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Functional AssessmentVerdict: ✅ Completed🧠 User Story ID: AC-001-A — Added Changes📝 Feature CompletenessThe Requirement was.. The system must incorporate the added changes as referenced in the input, ensuring general implementation of unspecified system updates. This is what is built... A comprehensive suite of Python programs was implemented, covering algorithms, data structures, networking, and utility scripts. 📊 Implementation Status
✅ Completed Components
🎯 Conclusion & Final AssessmentImportant 🟢 Completed Features: Key completed features include the implementation of various sorting algorithms (Bubble, Selection, Insertion, Merge, Quick), data structures (Array, Stack, Singly/Doubly Linked Lists), and networking tools (Port Scanner, Client-Server multithreading). |
| from _thread import * | ||
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| ServerSocket = socket.socket() | ||
| host = '127.0.0.1' |
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Hardcoded IP Address for Server Binding
I noticed the server is hardcoded to bind to 127.0.0.1. This restricts connections to the local machine only and will prevent the service from being accessible in containerized environments (like Docker) or when deployed to a cloud VM.
Let's change this to 0.0.0.0 to allow the server to listen on all available network interfaces. This makes the application portable and ready for deployment.
| host = '127.0.0.1' | |
| host = '0.0.0.0' |
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| ServerSocket = socket.socket() | ||
| host = '127.0.0.1' | ||
| port = 1233 |
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Hardcoded Port Number
I see the port number 1233 is hardcoded. This can lead to port conflicts in different environments and makes it difficult to reconfigure the application without changing the code.
Let's externalize this by reading the port from an environment variable, with a fallback to a default value. This is a standard practice for building configurable and portable applications.
| port = 1233 | |
| port = int(os.getenv('PORT', 1233)) |
| import socket | ||
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| ClientSocket = socket.socket() | ||
| host = '127.0.0.1' |
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Hardcoded IP Address for Client Connection
I noticed the client is hardcoded to connect to 127.0.0.1. This will only work for local testing and will fail when the client and server are deployed on different machines or in different containers.
Let's make this configurable by reading the target host from an environment variable. This will allow you to point the client to any server (e.g., a staging or production endpoint) without modifying the code.
| host = '127.0.0.1' | |
| host = os.getenv('SERVER_HOST', '127.0.0.1') |
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| ClientSocket = socket.socket() | ||
| host = '127.0.0.1' | ||
| port = 1233 |
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Hardcoded Port Number in Client
I see the client is configured to connect to port 1233, which is hardcoded. This creates a tight coupling with the server's configuration and requires code changes if the server port is ever updated.
Let's externalize this by reading the port from an environment variable, ensuring it stays in sync with the server's configuration.
| port = 1233 | |
| port = int(os.getenv('SERVER_PORT', 1233)) |
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| import hashlib | ||
| BLOCKSIZE = 65536 # Block read size if file is big enough | ||
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' |
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Hardcoded File Path
I've spotted a hardcoded absolute file path here. This path is specific to one user's machine and will cause the script to fail when run in any other environment, such as a CI/CD pipeline, a Docker container, or another developer's machine.
Let's make this script portable by accepting the file path as a command-line argument. This is a much more flexible and robust approach.
| import hashlib | ||
| BLOCKSIZE = 65536 # Block read size if file is big enough | ||
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' | ||
| hasher = hashlib.md5() |
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Use of Insecure MD5 Hashing Algorithm
I noticed the script is using hashlib.md5(). The MD5 algorithm is considered cryptographically broken and is not suitable for security-sensitive applications due to its vulnerability to hash collisions.
Let's switch to a more secure hashing algorithm like SHA-256. This will provide much stronger guarantees for file integrity checks.
| hasher = hashlib.md5() | |
| hasher = hashlib.sha256() |
🔍 Technical Quality Assessment📋 SummaryThis update adds a collection of tools for data organization, security, and basic calculations. While these tools provide new capabilities for handling information, several critical errors were found that could cause the system to crash or produce incorrect results for our users. These issues must be addressed to ensure a reliable and professional experience. 💼 Business Impact
🎯 Purpose & Scope
📊 Change AnalysisFiles by Category:
Impact Distribution:
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| File | Status | Description | Impact | Issues Detected |
|---|---|---|---|---|
Test2/P01_hello.py |
Added ( +28/ -0) | Added a new Python script that performs basic arithmetic operations and prints messages. | Low – The script is a standalone utility for basic calculations and printing, with minimal impact on the broader system. | 1 |
Test2/P04_Factorial.py |
Added ( +17/ -0) | Added a recursive factorial calculation script with basic input handling. | High – The current implementation contains a logic flaw that leads to infinite recursion and a stack overflow when a negative number is provided. | 2 |
Test2/P05_Pattern.py |
Added ( +112/ -0) | Added several functions to print different star patterns and a main block for user interaction. | Low – The changes introduce basic pattern printing logic which is primarily for educational or demonstration purposes. | 2 |
Test2/P06_CharCount.py |
Added ( +18/ -0) | Added a script to calculate character frequency in a given string. | Low – The script provides basic string processing functionality but contains inefficient dictionary key lookups. | 1 |
Test2/P07_PrimeNumber.py |
Added ( +23/ -0) | Added a Python script to check if a given number is prime. | Medium – The script provides a functional prime number checker but contains logical redundancies and potential output duplication for specific inputs. | 1 |
Test2/P20_OsModule.py |
Added ( +13/ -0) | Added a script demonstrating basic os module operations including directory creation and renaming. | Medium – The script performs file system operations that could fail if the directory already exists or if renaming targets non-existent files. | 1 |
Test2/P21_GuessTheNumber.py |
Added ( +24/ -0) | A simple 'Guess the Number' game implementation using the random module. | Low – This is a standalone script for a game; changes do not affect other parts of the system. | 2 |
Test2/P22_SequentialSearch.py |
