文件列表:

1 Recursion -1/ (0, 2022-11-30)
1 Recursion -1/factorial.py (177, 2022-11-30)
1 Recursion -1/fibonacci.py (98, 2022-11-30)
1 Recursion -1/first_index_num.py (417, 2022-11-30)
1 Recursion -1/isSortedBetter.py (180, 2022-11-30)
1 Recursion -1/last_index.py (868, 2022-11-30)
1 Recursion -1/n_is_present_or_not.py (241, 2022-11-30)
1 Recursion -1/power_n.py (114, 2022-11-30)
1 Recursion -1/print_n_num.py (180, 2022-11-30)
1 Recursion -1/sorted_list_or_not.py (229, 2022-11-30)
1 Recursion -1/sum_array.py (158, 2022-11-30)
1 Recursion -1/sum_n_num.py (142, 2022-11-30)
2 Recursion -2/ (0, 2022-11-30)
2 Recursion -2/binarySearch.py (281, 2022-11-30)
2 Recursion -2/merge_sort.py (570, 2022-11-30)
2 Recursion -2/replaceChar.py (201, 2022-11-30)
2 Recursion -2/replace_pi.py (198, 2022-11-30)
CodeChef/ (0, 2022-11-30)
CodeChef/maximise_colors.py (383, 2022-11-30)
CodeChef/secondLargest.py (110, 2022-11-30)
LICENSE (1068, 2022-11-30)
Linked_List/ (0, 2022-11-30)
Linked_List/insert_at_begining.py (679, 2022-11-30)
Linked_List/insert_at_end.py (880, 2022-11-30)
expression_tree.py (1705, 2022-11-30)

# :octocat: Python is a Multi-Paradigm:boom: Language:100: Python supports different styles of writing code. One can write python code in procedural, object oriented, functional or imperative manner. # ## Object Oriented Programmimng Paradigm:abacus: As an object oriented programming language, python supports all the core features of OOP such as inheritance, encapsulation, abstraction, polymorphism etc. The foundation of OOP is class and a class is defined to represent an object which can later be created and manipulated. # ## Procedural Programming Paradigm:printer: In this way the code is grouped in functions and code is serially executed step by step, so basically it combines the sedrial code to instruct computer with each step to perform certain task. # ## Functional Programming Paradigm:joystick: In functional way everything is bind in pure mathematical functions style. It uses the mathematical functions and treats every statements as functional expression as an expression is executed to produce a value # ## Classification of Data Structure: 1.Linear Data Structure: i. Static Data Structure: Array ii.Dynamic Data Structure: * Queue * Linked List * Stack 2.Non-Linear Data Structure: * Tree * Graph Linear data structure: Data structure in which data elements are arranged sequentially or linearly, where each element is attached to its previous and next adjacent elements, is called a linear data structure. Examples of linear data structures are array, stack, queue, linked list, etc. Static data structure: Static data structure has a fixed memory size. It is easier to access the elements in a static data structure. An example of this data structure is an array. Dynamic data structure: In dynamic data structure, the size is not fixed. It can be randomly updated during the runtime which may be considered efficient concerning the memory (space) complexity of the code. Examples of this data structure are queue, stack, etc. Non-linear data structure: Data structures where data elements are not placed sequentially or linearly are called non-linear data structures. In a non-linear data structure, we can’t traverse all the elements in a single run only. Examples of non-linear data structures are trees and graphs. For example, we can store a list of items having the same data-type using the array data structure.

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