Tutorial Playlist
200 Lessons1. Introduction to Python
2. Features of Python
3. How to install python in windows
4. How to Install Python on macOS
5. Install Python on Linux
6. Hello World Program in Python
7. Python Variables
8. Global Variable in Python
9. Python Keywords and Identifiers
10. Assert Keyword in Python
11. Comments in Python
12. Escape Sequence in Python
13. Print In Python
14. Python-if-else-statement
15. Python for Loop
16. Nested for loop in Python
17. While Loop in Python
18. Python’s do-while Loop
19. Break in Python
20. Break Pass and Continue Statement in Python
21. Python Try Except
22. Data Types in Python
23. Float in Python
24. String Methods Python
25. List in Python
26. List Methods in Python
27. Tuples in Python
28. Dictionary in Python
29. Set in Python
30. Operators in Python
31. Boolean Operators in Python
32. Arithmetic Operators in Python
33. Assignment Operator in Python
34. Bitwise operators in Python
35. Identity Operator in Python
36. Operator Precedence in Python
37. Functions in Python
38. Lambda and Anonymous Function in Python
39. Range Function in Python
40. len() Function in Python
41. How to Use Lambda Functions in Python?
42. Random Function in Python
43. Python __init__() Function
44. String Split function in Python
45. Round function in Python
46. Find Function in Python
47. How to Call a Function in Python?
48. Python Functions Scope
49. Method Overloading in Python
50. Method Overriding in Python
51. Static Method in Python
52. Python List Index Method
53. Python Modules
54. Math Module in Python
55. Module and Package in Python
Now Reading
56. OS module in Python
57. Python Packages
58. OOPs Concepts in Python
59. Class in Python
60. Abstract Class in Python
61. Object in Python
62. Constructor in Python
63. Inheritance in Python
64. Multiple Inheritance in Python
65. Encapsulation in Python
66. Data Abstraction in Python
67. Opening and closing files in Python
68. How to open JSON file in Python
69. Read CSV Files in Python
70. How to Read a File in Python
71. How to Open a File in Python?
72. Python Write to File
73. JSON Python
74. Python JSON – How to Convert a String to JSON
75. Python JSON Encoding and Decoding
76. Exception Handling in Python
77. Recursion in Python
78. Python Decorators
79. Python Threading
80. Multithreading in Python
81. Multiprocеssing in Python
82. Python Regular Expressions
83. Enumerate() in Python
84. Map in Python
85. Filter in Python
86. Eval in Python
87. Difference Between List, Tuple, Set, and Dictionary in Python
88. List to String in Python
89. Linked List in Python
90. Length of list in Python
91. Reverse a List in Python
92. Python List remove() Method
93. How to Add Elements in a List in Python
94. How to Reverse a List in Python?
95. Difference Between List and Tuple in Python
96. List Slicing in Python
97. Sort in Python
98. Merge Sort in Python
99. Selection Sort in Python
100. Sort Array in Python
101. Sort Dictionary by Value in Python
102. Datetime Python
103. Random Number in Python
104. 2D Array in Python
105. Abs in Python
106. Advantages of Python
107. Anagram Program in Python
108. Append in Python
109. Applications of Python
110. Armstrong Number in Python
111. Assert in Python
112. Binary Search in Python
113. Binary to Decimal in Python
114. Bool in Python
115. Calculator Program in Python
116. chr in Python
117. Control Flow Statements in Python
118. Convert String to Datetime Python
119. Count in python
120. Counter in Python
121. Data Visualization in Python
122. Datetime in Python
123. Extend in Python
124. F-string in Python
125. Fibonacci Series in Python
126. Format in Python
127. GCD of Two Numbers in Python
128. How to Become a Python Developer
129. How to Run Python Program
130. In Which Year Was the Python Language Developed?
131. Indentation in Python
132. Index in Python
133. Interface in Python
134. Is Python Case Sensitive?
135. Isalpha in Python
136. Isinstance() in Python
137. Iterator in Python
138. Join in Python
139. Leap Year Program in Python
140. Lexicographical Order in Python
141. Literals in Python
142. Matplotlib
143. Matrix Multiplication in Python
144. Memory Management in Python
145. Modulus in Python
146. Mutable and Immutable in Python
147. Namespace and Scope in Python
148. OpenCV Python
149. Operator Overloading in Python
150. ord in Python
151. Palindrome in Python
152. Pass in Python
153. Pattern Program in Python
154. Perfect Number in Python
155. Permutation and Combination in Python
156. Prime Number Program in Python
157. Python Arrays
158. Python Automation Projects Ideas
159. Python Frameworks
160. Python Graphical User Interface GUI
161. Python IDE
162. Python input and output
163. Python Installation on Windows
164. Python Object-Oriented Programming
165. Python PIP
166. Python Seaborn
167. Python Slicing
168. type() function in Python
169. Queue in Python
170. Replace in Python
171. Reverse a Number in Python
172. Reverse a string in Python
173. Reverse String in Python
174. Stack in Python
175. scikit-learn
176. Selenium with Python
177. Self in Python
178. Sleep in Python
179. Speech Recognition in Python
180. Split in Python
181. Square Root in Python
182. String Comparison in Python
183. String Formatting in Python
184. String Slicing in Python
185. Strip in Python
186. Subprocess in Python
187. Substring in Python
188. Sum of Digits of a Number in Python
189. Sum of n Natural Numbers in Python
190. Sum of Prime Numbers in Python
191. Switch Case in Python
192. Python Program to Transpose a Matrix
