass a series of keyword arguments to a function we can use xxargs parameter
  • By adding double asterisk (**) at beginning of a parameter it can take a list of key value peers
  • It returns a Dictionary
  • By using bracket notation we can get the values of a dictionary

• Scope

  • It's Impossible to call a variable which defined inside a function, outside of it
  • A local variable only works inside the scope also parameters
  • Thc completely equal variable in two different function is completely separate
  • When a function called, python interpreter allocate a memory to it's variables and release it at end function's execution
  • On the other side we have global variables which can be used anywhere in code
  • Global use memory for long time and you should not use them often
  • A global variable's value never change even inside a function
  • By using global keyword we can reference a local variable to a global one
  • Using global variables is not recommended because it can has a side effect in other functions

• Debugging

  • Start debugging process inside Debug panel (F5)
  • Choose current file and VSCode create a json file for your project (don't touch it)
  • By using bullet points (F9) you can define break point for debug process
  • By pushing F10 key you can step forward in process
  • By pushing F11 key you can step into a sub-process like a function
  • To stop debugger with shift+F5
  • Debugger stops wherever you placed a bullet point
  • To step out of a function or loop you can press shift+F11

• VSCode Tricks

  • In each line you can move to the end by pushing end key
  • In each line you can move to the beginning by pushing home key
  • By pressing Ctrl+end cursor move to the end of the file
  • By pressing Ctrl+home cursor move to the beginning of the file
  • By pressing alt plus arrow keys (top-down) you can move a line of code top or down
  • To duplicate a line press alt+shift+down keys
  • By pressing Ctrl+/ you can change a line to comment
  • By typing some characters of a variable you can place it by pushing enter

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Data Structure

• Lists

  • We use [] in Python to define a list or sequence of objects
  • Talk about different type of list (list of numbers, list of lists like a matrix)
  • zeros = [0] * 100 / Use + to concatenate or * to multiply
  • In python lists items doesn't need to be a same type
  • Use list() method to convert objects to list like list(range(20)) or list("Hello")
  • list() function takes an iterable as argument
  • Use len() method to get length of a list

• Accessing Items

  • By using Bracket notation we can have access to a list items
  • Talk about similar thing with regard strings
  • To modifying items use assign element. Change list Items like my_list[1] = "B"
  • Use [:] to get a range of items in list
  • By slicing a list, original list doesn't change
  • Use [::-1] to reverse a list ex: my_list(range(20))[::-1]

• Unpacking Lists

  • We can Unpack a list into multiple variables
  • first, second, third = my_list
  • Left and right side must be equal in number (Check for error)
  • Unpacking a large list : first, second, *other = my_list or first, *other, last = my_list
  • Using a asterisk * before a variable change it to a list and it is a packing in Python

• Lopping over Lists

  • Use for to loop over a list
  • enumerate() function unpack list item to key and value
  • This function convert each item of list to a tuple
  • Use for loop to show kays and values in a list (By indexing and unpacking)
  • Talk about for loop and represent items in each iteration

• Adding or Removing Items

  • Use append() method to add an item to end of a list
  • Use insert() method to add item at specific position in list
  • Use pop() method to remove an item from end of a list (remove with index)
  • Use .remove(item) to remove first occurrence of that item - remove without index
  • To remove all"b" in the list you should loop over list
  • Use del lst[0] to delete an item or del lst[:3] to delete a range of items
  • This is difference between pop() and del
  • Use clear() method to delete all items in the list

• Finding Items

  • To find index of an item use .index(item) method
  • index() method return ValueError when try to find an item that is not exist
  • Use if .. in .. statement to prevent this error
  • Use count(item) method to check existence of an item

• Sorting Lists

  • Use sort() method to sort a list
  • Use reverse parameter as keyword argument to sort your list in descending format lst.sort(key, reverse=True|False)
  • To sort a list without changing the original list use sorted(lst) function ex: sorted(my_list, reverse=True)
  • To sort a list of unordered items (complex) like list of tuples we should write a function and use sort item and pass all items to this function
  • We can pass a function not call to the sort() method as key parameter
  • You need to specify key parameter as keyword argument

• Lambda Functions

  • A lambda function is a one-line anonymous function that we can pass to other functions
  • Lambda function structure: lambda parameter: expression

