Introduction
Programmers often prefer Python due to its easy-to-read syntax and friendliness towards beginners. However, hiding underneath is a strong word collection that controls how your code works: keywords. These specific words are important in the Python interpreter, serving as the foundational elements for developing strong programs.
As bricks build a house, keywords are the cornerstone of your Python applications. Comprehending their function and correct application is crucial for creating effective and well-organized code. This article explores Python keywords, giving you the understanding to make the most of them and create successful Python programs.
We will examine different keywords that control the flow of code execution, such as if, else, for, and while. We will identify keywords that define functions (def) and classes (class), which are fundamental elements in modular and object-oriented programming. In addition, you will also acquire knowledge about keywords used for manipulating data.
Python Keywords
Keywords in Python are reserved words that can not be used as variable names, function names, or other identifiers.
| Serial Number | Keyword | Description |
| 1 | False | Boolean value representing falsity |
| 2 | None | Represents the absence of value |
| 3 | True | Boolean value representing truth |
| 4 | and | Logical AND operator |
| 5 | as | Used in aliasing and with statements |
| 6 | assert | Used for debugging to check for conditions |
| 7 | async | Defines an asynchronous context |
| 8 | await | Waits for an asynchronous call to complete |
| 9 | break | Breaks out of the current closest enclosing loop |
| 10 | class | Defines a class |
| 11 | continue | Continues with the next iteration of the loop |
| 12 | def | Defines a function or method |
| 13 | del | Deletes an object |
| 14 | elif | Else if condition |
| 15 | else | An alternative action in conditional statements |
| 16 | except | Used in try-except blocks to catch exceptions |
| 17 | finally | Block of code that executes no matter what |
| 18 | for | Defines a for loop |
| 19 | from | Specifies which module to import names from |
| 20 | global | Declares a global variable |
| 21 | if | Conditional statement |
| 22 | import | Imports a module |
| 23 | in | Checks if a value is present in a sequence |
| 24 | is | Checks if two variables refer to the same object |
| 25 | lambda | Creates an anonymous function |
| 26 | nonlocal | Declares a non-local variable |
| 27 | not | Logical NOT operator |
| 28 | or | Logical OR operator |
| 29 | pass | A null statement, a placeholder |
| 30 | raise | Raises an exception |
| 31 | return | Returns a value from a function |
| 32 | try | Specifies exception handlers and/or cleanup code |
| 33 | while | Defines a while loop |
| 34 | with | Used to wrap the execution of a block of code |
| 35 | yield | Used with generators, returns a generator object |
How to Find All the Python Keywords?
Below is the code which will help you find all the Python keywords:
import keyword
print("There are total {0} keywords in Python".format(len(keyword.kwlist)))
print("The list of keywords is : ")
print(keyword.kwlist)Conclusion
Congratulations! By understanding the role of keywords, you’ve taken a considerable step towards mastering Python. Remember, consistent practice is critical. As you write more Python code, you’ll gain experience using keywords effectively and build a strong foundation for tackling complex programming challenges.
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Hello Neeraj, Very nice piece of information. It is definitely worth a try and the best part of this article was the benchmarking(something on which other articles miss out) against other trivial approaches.
This is just amazing. I am working on the same task of replacing words and finding it difficult, developed rules to achieve the task ( i am using levenshtein distance, association from tm, some custom rules) . But, still the performance is not as desired. Will try this one too. just wondering, ,Does this package exist on R too?
Hi NSS, doubt: i installed pip install flashtext on my system command prompt, it is impoting there on my cmd prompt but still i cannot access this in anaconda (jupyter or spyder). so what to do? do i need to run conda command after running pip command always?
It seems like either you are using different python version in command prompt and jupyter or you are running jupyter in a different environment. To check, please copy the below command to both inside python shell in command prompt and jupyter notebook. Output of the commands should match. import sys sys.executable