Added ( +23/ -0) | Implementation of a sequential search algorithm with iteration counting. | Low – Adds a basic search utility. The use of global state for iteration counting may cause issues in concurrent or repeated calls. | 1 |
Test2/P23_BinarySearch.py |
Added ( +29/ -0) | Implementation of a standard binary search algorithm with iteration tracking. | Low – The changes provide a functional binary search utility, though the use of global state for iteration counting may cause issues in multi-threaded or imported contexts. | 1 |
Test2/P24_SelectionSort.py |
Added ( +21/ -0) | Implementation of the Selection Sort algorithm in Python. | Low – Adds a standard sorting utility function to the codebase. | 0 |
Test2/P25_BubbleSort.py |
Added ( +24/ -0) | Implementation of the Bubble Sort algorithm in Python with a basic test case. | Low – Adds a standard sorting utility function. The implementation is functionally correct but uses a non-optimized version of the algorithm. | 1 |
Test2/P26_InsertionSort.py |
Added ( +25/ -0) | Implementation of the Insertion Sort algorithm in Python. | Medium – Provides a sorting utility; however, the current implementation contains a logical flaw that can lead to data corruption in specific scenarios. | 1 |
Test2/P27_MergeSort.py |
Added ( +42/ -0) | Implementation of the Merge Sort algorithm including merge and mergeSort functions. | Medium – The implementation provides a functional sorting algorithm, but contains a performance bottleneck due to inefficient list manipulations. | 1 |
Test2/P28_QuickSort.py |
Added ( +65/ -0) | Added two implementations of the QuickSort algorithm: a standard in-place version and a more Pythonic list-comprehension based version. | Medium – The changes introduce sorting functionality. However, the in-place implementation contains a logic error that will cause incorrect sorting results. | 1 |
Test2/P29_ArgumentParser.py |
Added ( +21/ -0) | Added a Python script demonstrating the use of argparse to handle command-line arguments. | Low – The script provides a basic CLI interface for a specific function but has minor logical gaps in user guidance. | 1 |
Test2/P30_Array.py |
Added ( +107/ -0) | Implementation of a custom Array class in Python with basic insertion, deletion, and search operations. | Medium – The custom Array class has several logical flaws in its insertion and initialization logic that could lead to data corruption or runtime errors. | 4 |
Test2/P31_SinglyLinkedList.py |
Added ( +95/ -0) | Implementation of a Singly Linked List with basic operations like add, size, search, and remove. | Medium – The implementation provides core data structure functionality but contains a critical bug in the remove method that could lead to runtime crashes. | 1 |
Test2/P32_Multithreading_Client.py |
Added ( +24/ -0) | Implementation of a multithreaded TCP client that connects to a local server and exchanges messages in a loop. | Medium – The client establishes a connection and enters an infinite loop for communication, but lacks proper resource cleanup and error handling for connection loss. | 2 |
Test2/P32_Mutithreading_Server.py |
Added ( +38/ -0) | Implementation of a multithreaded TCP server using the socket and _thread modules. | Medium – The script provides a basic multithreaded server but contains logical flaws in connection handling and resource management that could lead to crashes or resource exhaustion. | 3 |
Test2/P33_DoublyLinkedList.py |
Added ( +108/ -0) | Implementation of a Doubly Linked List with basic operations like insertFirst, insertLast, and remove. | Medium – The implementation contains critical logic errors in the insertLast and remove methods that will cause runtime crashes or data corruption. | 2 |
Test2/P34_Stack.py |
Added ( +58/ -0) | Implementation of a Stack data structure with basic operations like push, pop, peek, and size checks. | Medium – The changes introduce a core data structure. However, a logic error in the empty check will cause the stack to behave incorrectly during runtime. | 1 |
Test2/P35_NarySearch.py |
Added ( +81/ -0) | Implementation of an N-ary search algorithm to find a key in a large sorted array. | High – The algorithm contains several logical flaws in boundary handling and partition logic that will cause it to fail for many keys or crash with index out of bounds errors. | 3 |
Test2/P36_SimpleReaderWriter.py |
Added ( +41/ -0) | Implementation of a simple Reader-Writer synchronization problem using a single Mutex lock. | Medium – The code demonstrates a basic synchronization pattern but contains potential runtime errors due to variable scoping and lacks optimal concurrency for multiple readers. | 2 |
Test2/P37_HangmanGame.py |
Added ( +76/ -0) | Implementation of a Hangman game in Python using random word selection and basic input validation. | Medium – The changes introduce a functional game, but several logic errors in state management and input handling will cause incorrect behavior during gameplay. | 3 |
Test2/P38_HashingFile.py |
Added ( +13/ -0) | Added a script to calculate the MD5 hash of a file using block reading for efficiency. | Medium – Provides a functional utility for file integrity checking, though it uses a cryptographically weak hashing algorithm. | 1 |
Test2/P39_Queue.py |
Added ( +0/ -0) | The file was added but appears to be empty based on the provided diff information. | Low – An empty file has no functional impact on the application logic. | 0 |
Test2/P40_CipherText copy.py |
Added ( +59/ -0) | Added a simple Caesar cipher implementation for encryption and decryption of text messages. | Medium – The implementation contains logical flaws in the wrapping logic and character handling that will result in incorrect encryption/decryption for certain keys and non-alphabetic characters. | 3 |
Test2/P40_CipherText.py |
Added ( +59/ -0) | Added a Caesar cipher implementation for encrypting and decrypting lowercase English text using a numeric key. | Medium – Provides basic cryptographic functionality but contains logical flaws in character wrapping and decryption logic that will result in incorrect output for certain keys. | 2 |
Test2/P41_PortScanner.py |
Added ( +26/ -0) | Added a simple port scanner script that checks for open ports on a given host within the range 1-1023. | Medium – The script provides basic port scanning functionality but has significant performance bottlenecks and potential reliability issues due to sequential scanning and lack of timeouts. | 2 |
Test2/P42_MultiprocessingPipes.py |
Added ( +25/ -0) | Added a script demonstrating multiprocessing communication using Pipes. | Medium – The script demonstrates inter-process communication but contains a logical flaw that will cause it to hang indefinitely. | 1 |
| print("Divide value is:", divide_value) | ||
| print("Multiply value is:", multiply_value) | ||
| print("Modulus:", increment_value % base_value ) # % -> remainder | ||
| print('Addition is:', int(a) + int(b)) |
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Undefined Variable Reference
I noticed that we're trying to use variables a and b in the addition logic, but they haven't been defined anywhere in the function or global scope. This will cause a NameError as soon as the code reaches this line. We should use the variables first_number and second_number that were collected from the user input earlier.