• Map Function

  • To transform (map) a part of all items in a list of complex items we need to apply a for loop an get the desire value from it
  • By using map function we can do it in a shorter and elegant way
  • It returns a map object (an iterable) and by type conversion we can transform it to a list object (list())
  • We can loop over it or convert it to a list

• Filter Function

  • When we need to apply a filter on a list and get a specific values filter function is the way
  • Filter function takes a lambda function as first parameter and select items based on the lambda function criteria
  • It returns an iterable object (filter object)
  • We can loop over it or convert it to a list

• List Comprehension

  • List comprehension in python: [Expression for item in items]
  • It's completely the same with the mapping process and filtering process

• Zip Function

  • To merge two or more list in a single list of tuples we can use zip function
  • It returns a Zip object which is a iterable
  • Add a string to zip function and see the result

• Stacks

  • A LIFO data structure (example of Books)
  • Website's pages visiting hierarchy is good simple fore Stack
  • We can use .append(), .pop() methods for simulating stack and stc[-1] and `not []' to check it
  • [] is another falsy value

• Queues

  • A FIFO data structure
  • We use deque for optimize Using queue
  • Use .popleft() and deque class to manage your queue in optimize way

• Tuples

  • Tuple is a read only list and we use () to define it
  • if we remove () Python Assume it as tuple like 1, or 1,2
  • Empty parentheses indicate a tuple
  • We can multiple a number into a tuple or concatenate tuples
  • We can convert a list or any iterable into a tuple using tuple() function
  • Indexing, packing, and unpacking rules are usable related to tuples
  • We cannot mutate tuples and assign a value of tuple to a new value
  • We use a tuple when we need a sequence of objects that should be untouched throughout the execution of program

• Swapping Variables

  • x, y = Y, x (Exercise)
  • This clause works as unpacking in tuples x, y = (11, 10)
  • Explain about tuples without ()

• Arrays

  • When we deal with a large sequence of numbers we should use Array
  • Array take less memory and work a little bit faster
  • In 99% of the cases we use lists but sometimes when we experience a performance problem, arrays can solve it
  • For the using array we should import it
  • Search for python 3 Typecode in Google
  • Array(typecode, iterable)
  • We can all methods of lists about arrays
  • All members in array should be the same type (test assigning float to integer array)

• Sets

  • Set is a unordered collection of data without duplicates
  • By converting a List to set by using set() function we can remove all duplicates
  • We use {} to define sets
  • Like lists we can add to (.add() method) and remove items (.remove() method) from a set
  • len() function return the size of a set
  • Shining usage of sets is in mathematics
  • Use | operator to make union of two sets
  • Use & operator to get the intersection of two sets
  • Use - operator to get the differences between two sets
  • Use ^ operator to get the symmetric differences between two sets
  • Sets items not in sequence and we cannot access them by index
  • We can existence of a value by using if .. in statement

• Dictionaries

  • Dictionary is a key value pe collection of data
  • In dictionary keys can only be an integer or a string and value can be kind of anything
  • Index in dictionaries is the key items (my_dict["key1"])
  • We can define a dictionary by using dict() function
  • Always check for existence of a key before use or call it by if ... in statement or .get() method
  • To delete an item use del statement
  • For loop on a dictionary return keys in each iteration
  • By using .items() we can get dictionary's item in the shape of tuple in each iteration
  • Practice on writing list comprehension (Change it to a set)
  • We can use Comprehension for sets and dictionaries
  • Val = {x : x*2 for x in range(5)}

• Generator Expression

  • Comprehension on tuples return a Generator Objects
  • Generator object like list is a iterable but generate value in each iteration
  • Generators don't store all values in memory
  • len() function doesn't work on generator object

• Unpacking Operator

  • We can print items of a list by using [*numbers] statement
  • We can use unpacking operators to combine lists
  • Also unpack operator work abut dictionaries by using **
  • If we have multiple item in our dictionaries, the last item will be used

