python-Notes.txt

Large collection of python notes.
  Jupyter Notebook
    type its name in command prompt opens jupyter notebook

  Ctrl+Alt+N
    Runs code in vscode with Code Runner Extension

  PyPi repo for open-source third party packages
    rubygems in rubygems
    php packagist
    cpan for properly
    npm for node

    internal libraries are known as standard libraries

    use pip to install

    pip install
      colorama - allows you to add color to items in command line
      requests - allows you make http requests with python
      openpyxl - use excel files in python
      pylint - checks code and reports possible errors
        pylint not recognized in w10
          add address to path variable in w10
          https://www.youtube.com/watch?v=i4yJi-cpwWk
      black - Python code formatter.
        https://www.youtube.com/watch?v=esZLCuWs_2Y&feature=youtu.be

  Basic Practice:
    http://codingbat.com/python
  More Mathematical (and Harder) Practice:
    https://projecteuler.net/archives
  List of Practice Problems:
    http://www.codeabbey.com/index/task_list
  A SubReddit Devoted to Daily Practice Problems:
    https://www.reddit.com/r/dailyprogrammer
  A very tricky website with very few hints and touch problems (Not for beginners but still interesting)
    http://www.pythonchallenge.com/
  PEP-8 Style guide
    https://www.python.org/dev/peps/pep-0008/

  py -3 -m venv [folderName]
    Creates Virtual Environment
    -3 is version of python
    -m is module you want to install
      venv virtual Environment
    [folderName is the name of the folder you want to create]

  requirements.txt
    a list of dependencies application will need to function properly
      (similar to package.json)
    pip install -r requirements.txt
      installs all the dependencies. (similar to npm install command)

  ast - abstract syntax tree - similar to a DOM tree but for python code in a file.
    This is how the interpreter views python code.

  # are comments
  '''
  These are doc strings
  '''

  print("something")
    prints to console.

  type()
    gets the data type of whatever you pass into the method

    NoneType is none (absence of value)

  help()
    returns documentation on whats in the parameter

  dir()
    returns a list of methods that can be used with datatypes/variables w/e
    help(set().add)

  Mutable - types that can be changed without have to be recreated in memory

  Immutable - types that cannot be changed and are pointers to a stored object in memory. 

  Callables - Are anything that can be called
    user-defined functions
    generators
    classes
    instance methods
  
  Singletons - objects
    None
    NotImplemented
    ellipsise


All code implicitly at indentation level 0 gets ran.

variables
  variable names should be snake_case

  _myVar - Single underscore indicates 'internal use' or 'private'
    Objects named this way will not get imported by a statement such as: 
      from module import *
  
  __myVar - Double underscore aka 'dunder' Used to "mangle" class attributes - use in inheritance chains

  __myVar__ - Double dunder are system-defined names that have a special meaning to the interpreter
    Dont invite variables, stick to python pre-defined
      '__all__'
      '__args__'
      '__author__'
      '__bases__'
      '__builtin__'
      '__builtins__'
      '__cached__'
      '__call__'
      '__class__'
      '__copy__'
      '__credits__'
      '__date__'
      '__decimal_context__'
      '__deepcopy__'
      '__dict__'
      '__doc__'
      '__exception__'
      '__file__'
      '__flags__'
      '__ge__'
      '__getinitargs__'
      '__getstate__'
      '__gt__'
      '__import__'
      '__importer__'
      '__init__'
      '__ispkg__'
      '__iter__'
      '__le__'
      '__len__'
      '__loader__'
      '__lt__'
      '__main__'
      '__module__'
      '__mro__'
      '__name__'
      '__package__'
      '__path__'
      '__pkgdir__'
      '__return__'
      '__safe_for_unpickling__'
      '__setstate__'
      '__slots__'
      '__temp__'
      '__test__'
      '__version__' 

  Method/function names should use snake-case not camel case
    def method_name:
    var_name = "snake case"


Strings are immutable
  you can't use indexing to change individual elements of a string
  String objects do not support item assignment.
  Dont support item assignment.

  Immutability is when you cannot change the object itself when manipulating it.
    You would have to create another object with the changes.