| print('Addition is:', int(a) + int(b)) | |
| print('Addition is:', int(first_number) + int(second_number)) |
| def factorial(number): | ||
| '''This function finds the factorial of the number passed as argument''' | ||
| if number < 0: | ||
| print('Invalid entry! Cannot find factorial of a negative number') |
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Infinite Recursion on Negative Input
I noticed that when a negative number is entered, the function prints an error message but continues execution. Since it doesn't return early, it proceeds to the recursive call, leading to a RecursionError (stack overflow). We should return None or raise an exception immediately after detecting a negative input.
| print('Invalid entry! Cannot find factorial of a negative number') | |
| return None |
| if number < 0: | ||
| print('Invalid entry! Cannot find factorial of a negative number') | ||
| if number == 0 or number == 1: | ||
| print("Hello") |
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| ''' | ||
| # first loop for number of lines | ||
| for i in range(level + 1): |
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Redundant Empty Line in Pattern 5
I noticed that pattern5 prints an extra empty line at the start. This happens because the loop starts at i=0, resulting in range(-1) for stars. We should start the range from 1 to match the intended pattern.
| for i in range(level + 1): | |
| for i in range(1, level + 1): |
| def pattern6(userInput): | ||
| ''' | ||
| following is the another approach to solve pattern problems with reduced time complexity | ||
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| for | ||
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| * | ||
| ** | ||
| *** | ||
| **** | ||
| ***** | ||
| ''' | ||
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| num = userInput | ||
| pattern = '*' | ||
| string = pattern * num | ||
| x = 0 | ||
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| for i in string: | ||
| x = x + 1 | ||
| print(string[0:x]) |
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| print(os.getcwd()) #Prints the current working directory | ||
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| os.mkdir('newDir1') |
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Potential FileExistsError
I notice we're calling os.mkdir('newDir1') without checking if the directory already exists. If this script is run a second time, it will crash with a FileExistsError. We should add a check or use exist_ok=True to make this more robust.
| os.mkdir('newDir1') | |
| if not os.path.exists('newDir1'): | |
| os.mkdir('newDir1') |
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| def guess(): | ||
| ''' This function guesses the randomnly generated number ''' | ||
| randomNumber = random.randint(0, 21) |
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Off-by-One Error in Random Range
I noticed that the random number is generated between 0 and 21, but the user prompt suggests the range is 0 to 20. This means a user could never guess the number 21 if it's generated, leading to a frustrating experience. We should align the generation range with the user instructions.
| randomNumber = random.randint(0, 21) | |
| randomNumber = random.randint(0, 20) |
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| while True: | ||
| count += 1 | ||
| number = int(input('Enter the number between 0 to 20: ')) |
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Potential Runtime Crash on Invalid Input
Currently, if a user enters something that isn't a number (like a letter or a blank space), the program will crash with a ValueError. It's a good practice to wrap the input conversion in a try-except block to handle these cases gracefully and keep the game running.
| number = int(input('Enter the number between 0 to 20: ')) | |
| try: | |
| number = int(input('Enter the number between 0 to 20: ')) | |
| except ValueError: | |
| print('Please enter a valid integer.') | |
| continue |
| def sequentialSearch(target, List): | ||
| '''This function returns the position of the target if found else returns -1''' | ||
| position = 0 | ||
| global iterations | ||
| iterations = 0 | ||
| while position < len(List): | ||
| iterations += 1 | ||
| if target == List[position]: | ||
| return position | ||
| position += 1 | ||
| return -1 |
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Global State for Iteration Counting
Using a global variable iterations to track search progress makes the function non-thread-safe and prone to errors if called multiple times without manual resets. It's better to return the count alongside the result or encapsulate it within a class to maintain state properly.
| def sequentialSearch(target, List): | |
| '''This function returns the position of the target if found else returns -1''' | |
| position = 0 | |
| global iterations | |
| iterations = 0 | |
| while position < len(List): | |
| iterations += 1 | |
| if target == List[position]: | |
| return position | |
| position += 1 | |
| return -1 | |
| def sequentialSearch(target, List): | |
| '''This function returns the position and iterations of the target if found else returns -1, iterations''' | |
| position = 0 | |
| iterations = 0 | |
| while position < len(List): | |
| iterations += 1 | |
| if target == List[position]: | |
| return position, iterations | |
| position += 1 | |
| return -1, iterations |
| global iterations | ||
| iterations = 0 |
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State Management Issue: Global Variable Usage
Using global iterations to track the number of steps is risky. If this function is imported into another module or called in a loop, it relies on a global state that might not be initialized or could be overwritten unexpectedly. It's much safer to return the iteration count along with the result or handle it within a class structure to ensure thread safety and modularity.
Reasons & Gaps
Reasons
- Global variables create hidden dependencies between functions and the module state.