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Exceptions

• Exceptions

  • An exception is a kind of error that terminate the execution of the program
  • Like index error in lists or getting None value is input from user
  • By using a try exception block we can handel potential errors
  • If you don't handel exceptions properly your program will crash
  • All codes after try block will be executed after accruing an exception
  • By adding an else statement to your try block, if no exception is thrown else block code wil be executed
  • It's possible that different kind of exceptions happens and it's important to handel them
  • We can define multiple exception block for our try clause or put all potential exceptions in one exception block (inside a parentheses)
  • If one of our try block exceptions be executed other exceptions will be ignored
  • We should release the external resources like files or network connections after finishing our job with them
  • To prevent duplicate or release external resources, we need to define a finally at the end of your try block
  • Also we can use with statement in the case of working with external resources
  • This resources will be released when the program doesn't need the anymore
  • If any object in python supports context management protocol, we should open them by with statement
  • These files has two __enter__ and __exit__ magic method
  • We can open multiple file with one with statement
  • We can raise an exception by using this statement
  • Check Python 3 built-in exceptions In Google
  • We can manage all raises exceptions by try block
  • Using Try-exception is costly and only use it for sample and small programs
  • Pass statement is necessary when we need to do nothing
  • Think about using try block if you can handel it with a sample if statement

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Classes

• Classes

  • A class is a blueprint or template that defines the structure and behavior of an object
  • An instance of a class represents a specific, unique occurrence of that class, with its own set of data and the ability to perform actions defined by the class
  • Wrap up: A Class is a blueprint for creating new objects
  • Wrap up: An Object is an instance of a class
  • Classes form the building blocks for organizing and manipulating data in a comprehensive and organized manner, enabling efficient and reusable software development
  • Examples of classes and instances in real world

• Creating Classes

  • We follow Pascal naming conventions in classes naming
  • By using class keyword we can define our custom classes
  • We can define a object by calling a class and assign it to a variable
  • Talk about inheritance related to classes and Python objects
  • Talk again about type() method
  • By using isinstance() method we can check that an object is instance of a certain class
  • We cannot use a class without making an instance of it

• Constructors

  • __init__ method is especial magic method that executed when a new object was creating
  • self is reference to the current new object
  • Python create our new object and put it in memory and reference that in self statement
  • An object has its own attributes that have data which related to it
  • For example human is class that have its attributes like eye color, skin color, hight, wight, and etc, and its functions like walking, jumping, eating, and etc
  • Python fill self variable automatically for us, when an object is created
  • We can use self to call this object attributes or functions
  • To use functions of an object it's not necessary to put object name in function arguments. Python does it automatically

• Class vs Instance Attributes

  • We can define a new attribute for an object after creating it
  • Objects in python are dynamic
  • Instance attributes belong to each object separately
  • Class level attributes are shared across all instances of a class
  • We can use a class level attribute without making an instance

• Class vs Instance Methods

  • When we create an instance of a class, we can use its functions as instance methods
  • These methods really need to work a specific object
  • Zero() method is factory method
  • To create a class level method we need to use cls statement instead of self
  • Also we need a decorator to extend our method behavior

• Magic Methods

  • Magic methods called by python interpreter automatically depend on who we use our objects or classes
  • Search Python 3 magic methods in google
  • Print point object and talk about the type
  • Use str magic method as example to convert variables to string

• Comparing Objects

  • Two object of a Class with same attributes are completely different because they have different references in memory
  • We should use __eq__ magic methods to represent a comparable form of our class and check equality
  • Implement __gt__ method and check it for < and > operators
  • If you implement a magic method python automatically figure out what to do if you use the other one

• Performing Arithmetic Operations

  • Use __add__ magic method to sum to object
  • Save the result to another variable and print an attribute of it

• Creating Custom Containers

  • We can define our custom Container using python built-in data structures like dictionary

  • Define add method for our TagCloud class

  • Use get method to get item

  • Convert tags to lowercase through getting item

  • Define basic options for your Custom TagCloud like len(), set, and get items

  • Private Members

  • To make an attribute unaccessible from outside a class prefix it with two underline

  • Check this by . notation on an instance of your object

  • This member is still accessible but is hard to access and it's a kind of warring

  • Check __dict__ method (It's dictionary that all the attribute of a class)

  • Python automatically prefix an attribute with the class name

• Properties

  • To have control over attributes we can define set-get method to control values (It's not Pythonic)
  • Also we Can use a more Pythonic way that called properties
  • Define a class attribute using property() method
  • Only path a reference to get and set method
  • You have access to your property and easily can set or get it
  • set and get method pollute your object interface
  • You can make them unaccessible by adding two underline but its not good
  • Also you can @property decorator to make your code professional
  • Change the set and get method name to ideal name
  • Add @name.setter proChange your constructor and your attribute to regular one

