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Intro variables if statements loops math arrays sorting list comprehension 2d arrays strings queues hash sets hash maps tuples heap functions nested functions classes
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Python for Coding Interviews:Dynamic Typing & Arrays
Dynamic Typing
Python is a dynamically typed language, which means that the
type of a variable is determined at runtime, rather than at
compile time. This allows for flexibility in coding, as variables can
be assigned different types of values at different points in the
program.
Arrays
In Python, arrays are typically represented using lists. A list is a
collection of values, enclosed in square brackets and separated
by commas. Lists can hold values of different types, including
integers, strings, and other lists.
Some useful list methods include:
append(x): adds an item to the end of the list
extend(L): adds all items in a list L to the end of the current
list
insert(i, x): inserts an item x at position i in the list
remove(x): removes the first occurrence of an item x from the
list
pop(i): removes and returns the item at position i in the list
sort(): sorts the list in place
index(x): returns the index of the first occurrence of an
item x in the list
In addition, list comprehension provides a concise way to create
lists based on existing lists or ranges. For example, the list
comprehension [2*x for x in range(5)] generates the list [0,
2, 4, 6, 8].
,While and For Loops
Python has both while and for loops for iteration.
The while statement repeatedly executes a block of code while a
condition is true. The for statement iterates over an iterable
object and executes a block of code for each item in the iterable.
Here is an example of using a for loop to iterate over the
elements in a list:
my_list = [1, 2, 3, 4, 5]
for x in my_list:
print(x)
Functions and Modulo Operator
Python functions are blocks of code that can be called by name.
Functions can take arguments and return values. Functions can
also be used to define recursive algorithms.
The modulo operator % returns the remainder of a division
operation. It can be used to perform a variety of operations, such
as checking whether a number is even or odd, or finding the last
digit of a number.
List Comprehension and Sets
List comprehension provides a concise way to create lists based
on existing lists or ranges. For example, the list
comprehension [2*x for x in range(5)] generates the list [0,
2, 4, 6, 8].
Sets are unordered collections of unique elements. They can be
created using curly braces or the set() constructor. Sets support
various operations, such as union, intersection, and difference,
using the pipe |, ampersand &, and minus - operators,
respectively.
, Queues, Hash Sets, and Hash Maps in
Python
Python has built-in support for queues using
the collections.deque class. Queues are useful for
implementing algorithms that require adding and removing
elements in a specific order.
A hash set is a set that stores elements in a hash table for faster
lookup. It can be implemented in Python using a dictionary.
A hash map is a dictionary that maps keys to values. It can be
implemented using a dictionary in Python.
Python Dictionaries: Building Adjacency
Lists
Dictionaries in Python are data structures that map keys to
values. They are useful for creating adjacency lists for
representing graphs.
Tuples in Hash Tables and Sets
Tuples can be used as keys in hash tables and sets because they
are hashable. They can be used to implement immutable objects,
such as a point in a 2D plane.
Preparing for Coding Interviews with neco.io
Neco.io offers resources to help prepare for coding interviews,
such as practice problems and mock interviews. It is important to
practice coding frequently and review basic data structures and
algorithms to be successful in coding interviews.
Generate Multiple Choice Quiz
While and For Loops in Python
While Loop
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