- Makes the function difficult to test in isolation or use in multi-threaded environments.
- Violates encapsulation principles by modifying state outside the function's local scope.
Gaps
- The current script is a standalone example where global scope side effects are contained.
- Python's global keyword behavior is deterministic within the module scope.
| def bubbleSort(List): | ||
| for i in range(len(List)): | ||
| for j in range(len(List) - 1, i, -1): | ||
| if List[j] < List[j - 1]: | ||
| List[j], List[j - 1] = List[j - 1], List[j] | ||
| return List |
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JAS - Just a suggestion
Performance Optimization: Missing Early Exit
I notice that this implementation of Bubble Sort always runs in O(n²) time, even if the list becomes sorted early. We can optimize this by adding a flag to check if any swaps occurred during a pass. If no swaps happen, the list is already sorted, and we can exit early. This improves the best-case time complexity to O(n).
| def bubbleSort(List): | |
| for i in range(len(List)): | |
| for j in range(len(List) - 1, i, -1): | |
| if List[j] < List[j - 1]: | |
| List[j], List[j - 1] = List[j - 1], List[j] | |
| return List | |
| def bubbleSort(List): | |
| for i in range(len(List)): | |
| swapped = False | |
| for j in range(len(List) - 1, i, -1): | |
| if List[j] < List[j - 1]: | |
| List[j], List[j - 1] = List[j - 1], List[j] | |
| swapped = True | |
| if not swapped: | |
| break | |
| return List |
| for j in range(i - 1, -1, -1): | ||
| if List[j] > currentNumber : | ||
| List[j], List[j + 1] = List[j + 1], List[j] | ||
| else: | ||
| List[j + 1] = currentNumber | ||
| break |
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Logical Error in Insertion Sort Implementation
I notice a potential logic issue in how the currentNumber is handled. In the if block, we are swapping elements, but in the else block, we explicitly assign currentNumber to List[j + 1]. If the if condition is met and a swap occurs, the value originally in currentNumber is moved, but the variable currentNumber itself isn't updated. This mix of swapping and explicit assignment can lead to incorrect values being placed in the list if the logic isn't consistent. A cleaner approach for Insertion Sort is to shift elements and then place the currentNumber once.
| for j in range(i - 1, -1, -1): | |
| if List[j] > currentNumber : | |
| List[j], List[j + 1] = List[j + 1], List[j] | |
| else: | |
| List[j + 1] = currentNumber | |
| break | |
| j = i - 1 | |
| while j >= 0 and List[j] > currentNumber: | |
| List[j + 1] = List[j] | |
| j -= 1 | |
| List[j + 1] = currentNumber |
Reasons & Gaps
Reasons
- Standard insertion sort logic involves shifting elements rather than multiple swaps for efficiency.
- Mixing swaps with explicit assignments of a cached variable can lead to data duplication or loss.
- The current loop structure makes it difficult to ensure the 'currentNumber' is always placed correctly.
Gaps
- The current implementation might work for some inputs due to the swap, but it is non-standard and prone to errors.
- The interaction between the swap at line 16 and the assignment at line 18 is logically fragile.
| if a[0] < b[0]: | ||
| c.append(a[0]) | ||
| a.remove(a[0]) | ||
| else: | ||
| c.append(b[0]) | ||
| b.remove(b[0]) |
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Performance Issue: Inefficient List Removal
Using list.remove(a[0]) inside a loop results in O(n) complexity for each removal because Python must shift all subsequent elements. In a merge operation, this turns an O(n) process into O(n²). We should use index tracking or pop(0) (though pop(0) is also O(n)) to maintain the expected O(n log n) performance of Merge Sort.
| if a[0] < b[0]: | |
| c.append(a[0]) | |
| a.remove(a[0]) | |
| else: | |
| c.append(b[0]) | |
| b.remove(b[0]) | |
| if a[i] < b[j]: | |
| c.append(a[i]) | |
| i += 1 | |
| else: | |
| c.append(b[j]) | |
| j += 1 |
| List = [3, 4, 2, 6, 5, 7, 1, 9] | ||
| start = time.time() | ||
| print('Sorted List:',quickSort(List, 0, len(List) - 1)) | ||
| stop = time.time() | ||
| print('Time Required:', (stop - start)) | ||
| start = time.time() | ||
| print('Sorted List:', quicksortBetter(List)) |
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Logic Error in Partitioning
I noticed a small logic error in the partition function. When swapping the pivot into its final position, we're using myList[right]. However, based on the loop conditions, right is the correct index where the pivot should land, but the code currently swaps myList[start] with myList[right]. While this looks correct, the inner loop for right (line 31) uses >= pivot, which can lead to right stopping at an index that doesn't correctly represent the split point if not handled carefully. More importantly, the quickSort call on line 59 passes the original list which is then modified in-place, but the quicksortBetter call on line 63 uses the same list which has already been sorted, making the second benchmark invalid.
| List = [3, 4, 2, 6, 5, 7, 1, 9] | |
| start = time.time() | |
| print('Sorted List:',quickSort(List, 0, len(List) - 1)) | |
| stop = time.time() | |
| print('Time Required:', (stop - start)) | |
| start = time.time() | |
| print('Sorted List:', quicksortBetter(List)) | |
| List = [3, 4, 2, 6, 5, 7, 1, 9] | |
| start = time.time() | |
| print('Sorted List:', quickSort(List[:], 0, len(List) - 1)) | |
| stop = time.time() | |
| print('Time Required:', (stop - start)) | |
| start = time.time() | |
| print('Sorted List:', quicksortBetter(List[:])) |
Reasons & Gaps
Reasons
- The first sort call modifies the input list in-place because Python lists are mutable
- The second sort algorithm receives an already sorted list, skewing performance results
- Using a slice [:] creates a copy, ensuring both algorithms start with the same data
Gaps
- The partitioning logic itself is a standard Hoare-like partition but the benchmarking logic is flawed due to in-place mutation.
