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15. Python for Loop
19. Break in Python
23. Float in Python
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27. Tuples in Python
29. Set in Python
53. Python Modules
57. Python Packages
59. Class in Python
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84. Map in Python
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86. Eval in Python
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125. Format in Python
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132. Interface in Python
134. Isalpha in Python
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137. Join in Python
140. Literals in Python
141. Matplotlib
144. Modulus in Python
147. OpenCV Python
149. ord in Python
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156. Python Arrays
158. Python Frameworks
160. Python IDE
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165. Python Seaborn
166. Python Slicing
168. Queue in Python
169. Replace in Python
173. Stack in Python
174. scikit-learn
175. Selenium with Python
176. Self in Python
177. Sleep in Python
179. Split in Python
184. Strip in Python
185. Subprocess in Python
186. Substring in Python
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197. XOR in Python
198. Yield in Python
199. Zip in Python
Diving into the profound depths of Python programming, we often come across terminologies that set the foundation for the language. Among these, keywords and identifiers play an integral role in shaping the way we perceive and utilize Python.
In this tutorial, we'll embark on an illuminating journey to explore these cornerstones, unveiling their significance, characteristics, and application. While keywords anchor the language with predefined, unalterable terms, identifiers offer the flexibility to name variables, functions, and more. Together, Python keywords and identifiers are indispensable for any Python programmer aiming for mastery and precision.
At the heart of Python's intuitive syntax lie its keywords, a set of reserved words that drive the core functionality of the programming language. Each keyword is like a specialized tool, intricately designed for specific tasks, ensuring the language remains structured yet versatile. On the other side, we have identifiers, which bestow us with the freedom to define our constructs, be it naming a variable that stores data or a function that performs a sequence of operations. In this tutorial, we will offer a glimpse into the vast universe of Python keywords and identifiers, preparing you for the basics of programming.
In the vast landscape of programming languages, Python stands out with its clear syntax and concise code. A pivotal element contributing to this clarity is Python's keywords. As we delve deeper into understanding these, it becomes evident that keywords are more than just reserved words; they are the foundational pillars that uphold the language's structure.
Every programming language possesses its own set of reserved words, and Python is no different. These keywords have predefined meanings and serve specific functions, ensuring that developers have a standardized way of executing particular operations. What sets Python apart, however, is the intuitive nature of its keywords, making it easy for both beginners and seasoned programmers to adopt.
Keyword Category | Representative Examples | Core Functionality |
Control Flow | if, else | Steer program logic |
Loop | for, while | Drive iteration |
Exception Handling | try, except | Address code exceptions |
Class/Function | def, class | Frame functions & classes |
In Python, keywords are reserved words that have special meanings and purposes in the language. These words cannot be used as identifiers (variable names, function names, etc.) because they are already assigned specific roles within the language. Here is a list of Python keywords:
It's important to note that Python keywords are case-sensitive, which means that if is a keyword, but IF or If are not. Additionally, keep in mind that these keywords cannot be used as variable names, function names, or any other identifiers within your code.
For the most up-to-date and accurate list of Python keywords, you can refer to the official Python documentation or use the keyword module in Python:
Code:
import keyword
print(keyword.kwlist)
Example:
# Defining a function using the "def" keyword
def greet(name):
print("Hello,", name)
# Using the "if" and "else" keywords to perform conditional branching
def check_age(age):
if age < 18:
print("You are a minor.")
else:
print("You are an adult.")
# Using the "for" keyword to iterate through a list
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(fruit)
# Using the "while" keyword for a loop with a condition
count = 0
while count < 5:
print("Count:", count)
count += 1
# Using the "return" keyword to return a value from a function
def add(a, b):
return a + b
# Using the "import" keyword to import a module
import math
print("Square root of 16:", math.sqrt(16))
# Using the "try", "except", and "finally" keywords for exception handling
try:
result = 10 / 0
except ZeroDivisionError:
print("Cannot divide by zero")
finally:
print("Exception handling complete")
# Using the "and" and "or" keywords for logical operations
x = True
y = False
print("x and y:", x and y)
print("x or y:", x or y)
Explanation:
# Using the "if" and "else" keywords to perform conditional branching
def check_age(age):
if age < 18:
print("You are a minor.")
else:
print("You are an adult.")
In this section, you've defined a function check_age that takes an age parameter. The function uses the if keyword to perform a conditional check. If the age is less than 18, it prints "You are a minor." Otherwise, it prints "You are an adult."