  # are comments

  a = "string"

  a[::-1]
    reverses the string
    "gnirts"

  a[1:]
    after first char to end of the world
    #tring

  # String multiplication
  letter = 'z'

  letter * 10
    # 'zzzzzzzzzz'

  #string formatting
  .format()
  f-strings

  n = "Yael"
  print('Hello, my name is {}'.format(n))

  # Hello, my name is Yael


  # formatting floating point numbers
  # float formatting follows "{value:width.precision f}"
  # width is the whitespace
  #   https://pyformat.info/

  result = 100/777
  print(result)
  print("The result was {r:1.3f}".format(r=result))
    0.1287001287001287
    The result was 0.129

  # f strings
  print(f'Hello, his name is {n}')

  .capitalize() - capitalizes first letter
  .title() - capitalizes every first letter of the word


Lists (arrays in python)
  support indexing and
  lists are mutable
  supports multidemensional arrays
  can have multiple object types

  # can concatenate lists

  l1 = ['one', 'two', 'three']
  l2 = ['four', 'five', 'six']
  l1 + l2

  ['one', 'two', 'three', 'four', 'five', 'six']

  # add to end of list. Similar to .push in js
  l1.append('addition')

  # pop, removes items from the end of the list and returns that object
  # by default index location is -1
  l1.pop()
  popped_item = l1.pop()
  popped_item

  # sorting is done by .sort() (like js)
  # does not return a list, just sorts it in the current lists

  # reversing is done by .reverse() (like js)
  # does not return a list



Dictionaries
  Are objects retrieved by key name
    (lists are retrieved by index position)
  Are mutable like Lists
  Unordered and cannot be sorted
  Formatting is similar to json
  Can support multidemensional dictionaries

  dictionaries are not ordered they are sets.

  ordereddict object can support sorting in dictionaries.

  # calling items in dict
  newDict = {"a": 1, "b": 2}

  newDict["a"]
    1



Tuples
  Similar to lists but are immutable.
    Once element inside of a tuple it, cannot be reassigned.
    tuple object does not support item assignment
  uses parenthesis
  You won't use tuples often
    You use tuples for when you pass around objects in your program that you don't want to get accidentally changed.
    Data integrity
  Does not have a lot of methods for tuples


  t[0]
    calls first value of tuple. Similar to list/(arrays in js)
  t.count('val')
    counts how many times 'val' appears in tuple.



Sets
  unorder collections of unique elements
  similar to arrayLists in Java.
  does not contain duplicate elements
  Union and Intersection
    Union - combination of two sets
      designated by the union symbol 'U'
      .union()
    Intersection - values that are similar in both sides of the union
      designated by upside down union symbol (upside down u)
      .intersection()


Booleans
  first letter of True or False has to be capitalize



FileIO
  %%write myfile.txt
    writes a text file with jupyter notebook

  open('[path]')
    opens file
    (does not work with extension, use python filename.py command)
    provide full file path to open a file somewhere else on your system.
  open('[path]',mode='val')
    mode='r' - read only
    mode='w' - write only
    mode='a' - append only
    mode='r+' - reading and writing
    mode='w+' - writing and reading (overwrites exisiting files or creates a new file)

  f.ready()
    Returns output of the file.
  f.seek(0)
    resets the read cursor to beginning of the file
  f.readlines()
    creates a list with each line on the list.

  f.close()
    closes file so you don't get errors elsewhere in your operating system.

  f.write()
    writes to the file
    cursor is at the end of the document

  with
    with keyword is like define? but does not define a method?



Comparison operatiors
  Same as javascript except with out ===
  == is the same as js ===



Logical operatiors
  and keyword instead of &&
  or keyword instead of ||
  not keyword negates the comparison operator
    (not 1 == 1) is equal to (1 != 1)

Control flow
  if, Elif and Else

  if some_condition:
    # execute some code
  elif some_other_condition:
    # execute some code
  else:
    # do something else

  For loops are similar to map function in js and forEach in Java
  for var in List:
    # do something

  Common to use _ for forloop if don't plan on using the variable within the loop.
  for _ in myL:
    print("Cool!")
  can iterate over tuples as well.

  Tuple unpacking - duplicate the structure in the list and you do something with them.
  Can iterate thru a dictionary as well.
  obj = {'k1': 1, 'k2': 2, 'k3': 3}

  for val in obj.values():
    print(val)

  for k in obj.keys():
    print(k)

  While-loops have else statement like if-else (elif)
    while some_boolean_condition:
      # do something
    else:
      # do something else

  Kernel > interrupt / restart
    If jupyter notebook gets into endless loop

  break - breaks out of the current closest enclosing loop
    similar to break to javascript
    exits the loop
  continue - goes to the top of the closest enclosing loop
    similar to continue in javascript
    skips the iteration and continues the loop
  pass - does nothing at all
    pass is used for prevent eof (end of file) errors.
    Can write a for loop and not add any code to execute (to come back later)

  Python has a ternary operator
    a = 25
    b = 'a < 5' if a < 5 else 'a >= 5'

  Special Operatorss
    range([start], [stop], [step-size])
      used in a for loop prints the range of from start to stop.
        Can change the increment value with step size. (can go up by 2, 3 or 4) default is 1.

      for num in range(0,11,2):
        print(num)

      list(range(0,11,2)) # casting numbers to a list.