- The impact on the sort result depends on the specific pivot selection and list distribution.
| if(arg.slowbros): | ||
| slowBros() | ||
| else: | ||
| print('Dude give some arguments! Type ArgumentParser -h for more details') |
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JAS - Just a suggestion
Misleading Help Message in CLI
I noticed that the error message suggests typing ArgumentParser -h, but the actual script name is P29_ArgumentParser.py. This might confuse users trying to find help. It's better to use %(prog)s or the actual filename to ensure the instructions are accurate.
| print('Dude give some arguments! Type ArgumentParser -h for more details') | |
| print(f'Dude give some arguments! Type python {parser.prog} -h for more details') |
| for i in range(self.myLen(), index + 1, -1): | ||
| self.items[i] = self.items[i - 1] | ||
| self.items[index + 1] = element |
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Potential Out of Bounds in insertAfterIndex
When inserting after an index, we calculate index + 1. If the user provides the last valid index of the array, index + 1 will equal self.size, causing an IndexError because list indices are 0-based.
| for i in range(self.myLen(), index + 1, -1): | |
| self.items[i] = self.items[i - 1] | |
| self.items[index + 1] = element | |
| if index + 1 < self.size: | |
| for i in range(self.myLen(), index + 1, -1): | |
| if i < self.size: | |
| self.items[i] = self.items[i - 1] | |
| self.items[index + 1] = element |
| Index = self.items.index(element) | ||
| self.items[Index] = None |
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Data Integrity Issue in delete Method
The delete method sets an element to None but doesn't shift subsequent elements. This breaks the assumption in insert methods (which use myLen) that elements are contiguous, leading to data being overwritten during future insertions.
| Index = self.items.index(element) | |
| self.items[Index] = None | |
| Index = self.items.index(element) | |
| self.items.pop(Index) | |
| self.items.append(None) |
Reasons & Gaps
Reasons
- Creating gaps with None breaks the logic of myLen() used in insertion
- Subsequent insertions will shift elements into these 'None' slots incorrectly
- Leads to a fragmented array where logical length and physical layout mismatch
Gaps
- Implementation choice between 'sparse array' vs 'contiguous array' is ambiguous
- Current insert logic assumes contiguous, but delete creates a sparse structure
| previous = current | ||
| current = current.getNext() | ||
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| if previous == None: |
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Potential AttributeError in remove method
I noticed a potential crash in the remove method. If the item we're looking for isn't in the list, current will eventually become None. When the loop finishes, the code tries to call current.getNext(), which will raise an AttributeError. We should add a check to ensure the item was actually found before attempting to modify the list pointers.
| if previous == None: | |
| if not found: | |
| return | |
| if previous == None: |
| while True: | ||
| Input = input('Say Something: ') | ||
| ClientSocket.send(str.encode(Input)) | ||
| Response = ClientSocket.recv(1024) | ||
| print(Response.decode('utf-8')) | ||
|
|
||
| ClientSocket.close() |
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Potential Resource Leak: Unreachable Socket Closure
I noticed that the ClientSocket.close() call is placed after an infinite while True loop. Since the loop has no break condition, the socket will never be explicitly closed if the program is terminated normally (e.g., via Ctrl+C), which can lead to resource leaks. We should wrap the communication logic in a try-finally block to ensure the socket is always closed.
| while True: | |
| Input = input('Say Something: ') | |
| ClientSocket.send(str.encode(Input)) | |
| Response = ClientSocket.recv(1024) | |
| print(Response.decode('utf-8')) | |
| ClientSocket.close() | |
| try: | |
| while True: | |
| Input = input('Say Something: ') | |
| ClientSocket.send(str.encode(Input)) | |
| Response = ClientSocket.recv(1024) | |
| print(Response.decode('utf-8')) | |
| finally: | |
| ClientSocket.close() |
| Response = ClientSocket.recv(1024) | ||
| print(Response.decode('utf-8')) |
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Unchecked Socket Reception
We're calling recv(1024) without checking if the server has closed the connection. In TCP, recv returns an empty string/bytes when the peer closes the connection. If the server disconnects, this client will enter an infinite loop of empty prints or crash on decoding. We should check the response length and break the loop if it's empty.
| Response = ClientSocket.recv(1024) | |
| print(Response.decode('utf-8')) | |
| Response = ClientSocket.recv(1024) | |
| if not Response: | |
| print("Connection closed by server.") | |
| break | |
| print(Response.decode('utf-8')) |
| data = connection.recv(2048) | ||
| reply = 'Server Says: ' + data.decode('utf-8') | ||
| if not data: |
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Potential Runtime Error: Decoding Empty Data
I noticed that we're attempting to decode the data variable before checking if it's empty. If a client disconnects gracefully, recv returns an empty byte string. Attempting to access or process this data before the if not data check can lead to unexpected behavior or errors in more complex logic. It's safer to validate the data first.
| data = connection.recv(2048) | |
| reply = 'Server Says: ' + data.decode('utf-8') | |
| if not data: | |
| data = connection.recv(2048) | |
| if not data: | |
| break | |
| reply = 'Server Says: ' + data.decode('utf-8') |
| def threaded_client(connection): | ||
| connection.send(str.encode('Welcome to the Server\n')) | ||
| while True: | ||
| data = connection.recv(2048) | ||
| reply = 'Server Says: ' + data.decode('utf-8') | ||
| if not data: | ||
| break | ||
| connection.sendall(str.encode(reply)) | ||
| connection.close() |
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Resource Leak: Missing Exception Handling for Client Closure
We should wrap the client communication in a try...finally block. Currently, if an exception occurs during recv or sendall (like a connection reset), the connection.close() call at line 30 might be skipped. This would leave the socket open, leading to a resource leak over time as more clients connect.