193. Type Casting in Python
194. What are Lists in Python?
195. Ways to Define a Block of Code
196. What is Pygame
197. Why Python is Interpreted Language?
198. XOR in Python
199. Yield in Python
200. Zip in Python
If you have a basic understanding of Python then you must also be aware of how important module and package in Python is. Both these functionalities are required in Python to structure and organize code. However, they serve different purposes. Where a module is a simple Python file, a package is a collection of multiple modules.
In this tutorial, we will dive into a comprehensive exploration of one of Python's most important and potent functions; module and package in Python. This manual has been carefully tailored for professionals looking to hone their Python proficiency and this digs deep into these functions to illustrate their importance and effectiveness. As we proceed on this journey, you will learn how modules and packages can drastically alter the way you approach some coding issues, particularly with reusability and accuracy in mind.
Python, which is renowned for its flexibility and efficiency, gives developers a wide range of functions based on modules and packages. Module and package in Python stand out among the broad group of functionalities being particularly noteworthy. They stand out for their clarity and reusability, which makes them vital tools for developers who want to build code that is clearer and more organized.
This tutorial establishes what modules and packages actually are and provides a glimpse into the power of these functions and how, despite their conciseness, they serve a crucial part in a Python programmer's toolkit.
Modules in Python can be simple Python files or it can be a mixture of multiple functions that can be applied to offer numerous functionalities to a Python program. So, we can use Python modules in a multipurpose way with the main aim of providing functionalities in a program. A Python module is generally denoted in the form of a .py extension file.
Modules in Python are generally statements in a Python program that incorporate various types of Python functions and variables to successfully perform certain tasks. Python modules can be depicted as a ready-made library to use the provided codes in some other scripts as well. These codes can be easily accessed by other programmers to use them and their projects.
You can check out the modules in Python example to better understand the concept:
# importing the library and module
import math
from math import pow
# using the pow() function
pow(3, 5)
# printing pow()
print(pow)
In the following code snippet, we have used the pow() function to see the result of the powers of the number and imported the required module. Thereafter we have printed the value of the particular calculation for the user by applying the print statement.
However, there are two types of modules in Python that we have explained below:
Built-in modules in Python are those modules that have been built to streamline various processes and enhance the readability of codes. Python has an impressive collection of built-in modules. These modules offer an abundance of functions and can be accessed immediately even without installing any of the Python packages.
Because of the built-in modules in Python, it offers a wide range of functions and tools that help developers effectively achieve their tasks and troubleshoot coding issues. It does not require the installation of any additional applications or packages.
Here are some examples for you to understand the function of built-in modules in Python:
Code:
# Example using the os module
import os
print(os.getcwd())
print(os.listdir())
# Example using the sys module
import sys
print(sys.version)
print(sys.argv)
# Example using the math module
import math
print(math.pi)
print(math.sin(math.pi / 2))
# Example using the json module
import json
data = {
"name": "John Doe",
"age": 30,
"city": "New York"
}
json_data = json.dumps(data)
print(json_data)
# Example using the datetime module
import datetime
now = datetime.datetime.now()
print(now)
print(now.year)
print(now.month)
print(now.day)
# Example using the re module
import re
text = "The quick brown fox jumps over the lazy dog."
result = re.search(r"fox", text)
print(result.start(), result.end(), result[0])
# Example using the random module
import random
print(random.randint(1, 100))
print(random.choice([1, 2, 3, 4, 5]))
Outputs:
User-defined modules in Python are those modules that are created by the users to make their projects easy and simple. These modules may contain various classes, variables, functions, tools, and a variety of codes that can again be used while carrying out some other project.
Let us walk you through the concept of user-defined modules in Python with the help of an example:
# calculator.py
def add(a, b):
return a + b
def sub(a, b):
return a - b
def mul(a, b):
return a * b
def div(a, b):
return a / b
# main.py
import calculator
print("Addition of 5 and 4 is:", calculator.add(5, 4))
print("Subtraction of 7 and 2 is:", calculator.sub(7, 2))
print("Multiplication of 3 and 4 is:", calculator.mul(3, 4))
print("Division of 12 and 3 is:", calculator.div(12, 3))
Packages in Python are regarded as a collection of data and materials that allows the developers to start writing codes for their projects. Python package serves as a user variable API for any source code. In this way, developers can enable any functional runtime script at any moment, using Python packages.