• Inheritance

  • Classes with same method can make your code busy and noisy hard to maintain
  • Avoid DRY. it means: Don't Repeat Yourself
  • We can use inheritance or composition to solve this problem
  • Inheritance is a mechanism that allows us to define common behavior or common functions in one class and then inherit them in other classes
  • We use parentheses in front of a class name and write the parent class inside it to inherit all attributes and methods from Base class to Sub class
  • Sub class inherit all methods and attributes from base class

• The Object Class

  • Use isinstance() Method to reveal relationship between classes and object class
  • Object class is base class for all classes in python
  • Check inheritance between a class and object class by isinstance() and inspecting an instance of both of them
  • issubclass() method return True if a class is subclass of another class

• Method Overriding

  • When we use a subclass, some methods like constructor are overriding the Base class constructor
  • By using super() method we can call base class constructor in a sub class
  • To change the sequence of call super() method we can change the position of method
  • To recap method overriding means replacing or extending a method defined in base class

• Multi-level Inheritance

  • Inheritance prevent code duplication and allows us to reuse code
  • Too much Inheritance between classes can increase complexity and introduce lots of issues (Too much of a good thing is bad thing)
  • Remember, We should use multi-level inheritance in one or two level, not more

• Multiple Inheritance

  • If You use multiple Inheritance not properly it's gonna be source of issues
  • In multiple Inheritance python interpreter, first look for specific method in sub class and after that try to find it in multiple parents class in order from left to right
  • Multiple inheritance is not a bad thing, just like multi-level inheritance, if you don't use it properly it can cause problems
  • Before using multiple inheritance, check that the parent classes should have the minimum subscription

• A Good Example of Inheritance

  • A good Example of Inheritance on streaming from file and network in our web application

• Abstract Base classes

  • In our good example of inheritance, we have two serious problems:
    • We should built a sub class of Stream class and then use it
    • If we need to define a new sub class for Stream class, we should define read() method exactly like other sub stream classes
  • In this case we should Covert Stream class to an abstract base class
  • It's like a half baked cookie
  • We need to import ABC class and abstractmethod decorator from abc module
  • Remember we cannot instantiate a abstract class (we con not make instance of it)
  • If a class derive from a abstract class it has to implement its abstract methods

• Polymorphism

  • Poly means many, Morph means form
  • It enables objects of different types to be treated as objects of a common superclass
  • By define a abstract method and concrete a method our functions can use many forms of classes automatically
  • A function can deal with concrete methods of different classes automatically

• Duck Typing

  • To use Polymorphism we define a abstract class with common behavior and create subclasses with that behavior
  • If something like duck and quacks like duck, it's a duck
  • Python is dynamically type language and it doesn't check the type of object
  • If a certain method exist in object python accept it as abstract base method

• Extending Built-it Types

  • We can extend a built-in class like string class in python and give it more functionality by define a new class
  • Do it for list

• Data Classes

  • In Python we have classes that have only data and do not show any behavior
  • We can use id() method to print physical address of an object
  • We can use namedtuple library to define a class that have only data
  • namedtuples are immutable

Modules

• Creating Modules

  • A real program can contain tens of thousand lines of code
  • We write python code in separate modules
  • Python modules naming is like variables
  • Each module contain highly related objects (functions, variables, classes, etc.)
  • We can use objects in one file inside of another file by call theme by from ... import statement
  • By pressing ctrl+space after modules name in import statement we can see all methods and classes inside that modules
  • Using * to import all objects in a module can caused a overwriting and malfunction
  • If we used import statement only we should call objects by adding module name bef ore of any object (sales.calc_tax())

• Compiled Python Files

  • When we import a module inside another module python after first time running code make a compiled version of module to speed up in code execution later
  • Python look at the time of edit of compiled file for updating it
  • Name of the compiled file contain the version of cpython that used to execute this code
  • These files contain python bytecodes

• Module Search Paths

  • When we import a module at start of compiling a py file python look for finding that module in some predefined directories which come with the python installation

• Packages

  • When we want to organize our python files in separate directories we should make packages
  • Adding __init__.py file to a directory convert it to a python package
  • A package is container for one or more modules

• Sub-Packages

  • After add new directory we should add init file
  • And make change in import statement

• Intra-packages References

  • To import a module inside another module of another package we can use absolute ot relative statement
  • Absolute import is better and PEP* recommend it

• The dir() Function

  • dir() is a built-function that show all methods inside a module

• Executing Modules as Script

  • When a module load for the first time all statement in it will be executed
  • The name of the module that starts our program is always main
  • After add if name == "main": to a module when run in directly the the block code of it will be executed. but when imported it into another file this part of code will be ignored
  • by this way we make this file useable as script as well as reuseable module that we can import into another module

Python Standard Library

• What we are going to learn

  • Working with the path, Files, SQLite, Date/Time, Random values and So on...

