Advanced Python after beginner python for intermediate learners

From the map() function, which applies a specified function to each
element of an iterable and returns a new iterable with the modified
elements, to the enumerate() function which adds a counter to an
iterable and returns an iterable of tuples, these functions can help you
write cleaner and more concise code.
Let’s take a closer look at these advanced Python functions and see how
to use them in your code.

map()
The map() function applies a specified function to each element of an iterable (such as a list, tuple, or
string) and returns a new iterable with the modified elements.
For example, you can use map() to apply the len() function to a list of strings and get a list of the lengths of
each string:

You can also use map() with multiple iterables by providing multiple function arguments. In this case, the
function should accept as many arguments as there are iterables. The map() function will then apply the
function to the elements of the iterables in parallel, with the first element of each iterable being passed as
arguments to the function, the second element of each iterable being passed as arguments to the function,
and so on.
For example, you can use map() to apply a function to two lists element-wise:
def multiply(x, y):
return x * y
a = [1, 2, 3]
b = [10, 20, 30]
result = map(multiply, a, b)
print(result) # [10, 40, 90]

reduce()
The reduce() function is a part of the functools module in Python and allows you to apply a function to a
sequence of elements in order to reduce them to a single value.
For example, you can use reduce() to multiply all the elements of a list:

You can also specify an initial value as the third argument to reduce(). In this case, the initial value will be
used as the first argument to the function and the first element of the iterable will be used as the second
argument.
For example, you can use reduce() to calculate the sum of a list of numbers:

filter()
The filter() function filters an iterable by removing elements that do not satisfy a specified condition. It
returns a new iterable with only the elements that satisfy the condition.
For example, you can use filter() to remove all the even numbers from a list:
def is_odd(x):
return x % 2 == 1
a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
odd_numbers = filter(is_odd, a)
print(odd_numbers) # [1, 3, 5, 7,
9]
You can also use filter() with a lambda function as the first argument:
a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
odd_numbers = filter(lambda x: x %
2 == 1, a)
print(odd_numbers) # [1, 3, 5, 7,
9]

zip()
The zip() function combines multiple iterables into a single iterable of tuples. The zip() function stops
when the shortest iterable is exhausted.
For example, you can use zip() to combine two lists into a list of tuples:
a = [1, 2, 3]
b = ['a', 'b', 'c']
zipped = zip(a, b)
print(zipped) # [(1, 'a'), (2,
'b'), (3, 'c')]
You can also use zip() with more than two iterables:
a = [1, 2, 3]
b = ['a', 'b', 'c']
c = [True, False, True]
zipped = zip(a, b, c)
print(zipped) # [(1, 'a', True),
(2, 'b', False), (3, 'c', True)]

You can unpack the tuples in a zip() object by using the * operator in a function call or a list
comprehension:

enumerate()
The enumerate() function adds a counter to an iterable and returns an iterable of tuples, where each tuple
consists of the counter and the original element.
For example, you can use enumerate() to loop over a list and print the index and value of each element:

You can also specify a start value for the counter as the second argument to enumerate():
we covered some advanced Python functions that can be useful in your code. We looked at the map(),
reduce(), filter(), zip(), and enumerate() functions, and provided examples of how to use them. These
functions can help you write more efficient and concise code, and are worth exploring further.

Modules and Libraries in Python

1. What is a Module?
A module in Python is a file that contains Python code (functions, classes, or variables)
that you can reuse in your programs.
Any Python file with the .py extension is a module.
You can import a module into another program to access its functions or classes.
2. What is a Library?
A library is a collection of modules or packages that provide pre-written functionality to
simplify coding tasks.
Example: Libraries like NumPy for arrays, Pandas for data analysis, and Matplotlib for
plotting.
3. Importing Libraries and Modules
You can import libraries or modules using the import statement.

Basic Import Syntax:
Importing Specific Functions or Classes

https://www.learnpython.dev/03-intermediate-python/50-libraries-module
s/30-modules-and-imports/
We will study little from this site now…

4. Installing External Libraries Using pip
What is pip?
● pip is Python's package manager used to install external libraries that are not built
into Python.
● Libraries like NumPy, Pandas, and Matplotlib are installed using pip.
Installing a Library
pip install library_name
For example:
pip install numpy
pip install pandas

Decimal Formatting:
Formatting decimal or floating point numbers with f-strings is easy - you can pass in both a
field width and a precision. The format is {value:width.precision}. Let’s format pi (3.1415926)
to two decimal places - we’ll set the width to 1 because we don’t need padding, and the
precision to 3, giving us the one number to the left of the decimal and the two numbers to the
right
Note how the
second one is
padded with
extra spaces -
the number is
four characters
long (including
the period), so
the formatter
added six extra
spaces to equal
the total width
of 10.