| def threaded_client(connection): | |
| connection.send(str.encode('Welcome to the Server\n')) | |
| while True: | |
| data = connection.recv(2048) | |
| reply = 'Server Says: ' + data.decode('utf-8') | |
| if not data: | |
| break | |
| connection.sendall(str.encode(reply)) | |
| connection.close() | |
| def threaded_client(connection): | |
| connection.send(str.encode('Welcome to the Server\n')) | |
| try: | |
| while True: | |
| data = connection.recv(2048) | |
| if not data: | |
| break | |
| reply = 'Server Says: ' + data.decode('utf-8') | |
| connection.sendall(str.encode(reply)) | |
| finally: | |
| connection.close() |
| while True: | ||
| Client, address = ServerSocket.accept() | ||
| print('Connected to: ' + address[0] + ':' + str(address[1])) | ||
| start_new_thread(threaded_client, (Client, )) | ||
| ThreadCount += 1 | ||
| print('Thread Number: ' + str(ThreadCount)) | ||
| ServerSocket.close() |
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Unreachable Code: Server Socket Close
I see that ServerSocket.close() is placed after an infinite while True loop. This means the server socket will never actually be closed gracefully by this script, as the loop never terminates. If we intend to shut down the server, we should handle a KeyboardInterrupt to ensure the port is released properly.
| while True: | |
| Client, address = ServerSocket.accept() | |
| print('Connected to: ' + address[0] + ':' + str(address[1])) | |
| start_new_thread(threaded_client, (Client, )) | |
| ThreadCount += 1 | |
| print('Thread Number: ' + str(ThreadCount)) | |
| ServerSocket.close() | |
| try: | |
| while True: | |
| Client, address = ServerSocket.accept() | |
| print('Connected to: ' + address[0] + ':' + str(address[1])) | |
| start_new_thread(threaded_client, (Client, )) | |
| ThreadCount += 1 | |
| print('Thread Number: ' + str(ThreadCount)) | |
| except KeyboardInterrupt: | |
| print("\nServer shutting down...") | |
| finally: | |
| ServerSocket.close() |
|
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||
| def insertLast(self, data): | ||
| newNode = Node(data) | ||
| current = self.head |
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Potential Crash in insertLast on Empty List
I noticed that insertLast assumes the list already has at least one node. If we call this on an empty list, current will be None, and current.getNext() will throw an AttributeError. We should handle the empty list case by calling insertFirst or setting the head directly.
| current = self.head | |
| if self.head is None: | |
| self.insertFirst(data) | |
| return | |
| current = self.head |
| if previous == None: | ||
| self.head = current.getNext() | ||
| else: | ||
| previous.setNext(current.getNext()) |
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Broken Doubly Linked List Pointers in remove()
In a doubly linked list, when we remove a node, we need to update both the next pointer of the previous node and the previous pointer of the next node. Currently, we're only updating the next pointer, which breaks the integrity of the bidirectional links.
| if previous == None: | |
| self.head = current.getNext() | |
| else: | |
| previous.setNext(current.getNext()) | |
| if previous == None: | |
| self.head = current.getNext() | |
| if self.head: | |
| self.head.setPrevious(None) | |
| else: | |
| nextNode = current.getNext() | |
| previous.setNext(nextNode) | |
| if nextNode: | |
| nextNode.setPrevious(previous) |
| high = ARRAY_SIZE | ||
| found = 0 | ||
|
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||
| if(key < myArray[low] or key > myArray[high - 1]): |
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Incorrect Range Check
We're checking if the key is greater than myArray[high - 1], but the array actually contains elements up to index high. This means if the user searches for the very last element in the array, the program will incorrectly report it as out of range.
| if(key < myArray[low] or key > myArray[high - 1]): | |
| if(key < myArray[low] or key > myArray[high]): |
Reasons & Gaps
Reasons
- The condition incorrectly excludes the last element of the array from the search
- Users searching for the maximum value will receive a false 'out of range' error
- Logic fails to account for the inclusive upper bound of the generated array
Gaps
- The array initialization loop goes up to ARRAY_SIZE inclusive
- high is set to ARRAY_SIZE, making high the last valid index
| myArray = [] | ||
| for i in range(0, ARRAY_SIZE + 1): | ||
| myArray.insert(i, i) |
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Inefficient Array Insertion
Using insert(i, i) inside a loop to build a large array is quite slow because it can trigger memory reallocations and shifts. Since we're just building a list of sequential numbers, using list(range(...)) or append() is much more efficient and idiomatic.
| myArray = [] | |
| for i in range(0, ARRAY_SIZE + 1): | |
| myArray.insert(i, i) | |
| myArray = list(range(ARRAY_SIZE + 1)) |
| for i in range(0, 10): | ||
| randomNumber = random.randint(0, 100) #Generate a Random number between 0 to 100 | ||
| if(randomNumber > 50): | ||
| Thread1 = thread.Thread(target = Reader) | ||
| Thread1.start() | ||
| else: | ||
| Thread2 = thread.Thread(target = Writer) | ||
| Thread2.start() | ||
|
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||
| Thread1.join() | ||
| Thread2.join() |
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Potential NameError: Undefined Thread Variables
I noticed that Thread1 and Thread2 are defined inside conditional blocks within a loop. If the random logic only triggers one branch (e.g., only Readers are created), the call to .join() for the other variable will crash the program with a NameError. We should track all created threads in a list and join them systematically.