Python modules and package lists are very useful in collaborating with other modules. The main aim of Python packages is to divide large amounts of code into smaller divisions so that they can be effectively used to create large-scale real-world applications. A Python package is generally denoted as a __init__.py file.
Let us explain this concept with the help of an example that demonstrates a package in Python:
# importing the package
import science
# printing a statement
print("We have imported the science package")
Output:
We have imported the science package
In the following code snippet, we have explained the uses and functionality of a Python package and printed a statement for the users.
A Python library can be defined as a collection of source code that can be used multiple times in an iterative manner. Python libraries are very important as it saves a lot of time and is also an open-source platform. Just like a physical library, a Python library also consists of numerous resources in the form of source code that can be used as and when required.
Additionally, a group of connected modules is also named a Python library. It consists of a variety of code bundles that are utilized by the programmers according to their requirements. Thereafter programmers need not write the same long codes repeatedly.
The Python library makes the job of programmers a bit easier. They can simply copy the source chords from the Python library rather than writing the same codes again. Disciplines like machine learning, data visualization, computer science, etc. significantly rely upon Python libraries.
Let's illustrate the importation of a Python library with the help of an example:
import pandas as pd
df=pd.read_csv("file_name.csv
")
In the following code snippet, we are importing the pandas library.
Python modules and packages are different from each other. A Python package defines codes as a distinct unit for every function, whenever incorporating a library. Whereas a Python module is in itself a separate library that consists of various functionalities. The major advantage that Python packages offer over modules is that the codes can be reused.
Thus, a Python package is different from a Python module majorly in the following two heads:
A default namespace is assigned to a program whenever it is executed for the first time in a package. This namespace helps to provide an identification mark to that particular source code. However, a beginner programmer can also incorporate them from the library. Always try to stick to general namespaces for the codes to run effortlessly.
Here's a code example for you to understand the functionality of explicit namespaces:
def Acad():
para = "upgrad"
Acad()
Output:
>>> Acad
<function namespace at 0x000001F91DE9FF70>
>>>
With the convenience API, you can namespace certain code objects. In this way, you can reach the core of the code and see where the problem lies and how you can solve it. Also, it helps in analyzing codes that you may use as a user interface as and when required.
Let's illustrate the performance of convenience API with the help of an example:
import hello
hello.hey()
Output:
Error
Modules in Python and packages are closely related to each other but they have certain differences. Let us explain to you the difference between modules and files in Python that are stated as under:
Basis | Python Module | Python Package |
Meaning | A Python module is a simple Python file or a collection of various functions required to perform a program. | A Python package is a collection of multiple modules, denoted in a __init__.py file. |
Objective | The main objective of creating a Python module is to properly organize codes. | The purpose of a Python package is to instill distribution and reusability of codes. |
Organization | A Python module organizes source code within a simple file. | A Python package organizes related modules in a directory hierarchy. |
Necessary for | Python modules are required for only Python files that are .py format files. | Python packages are required for both .py files and __init__.py files. |
Sub-modules | There are no sub-modules. | There are multiple sub-modules and sub-packages in a Python package. |
How to import | import module_name | import package_name.module_name |
Example | Popular examples of Python modules are CSV, OS datetime, math, etc. | NumPy, Django, Pandas, and Matplotlib are some instances of a Python package. |
We now recognize the crucial impact that Python's modules and packages had in influencing our programming experience after navigating through the language's many subtleties. Together, modules and packages provide the fundamental reusability and dynamism that balance the language. Understanding such components becomes increasingly important as we continue on our Python development journey and if we are to write effective, organized, and optimized code.
However, there is much more to learn about Python. Programming is a huge and constantly changing field. upGrad provides a wide range of upskilling courses for enthusiastic professionals who share a thirst for education. With upGrad, dive deeper, learn more, and let your coding adventure grow.
1. Is NumPy a module or a package?
NumPy is definitely a package as it includes multiple sub-modules such as random, doc, FFT, etc. It can be said that NumPy is a collection of modules.
2. How to use a Python import file?
To import a file or a module, build a Python script and use the 'import' keyword followed by the name of the module. Do not specify the file extension here. For instance, import my_ module.
3. How many modules are there in Python?
A standard Python library contains more than 200 modules. The exact number of the module may vary from one distribution to another.
PAVAN VADAPALLI
Director of Engineering
Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working …Read More
Popular
Talk to our experts. We’re available 24/7.
Indian Nationals
1800 210 2020
Foreign Nationals
+918045604032
upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enrolling. upGrad does not make any representations regarding the recognition or equivalence of the credits or credentials awarded, unless otherwise expressly stated. Success depends on individual qualifications, experience, and efforts in seeking employment.
upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...