Multiline Strings
Sometimes it’s easier to break up large statements into multiple lines. Just prepend every line with
f:

Trimming a string
Python strings have some very useful functions for trimming whitespace. strip() returns a new
string after removing any leading and trailing whitespace. rstrip() and does the same but only
removes trailing whitespace, and lstrip() only trims leading whitespace. We’ll print our string inside
>< characters to make it clear:
Note the different spaces inside of the brackets. These functions also accept an optional argument of
characters to remove. Let’s remove all leading or trailing commas:

Replacing Characters
Strings have a useful function for replacing characters - just call replace() on any string and pass in what
you want replace, and what you want to replace it with:
str.format() and % formatting
Python has two older methods for string formatting that you’ll probably come across at some point.
str.format() is the more verbose older cousin to f-strings - variables appear in brackets in the string but
must be passed in to the format() call. For example:

Note that the variable name inside the string is local to the string - it must be assigned to an outside
variable inside the format() call, hence .format(name=name).
%-formatting is a much older method of string interpolating and isn’t used much anymore. It’s very similar
to the methods used in C/C++. Here, we’ll use %s as our placeholder for a string, and pass the name
variable in to the formatter by placing it after the % symbol.
*******************************************************************

Advanced Looping with List Comprehensions

List Comprehensions
List comprehensions are a unique way to create lists in Python. A list comprehension consists of brackets
containing an expression followed by a for clause, then zero or more for or if clauses. The expressions can
be any kind of Python object. List comprehensions will commonly take the form of [<value> for <vars>
in <iter>].
A simple case: Say we want to turn a list of strings into a list of string lengths. We could do this with a for
loop:
We can do this much easier with a list comprehension:

We can also use comprehensions to perform operations, and the lists we assemble can be composed of any
type of Python object. For example:
In the above example, we assemble a list of tuples - each tuple contains the element “length” as well as
each number from the len() function multiplied by two.
Conditionals
You can also use conditionals (if statements) in your list comprehensions. For example, to quickly make a list of
only the even lengths, you could do:
Here, we check divide every string length by 2, and check to see if the remainder is 0 (using the modulo
operator).

String Joining with a List Comprehension
Back in our exercise on converting between types, we introduced the string.join() function.
You can call this function on any string, pass it a list, and it will spit out a string with every
element from the list “joined” by the string. For example, to get a comma-delimited list of
numbers, you might be tempted to do:
Unfortunately, you can’t join a list of numbers without first converting them to strings. But
you can do this easily with a list comprehension:

Some mathematical functions, such as sum, min, and max, accept lists of numbers to operate
on. For example, to get the sum of numbers between zero and five, you could do:
But remember, anywhere you can use a list, you can use a list comprehension.
Say you want to get sum, minimum, and maximum of every number between 0 and 100 that
is evenly divisible by 3? No sense typing out a whole list in advance, just use a
comprehension:

Exception Handling:
Many languages have the concept of the “Try-Catch” block. Python uses four keywords:
try, except, else, and finally. Code that can possibly throw an exception goes in the try
block. except gets the code that runs if an exception is raised. else is an optional block
that runs if no exception was raised in the try block, and finally is an optional block of
code that will run last, regardless of if an exception was raised. We’ll focus on try and
except for this chapter.
First, the try clause is executed. If no exception occurs, the except clause is skipped and
execution of the try statement is finished. If an exception occurs in the try clause, the rest of
the clause is skipped. If the exception’s type matches the exception named after the except
keyword, then the except clause is executed. If the exception doesn’t match, then the
exception is unhandled and execution stops.

The except Clause
An except clause may have multiple exceptions, given as a parenthesized tuple:
A try statement can also have more than one except clause:

Finally
Finally, we have finally. finally is an optional block that runs after try, except, and else,
regardless of if an exception is thrown or not. This is good for doing any cleanup that
you want to happen, whether or not an exception is thrown.
As you can see, the Goodbye! gets printed just before the unhandled
KeyboardInterrupt gets propagated up and triggers the traceback.

Advanced Python after beginner python for intermediate learners

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