      Range is a generator
        Generator is a special type of function that will generate information instead of save it all to memory

    enumerate(str)
      Return index count along with value when used in for loop in a tuple
      list(enumerate(str)) # casting tuples to a list

    zip(list1, list2)
      combines to lists for iteration
      if you run zip a lone, it returns the generated zip's memory address
      returns list a list of tuples

      will only display as far back as the list that is the shortest
        list 1 = 5 items
        list 2 = 3 items
        zip will print out 3 items.

      list(zip(list1, list2)) # can be casted to a list

    in [keyword operator]
      similar to indexOf in js. Except that it returns a boolean like .contains in javascript
      used a lot when working with strings

    min(list)
      shows minimum value in a list

    max(list)
      shows maximum value in a list

    shuffle(list)
      from random [package] import shuffle
      randomizes items in a list.
      does not return anything

    randint(min, max)
      returns a random number with min and max.
      similar to javascript Math.Random()

    input('str')
      Accepts input from user
      accepts everything as a string.
      Can be wrapped for casting.



List Comprehensions
  [expression for item in list]
    https://www.programiz.com/python-programming/list-comprehension
  [ expression for item in list if conditional ]
    List comprehension with if statement
    [s for s in stores if s["name"] == name]
    https://stackoverflow.com/questions/4406389/if-else-in-a-list-comprehension

  flattened for loops
    celcius = [0,10,20,34.5]
    fahrenheit = [((9/5) * temp + 32) for temp in celcius]
    append is implied in flattened for loops

    if else statements are reverse order
    results = [x if x % 2 == 0 else 'ODD' for x in range(0,11)]

    can do nested loops
    results = [x*y for x in [2,4,6,] for y in [1,10,1000]]

    Always try to do readability first.



Methods
  def name_of_function():
    print("some code")

  How to document methods
    '''
    DOCSTRING: Information about the function
    INPUT: no input...
    OUTPUT: Hello
    '''

  def func(a: int, b: int): - Helps the dev know what datatype to use, but does not stop you from using other datatypes
    func(2,3) # 6
    func("cookies", 2) # cookies cookies

  positional arguments - the name given to arguments of a method where the first item will be first variable in method. Second argument is the second variable etc. Based off of position they are in the parameters of the method.

  def func(a,b,c=0,d=0,e=0):

  *args - arguments
    Allows you take a arbitrary number of arguments
    Arguments will be treated as a tuple inside of the function
    def func(*args):

  **kwargs - keyword arguments
    arbitrary number of keyword arguments
    treats it as a dictionary as a input.
      def func(**kwargs):
      func(a=1, b=2):

  args and kwargs can be used in combination
    Useful to be used outside of arguments
      func(*args, **kwargs):
      func(1,2,3,4,5,6,a=1,b=2,c=3)

  Lambda Expressions - Anonymous function - Map and Filter
    Way to create anonymous functions that are used only once.

    map - map(func, iter) - used to replace the for loop, with less code. Allows you to run a method on each item in the iter.
      can cast into list, by wrapping list() around it.

    filter - returns a iterable when the items passed in the function are True.

    reduce -
      no longer built-in function
      demoted to functtools module
      "Use functools.reduce() if you really need it; however 99% of the time an explicit for loop is more readable."
        Guido Van Rossum, Python Creator


    lambda - keyword creates anonymous function.
      lambda num: num ** 2
      can write python in one line, but not standard in styling (but looks cool)
      Should only use it when you can easily read it if you were to come back to your code later.

  Nested Statements and Scope
    create a variable in python, the variable is stored in a namespace.
      namespace also has a scope (similar to javascript)

    LEGB - Local Enclosing, Global (module), Built-in
      Order that python is going to look for variables in

    global - keyword used within another scope can change the global variable value
      Not recommended.



OOP
  __init__ - constructor
  __str__ - equal to toString method
  __len__ - equal to .length() method
  __del__ - deletes the object

  method - is a function that inside of a class that will work with the object in some Way
  method overloading - is done by setting default value of none.

  Inheritance
    child classes are called derived classes.

  Polymorphism
    Won't really use it much in Python

  Abstraction
    Class thats not expected to be instantiated on, designed to be a base class.

  Encapsulation
    Defining variables with dunder, will make them private
    __privateVar



Create own modules in packages in Python
  Modules - is .py script to use in another .py
  __name__ - gets assigned a name depending on how you are running the script.
    this var gets assigned in the background
    if __name__ == "__main__" - if true, it means you are running the .py file directly.