• Working With Path

  • After import path library we ca use it in different ways
  • We can use raw strings to scape lots of double \\
  • search python 3 pathlib in google
  • The most important methods of this library is exist(), is_file(), is_dir(), with_name() and ...

• Working With Directories

  • Important methods in Pathlib library for work with directories
  • We use iterdir() method to get list of files and directories in a particular directory
  • It returns a generator object because a directory can contain a millions of files within
  • We use glob() method to find files based on a specific pattern
  • We use rglob() method to find files based on a specific pattern recursively

• Working With Files

  • Useful methods to working with files is exist(), unlink(), rename(), stat() and ...
  • Use time module to convert timestamp to a human readable format
  • By using read_text(_) or read_bytes() and also write_text(_) or write_bytes() methods we can change content our file
  • We can use shutil library to copy files instead of using read_text(_) or write_text() methods

• Working With ZIP and CSV Files

  • To work with zip file Use zipfile library
  • To work with CSV file Use csv library
  • csv is acronym for Comma Separated Values
  • After importing csv module we use open built-in function to open() a csv file
  • By using writer() method we can built a csv file and write data in it
  • By using reader() method we can read from a csv file
  • By using list() method we can make a list of csv rows

• Working With JSON Files

  • JSON is javaScript Object Notation
  • We use JSON to format data in human readable way
  • To answer the requests that ask some data from your website you need to provide data in JSON format
  • Note that dump() and load() convert between files and objects, while dumps() and loads() convert between strings and objects

• Working With XML Files

  • XML means eXtensible Markup Language (not programming language)
  • It was designed for storing, organize, and transport data
  • It has no predefined tags
  • XML separates information for presentation
  • XML tags doesn't look like anything in the browser
  • prolog is the first line of xml and it's optional
  • <?xml version=1.0 encoding="UTF-8"?
  • Your xml file has root element tag all elements have to start with opening tag <tag_name> and closing tag </tag_name> (it's a case sensitive language)
  • Nesting is important and avoid mismatch
  • There is two different modules that allows us to work with xml file xml.sax and xml.dom
  • In sax we never load whole file in to the ram and we only load the pieces that we need and we can't change content (very large xml file)
  • In dom we load whole file into the ram and we can read write and change file in a hierarchical structure
  • We need a handler (work with file) and parser (translate file)

• Working With SQLite Database

  • SQLite is very light weight Database that we use to store data of an application
  • We can use SQLite Database browser to manage our sqlite db file in visual (download db browser for sqlite from google)
  • Insert data into database using a SQL INSERT query text
  • Read data from database using a SQL SELECT query text
  • When we try to read from database we'll get cursor

• Working With Timestamps

  • To work with time and date in python we can use two modules (time, datetime)
  • Time module returns timestamp and datetime module returns an object that contains many attributes like year, month, and ...
  • Start of timestamp in unix base systems is a actual date (1970-1-1) and timestamp demonstrates all seconds from that time

• Working With DatetTimes

  • DateTime object can converts a date to python object
  • DateTime can show currents date time by method now()
  • DataTime object can converts strings to real datetime by strptime() method (by using a pattern like ("%Y/%m/%d"))
  • Search Python 3 Strptime in Google
  • DataTime object can converts timestamp object to string by fromtimestamp() method
  • DataTime object can converts datetime object to string by strftime() method
  • We can compare datetime objects

• Working With Time Deltas

  • We can add or subtract a duration from our datetime object
  • timedelta has it's attributes and methods

• Generating Random Values

  • We can make random values by using random module
  • We use string module to give choices method all ascii letters and numbers to generate a good password
  • By using join() method we can join all items in a list together

• WebBrowser Module

  • We can open a web browser by using webbrowser Module

• Send Email

  • We can send email by using email module
  • First we should add all info that an email need to be sended by sntp protocol

• Line Arguments

  • By using argv module we can have access to command prompt extra codes like user or password attributes which have been written by user

Python Package Index

• Pypi

  • There are times that we need features that not implemented in the Python standard libraries
  • We use Pypi(Python Packaging Index) to import lots of useful libraries to our program
  • Visit pypi.org and search on it to find your desireable package
  • Search in google: "Best python packages for working with ..."