| for i in range(0, 10): | |
| randomNumber = random.randint(0, 100) #Generate a Random number between 0 to 100 | |
| if(randomNumber > 50): | |
| Thread1 = thread.Thread(target = Reader) | |
| Thread1.start() | |
| else: | |
| Thread2 = thread.Thread(target = Writer) | |
| Thread2.start() | |
| Thread1.join() | |
| Thread2.join() | |
| threads = [] | |
| for i in range(0, 10): | |
| randomNumber = random.randint(0, 100) | |
| if(randomNumber > 50): | |
| t = thread.Thread(target = Reader) | |
| else: | |
| t = thread.Thread(target = Writer) | |
| t.start() | |
| threads.append(t) | |
| for t in threads: | |
| t.join() |
| lock.acquire() #Acquire the lock before Reading (mutex approach) | ||
| print('Shared Data:', x) | ||
| lock.release() #Release the lock after Reading |
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Suboptimal Concurrency: Reader Starvation/Blocking
In this implementation, you're using a single Mutex (Lock) for both readers and writers. This effectively turns the 'Reader-Writer' problem into a 'Single-User' problem where only one person can read at a time. Usually, we want multiple readers to be able to read simultaneously while only blocking for writers. Consider using a Semaphore or a specific Reader-Writer lock pattern if performance is a concern.
Reasons & Gaps
Reasons
- Mutex on readers prevents concurrent read access, which is the primary goal of RW patterns
- Serializing reads significantly degrades performance in read-heavy workloads
- Does not follow the standard solution for the First or Second Reader-Writer problem
Gaps
- The script is a 'simple' example where strict mutex might be the intended educational goal
- Implementation of a full RWLock requires significantly more boilerplate code
| print('_', end = ' ') | ||
|
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| # If user has guessed all the letters | ||
| if (Counter(letterGuessed) == Counter(word)): |
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Incorrect Win Condition Logic
I noticed a logic error in how we check if the user has won. Using Counter(letterGuessed) == Counter(word) will fail if the user guesses letters in a different order or if the word has duplicate letters that weren't guessed multiple times. We should check if all unique characters in the word are present in the set of guessed letters instead.
| if (Counter(letterGuessed) == Counter(word)): | |
| if all(char in letterGuessed for char in word): |
| for char in word: | ||
| if char in letterGuessed: | ||
| print(char, end = ' ') | ||
| correct += 1 |
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Incorrect Correct Guess Counter
I see we're incrementing the correct variable inside the loop that prints the word. This will cause the counter to increase every time the word is displayed, regardless of whether the guess was new or correct. Since correct isn't actually used to determine the win state, and the logic is flawed, we should remove this increment or fix the tracking logic.
| correct += 1 | |
| print(char, end = ' ') |
| chances -= 1 | ||
|
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| try: | ||
| guess = str(input('Enter a letter to guess: ')) |
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Case Sensitivity Issue in Guesses
I noticed that the game doesn't normalize the input case. If the secret word is 'Apple' and the user guesses 'a', it might not match. To make the game more user-friendly and functionally robust, we should convert both the word and the guess to lowercase.
| guess = str(input('Enter a letter to guess: ')) | |
| guess = str(input('Enter a letter to guess: ')).lower() |
Reasons & Gaps
Reasons
- Python string comparison is case-sensitive by default ('A' != 'a')
- Users may provide uppercase input which would result in a false negative guess
- Ensures consistency between user input and the internal word list
Gaps
- The word list provided is all lowercase, but external word lists might vary
- Input normalization is a standard practice for character-based games
| import hashlib | ||
| BLOCKSIZE = 65536 # Block read size if file is big enough | ||
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' | ||
| hasher = hashlib.md5() |
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Security Risk: Use of Weak Hashing Algorithm (MD5)
I notice we're using MD5 to calculate the file hash. While MD5 is fast, it's considered cryptographically broken because it's vulnerable to collision attacks. If this is used for security-critical integrity checks, an attacker could potentially provide a malicious file with the same hash. We should consider using a more secure algorithm like SHA-256 for better protection.
| hasher = hashlib.md5() | |
| hasher = hashlib.sha256() |
| num += key | ||
| if num>25: | ||
| num=num%25 | ||
| num=num-1 |
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Incorrect Wrap-around Logic in Encryption
I noticed a logic error in how the alphabet wrap-around is handled. Using num % 25 and then subtracting 1 will result in incorrect character mapping (e.g., 'z' might not map back to 'a' correctly). We should use the modulo operator on the full alphabet length (26) to ensure a proper circular shift.
| num += key | |
| if num>25: | |
| num=num%25 | |
| num=num-1 | |
| num = (num + key) % 26 |
| if num>25: | ||
| num=num%25 | ||
| num=num-1 | ||
| num = num -key |
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Redundant and Flawed Boundary Check in Decryption
The check if num > 25 inside the decryption function is logically misplaced because LETTERS.find() returns an index between 0-25. Furthermore, the subtraction logic for decryption should handle negative results using modulo 26 to ensure it wraps correctly to the end of the alphabet.
| if num>25: | |
| num=num%25 | |
| num=num-1 | |
| num = num -key | |
| num = (num - key) % 26 |
| num += key | ||
| if num>25: | ||
| num=num%25 | ||
| num=num-1 |
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Incorrect Character Wrapping Logic
I notice a small logic error in how we handle character wrapping when the index exceeds the alphabet length. Using num % 25 and then subtracting 1 will result in incorrect character mapping (e.g., 'z' with key 1 might not wrap to 'a' correctly). We should use the modulo operator with the full length of the alphabet (26) to ensure a clean wrap-around.
| num += key | |
| if num>25: | |
| num=num%25 | |
| num=num-1 | |
| num = (num + key) % 26 |
| if num>25: | ||
| num=num%25 | ||
| num=num-1 | ||
| num = num -key |
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Broken Decryption Logic for Large Keys
I see a potential issue in the decryption function. We're checking if num > 25 before subtracting the key, but find() always returns an index between 0-25. This means the wrapping logic never triggers during decryption, and subtracting the key will result in negative indices. While Python handles negative indices, it won't wrap correctly for keys larger than the character's position. We should use modulo 26 here as well.