  __main__ - name of the file being ran. Implicitly set by python



Errors and Exception handling
  try - this will try and run your code
  except - will do something if it catches an error
  else - else block will run if there are no errors. If there is an error it will not run.
    (means theres is no exception)
  finally - will run regardless of an error.
    wise to add function calls here.

  raise - errors are not 'called' in python they are 'raised'

  different types of errors and exceptions
    syntax errors - errors with syntax
    exceptions - error when attempt to execute. Syntax is correct
      https://docs.python.org/3/library/exceptions.html#bltin-exceptions
        List of python built in exceptions



Unit Testing
  pylint - library that looks at your code and reports possible issues
    mainly for working with other people or an organization
    Styling rules are known as PEP8
      https://www.python.org/dev/peps/pep-0008/
      python3 disallowed the use of tabs and spaces for indentation
        use spaces instead of tabs
    pylint not recognized in w10
      add address to path variable in w10
      https://www.youtube.com/watch?v=i4yJi-cpwWk
  unittest - built-in library will allow you to test your own programs and check you are getting desired outputs
    You wil create a test class.
    Best to go from simple to complex.



Python Decorators
  Docorators = java annotations
  Decorate a function - on/off switch to add new code (functionality) to a function.
    allow you to tack on extra functionality to an already exisiting function
    use @ operators placed on top of the original function
      annotations like in Java ?

  functions are objects that can be passed into other objects
  can define function inside of a function

  @annotation - the annotation has to be the name of a function that takes a function as a argument
    really common in web frameworks like django or flask

  decorates the function with some extra code.



Generators
  Allows you to write a function that can send a value back and then later resume to pick up where it left off
  Generate a sequence of values overtime.

  example would be the range function
    keeps track of the last number it returned and the step size.
    Does not create a giant list in memory.

  yield - keyword that returns a value instead of storing it in memory.
    allows you to iterate thru loops
    create own generators using yield

  next - What for-loops use to call the next value
  iterator - (iter()) allows you to interate thru objects

  string objects support iter, but cannot be interated over with next() function
    Have to convert objects that are iterable to iter

  generator expressions - are faster than list comprehension
  generator comprehension - https://www.pythonlikeyoumeanit.com/Module2_EssentialsOfPython/Generators_and_Comprehensions.html



Collections
  countainer dicts

  counter - dictionary sub class.
    Counts the number of times a element shows up in a list.
      (list or iterable)
    returns a dictionary.
    .most_common(#)
      shows the most common values in that list.
      replacing # with the number will show you the top # elements in that list

    sum(c.values())                 # total of all counts
    c.clear()                       # reset all counts
    list(c)                         # list unique elements
    set(c)                          # convert to a set
    dict(c)                         # convert to a regular dictionary
    c.items()                       # convert to a list of (elem, cnt) pairs
    Counter(dict(list_of_pairs))    # convert from a list of (elem, cnt) pairs
    c.most_common()[:-n-1:-1]       # n least common elements
    c += Counter()                  # remove zero and negative counts


  defaultdict - all methods provided by dicionary but takes first argument (default_factory) as default datatype for the dictionary.
    faster than using dict.set_default method
    Will never raise a KeyError
      any key that does not exist gets the value returned by the default factory


  orderedDict - remembers the order in which its contents are added
    normal dictionary is a mapping, does not retain order


  namedtuple - assigns names to numerical index in the tuple
    like normal tuple, and assigns object type
    namedtuple('name of class', 'param1 param2 param3')
    sub class of tuple



Dateime
  builtin module to work with date and time.
    manages timezone information

    datetime.time()
      https://docs.python.org/2/library/datetime.html#time-objects

  tzinfo - Timezone information
  datetime.date.today().timetuple()
    returns a tuple of information in that time instance

  doing arithmetic with time will return the timedelta



pdb
  interactive debugger for python programs
  pythons built in debugger
  not taught to beginners at all

  (Pdb) q
    will quit the debugger

  https://docs.python.org/3/library/pdb.html



timeit
  Times your code execution
  timeit.time( # expression as a string, number of times you want to run it)
    returns the time in seconds.

  significant time difference using map

  https://docs.python.org/2/library/timeit.html



StringIO
  implements an in-memory file like object.
    can be used as input or output to most functions that would expect a standard file object
    usually used for scraping from the web.

  Can convert strings and read and write to them as if they were files

  https://docs.python.org/2/library/stringio.html

  cStringIO - faster implementation of stringio



Regular Expressions
  https://www.w3schools.com/python/python_regex.asp
  https://docs.python.org/3/library/re.html

  Similar in syntax to pearl
  import re

  re.search("")
    returns a match object
    if no pattern is returned, None is returned.

  .start()
    shows index of when the match begins

  .ends()
    shows index of when the match ends.

  how to split domain names from a email address?
    common interview question
    re.split()

  re.split([term], [phrase])
    splits a phrase and returns a list by the term.

  re.findall([term], [phrase])
    returns a list of all the matches

  meta-characters
    r'' - designates the pattern
    repetition sets
    character sets
    exclusion
    character ranges
    Escape codes

  People usually refer to documentation when working with regex
    completepython3bootcamp-files / 13-advancedPythonModules / 05-regular expressions