• Pip

  • We use tool named pip to manage our packages
  • Use "pip install 'package-name'" to install a package
  • We can use 'pip list' to check our installed packages
  • Check a package like requests in pypi.org
  • By adding == and the a specific version number we can install an earlier or older version of a package(requests==2.9.*) (~)
  • use pip uninstall 'package-name' to uninstall a package
  • Import an installed packages in python file as example

• Virtual Environments

  • When we need to work with two different version of a package in two separated projects simultaneously we should create a virtual environment for each of them
  • By python -m venv env we can make a virtual environment for our project
  • Our packages would be installed inside the site-packages directory
  • In windows, to active the virtual environment we should use this command: env\bin\activate.bat
  • We use deactivate command to deactivate venv

• Pipenv

  • Pipenv is tool that combine pip with virtual environment to a single tool
  • Install pipenv using pip first
  • To install packages using pipenv we use pipenv command instead of pip in pip install command
  • We can locate our new virtual environment by command: pipenv --venv
  • We activate our virtual environment by this command : pipenv shell and deactivate it by exit
  • In vscode we need some configuration to use pipenv
  • After implementing pipnv you need to change the path of python to your project virtual environment directory
  • pipfile and pipfile.lock help to keep track of our project dependencies
  • In another computer by using pipenv install we can install all our projects' dependencies (It looks for pipfile)
  • To install all packages in their actual version that used in the time of developing of the package
  • pipenv graph shows you all installed dependencies
  • By using pipenv uninstall you can remove a dependency
  • To find the out dated packages we can use pipenv update --outdated
  • By using pipenv update we can update our dependencies
  • pydoc3 math show the documentation of math library
  • pydoc -w PACKAGE_NAME can convert a package to HTML file

Tkinter

• GUI Application

  • Create virtual environment and run it
  • Install tkinter library (pipenv install tk)
  • Install pyinstaller library
  • Create your part_manager.py file
  • Create your db.py file
  • Import tkinter library (import tkinter as tk)
  • mainloop() method Keep your app run permanently
  • Change your app title
  • You need to add a widget to your root application
  • By calling StringVar(), Label(), and Entry() methods we can create a data entry section
  • We can add grid geometry to add a button to our application
  • grid is most compatible geometry manager that is most flexible with all kind of applications
  • By using geometry() method we can apply size to our app
  • Add some widget to your app (Label, textbox and ...)
  • Create a listbox using Listbox() method for your app to show items
  • rowspan and columnspan give more space to your grid cells vertically and horizontally
  • Now we need a scrollbar. Create it with Scrollbar() method and place it in the third column
  • By using configure() method we can stick our scrollbar to listbox
  • command option set scroll behavior
  • Now we need to add our buttons to app by using Button() method
  • For command option we need to path a function that do something when user push the button
  • Define your command functions at top of the file
  • Now we need to define our database in db.py file
  • It's more better, organized and optimized to use class
  • In our class constructor we need to define db and connection to it
  • Also we should define table at first if it doesn't exist
  • Now we need to define CRUD operations in the form of the class methods
  • After define cursor in each method you need execute your SQL command and finally commit it
  • Give your values to cursor in the form of tuple
  • In the case of deleting an object it's important that you have a deconstructing method in your class
  • Now create an object with your class and insert some date into it (Use my_file repo)
  • Import your Database class inside part_manager module and instantiate it
  • Now we can all our methods inside the db module and place them in the functions that we define for buttons
  • populate_list echo all records inside the database
  • First delete all items in listbox and import database information into it
  • Define add_item method and use it as command for Add Part button
  • Your app add item even all textbox are empty and you should avoid it by using messagebox and check input
  • To remove an item we need to find its id by another method called select_item whcih we define to get selected item in the list
  • Our select item should get an event that is binded to our Listbox SELECT
  • Also we need to fill textboxes with actual info in data base after selection
  • To remove an item just by passing first element of selected item to remove() method we can do it
  • For Update you should give the selected item id and all textboxes info to update method
  • Now you can create an executable file of your application by using pyinstaller module ad this command:
  • "pyinstaller --onefile --windowed app.py"

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