# Using the "for" keyword to iterate through a list
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(fruit)
Here, you've created a list of fruits and then used the for keyword to iterate through each fruit in the list. The variable fruit takes on each value in the fruits list, and the loop prints each fruit's name.
# Using the "while" keyword for a loop with a condition
count = 0
while count < 5:
print("Count:", count)
count += 1
This code block demonstrates a while loop. It initializes a count variable to 0 and then enters a loop that prints the current value of count and increments it by 1. The loop continues as long as the count is less than 5.
# Using the "return" keyword to return a value from a function
def add(a, b):
return a + b
Here, you've defined a function add that takes two parameters a and b. The function returns the sum of a and b using the return keyword.
# Using the "import" keyword to import a module
import math
print("Square root of 16:", math.sqrt(16))
This code demonstrates the use of the import keyword. It imports the math module and then uses the math.sqrt() function to calculate and print the square root of 16.
# Using the "try", "except", and "finally" keywords for exception handling
try:
result = 10 / 0
except ZeroDivisionError:
print("Cannot divide by zero")
finally:
print("Exception handling complete")
This section uses the try, except, and finally keywords for exception handling. It attempts to perform a division by zero, which would raise a ZeroDivisionError exception. The except block catches the exception and prints an error message. The finally block always runs, whether an exception occurred or not.
# Using the "and" and "or" keywords for logical operations
x = True
y = False
print("x and y:", x and y)
print("x or y:", x or y)
Lastly, you're using the and and or keywords to perform logical operations. The code prints the result of the logical AND and logical OR operations between the boolean values x and y.
Code:
print("example of True, False, and, or, not keywords")
print(True and True)
print(True or False)
print(not False)
In Python, identifiers are names given to various programming elements such as variables, classes, modules, functions, etc. These names are used to uniquely identify these elements in your code. Here are the rules for creating valid identifiers in Python:
Here are some examples of valid identifiers in Python:
variable_name = 42
_total = 100
myFunction = lambda x: x * 2
MyClass = MyClassDefinition()
And here are some examples of invalid identifiers:
3var = "Invalid" # Identifier can't start with a digit
my-variable = 10 # Hyphens are not allowed in identifiers
class = "Class" # 'class' is a keyword and cannot be used as an identifier
Remember that using descriptive and meaningful names for your identifiers is important for code readability and maintainability.
It's worth noting that while underscores at the beginning of identifiers have no special meaning in terms of the Python language itself, a common convention is to use a single underscore at the beginning of an identifier to indicate that it's intended to be a "private" or "internal" variable, function, or method within a class or module. For example:
_internal_variable = 42
Code:
for j in range(1, 10):
print(j)
if j < 4:
continue
else:
break
Here are the rules for naming valid identifiers in Python:
Here are some examples of valid and invalid identifiers based on these rules:
Valid Identifiers:
variable_name = 42
_total = 100
my_function = lambda x: x * 2
MyClass = MyClassDefinition()
Invalid Identifiers:
3var = "Invalid" # Starts with a digit
my-variable = 10 # Contains hyphen
class = "Class" # Same as a keyword
Code:
for i in range(1,7):
if i == 1:
print('One')
elif i == 2:
print('Two')
else:
print('else block execute')
Code:
def upGrad():
p=20
if(p % 2 == 0):
print("given number is even")
else:
print("given number is odd")
upGrad()
Having navigated through the intricate nuances of Python's keywords and identifiers, we now appreciate their pivotal role in shaping our programming journey. Their synergy balances the language, with keywords providing the foundational rigidity and identifiers infusing dynamism.
As we continue to evolve in our Python journey, understanding such elements becomes instrumental in writing efficient, clean, and optimized code. However, the road to mastering Python doesn't end here. The realm of programming is vast and ever-evolving. For those enthusiastic professionals who resonate with a hunger for knowledge, upGrad offers a multitude of upskilling courses. Dive deeper, explore further, and let your coding journey flourish with upGrad.
1. What are keywords in Python?
Keywords in Python are reserved words with specific functions and meanings, essential in determining the structure of the language.
2. What is the difference between keywords and identifiers in Python?
While keywords are reserved words with predefined meanings, identifiers are user-defined names given to entities like variables and functions.
3. All keywords in Python are in which case?
All keywords in Python are in lowercase, emphasizing the language’s case sensitivity.
4. How are identifiers in Python chosen?
Identifiers are user-defined and should be chosen descriptively, avoiding any conflict with existing keywords.
5. Why is understanding keywords essential for advanced Python programming?
Grasping keywords ensures streamlined coding, as these words help structure the language, facilitating the creation of efficient programs.
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