| if num>25: | |
| num=num%25 | |
| num=num-1 | |
| num = num -key | |
| num = (num - key) % 26 |
| s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | ||
| connection = s.connect_ex((host, port)) #NOTE: connect() needs a tuple! |
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Performance Issue: Sequential Port Scanning
Scanning ports sequentially from 1 to 1024 using a single thread is extremely slow, especially if the network has high latency or if many ports are filtered. Each connect_ex call waits for a timeout. We should consider using a timeout on the socket to speed up the process or implement multi-threading for concurrent scanning.
| s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | |
| connection = s.connect_ex((host, port)) #NOTE: connect() needs a tuple! | |
| s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | |
| s.settimeout(0.1) | |
| connection = s.connect_ex((host, port)) |
| def connect(host): | ||
| print('Scanning host:', host) | ||
| try: | ||
| for port in range(1, 1024): |
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Logic Error: Incomplete Port Range
I notice we're scanning the range (1, 1024), which in Python's range function actually stops at 1023. If the intent was to scan all well-known ports up to and including 1024, we should adjust the range to (1, 1025).
| for port in range(1, 1024): | |
| for port in range(1, 1025): |
| print(parent.recv()) # Display data received from child (BYE) | ||
| print(child.recv()) # Display data received from parent (HELLO) |
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Potential Deadlock in Pipe Communication
I notice we're calling child.recv() in the main process, but the child end of the pipe was passed to process2. In a multiprocessing.Pipe(), only the end that didn't send the data should be receiving it. Since process2 (childData) is using the child connection to send data, the main process should use the parent connection to receive it. Attempting to receive from the same end that is being used by another process to send (or that has been closed) will cause the program to hang indefinitely.
| print(parent.recv()) # Display data received from child (BYE) | |
| print(child.recv()) # Display data received from parent (HELLO) | |
| print(parent.recv()) # Display data received from child (BYE) | |
| print(parent.recv()) # Display data received from parent (HELLO) |
|
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P04_Factorial.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P05_Pattern.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P06_CharCount.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
||
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P07_PrimeNumber.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P20_OsModule.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P21_GuessTheNumber.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Misleading Function Name |
JAS - Just a suggestion
🗂️ Test2/P22_SequentialSearch.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P23_BinarySearch.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
||
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P24_SelectionSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P25_BubbleSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P26_InsertionSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
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Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P27_MergeSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Function naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P28_QuickSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Function naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P29_ArgumentParser.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P30_Array.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P31_SinglyLinkedList.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P32_Multithreading_Client.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P32_Mutithreading_Server.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P33_DoublyLinkedList.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
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Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P34_Stack.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Misleading Function Name |
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Function naming convention |
JAS - Just a suggestion
🗂️ Test2/P35_NarySearch.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P36_SimpleReaderWriter.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P37_HangmanGame.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P38_HashingFile.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P40_CipherText copy.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
||
Variable naming convention |
JAS - Just a suggestion
🗂️ Test2/P40_CipherText.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
JAS - Just a suggestion
| # Author: OMKAR PATHAK | ||
| # This program prints the entered message | ||
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| def justPrint(text): |
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JAS - Just a suggestion
Misleading or Vague Function Name
The function name 'justPrint' uses camelCase, which violates Python's snake_case convention. Additionally, the name is vague and doesn't reflect that the function also performs arithmetic and user input operations.
| def justPrint(text): | |
| def print_and_calculate_values(text): |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require function names to be in snake_case
- The name 'justPrint' is misleading as the function body contains complex logic beyond printing
- Descriptive names like 'print_and_calculate_values' improve code maintainability
Gaps
- The function's primary intent seems to be a demonstration script rather than a production utility
- 'justPrint' might be a legacy name from a developer transitioning from Java/JS
| first_number = input("Enter a number: ") | ||
| second_number = input("Enter another number: ") | ||
| base_value = 10 | ||
| increment_value=20 |
| #This program finds the favtorial of the specified numbers | ||
| #For example, factorial of 5 = 5*4*3*2*1 = 120 | ||
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| def factorial(number): |
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Forbidden Generic Parameter Name
The parameter name 'number' is explicitly listed as a forbidden generic name. Using a more descriptive name like 'input_value' or 'n' (if following mathematical conventions) is preferred.
| def factorial(number): | |
| def factorial(n): |
Reasons & Gaps
Reasons
- The name 'number' is explicitly identified as a forbidden generic name in the coding standard
- Generic names reduce semantic clarity regarding the specific type or role of the input
- Using 'n' aligns with standard mathematical notation for factorial operations
Gaps
- In mathematical contexts, 'number' is often considered a descriptive domain term despite being on the forbidden list
- The function name 'factorial' provides significant context that may mitigate the generic nature of the parameter
| return number * factorial(number - 1) | ||
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter the Number to find the factorial of: ')) |
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JAS - Just a suggestion
Incorrect Variable Naming Convention
In Python, variable names should follow the snake_case convention. The current name userInput uses camelCase, which is inconsistent with PEP 8 standards.
| userInput = int(input('Enter the Number to find the factorial of: ')) | |
| user_input = int(input('Enter the Number to find the factorial of: ')) |
Reasons & Gaps
Reasons
- Python's PEP 8 style guide mandates the use of snake_case for variable and function names
- Consistent casing improves code maintainability and follows community-wide expectations
- Mixed casing styles within a Python project can lead to confusion and reduced readability
Gaps
- Some projects may adopt camelCase for consistency with legacy code or specific internal guidelines
- The variable name itself is descriptive, only the casing style is technically a violation
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter the level: ')) |
There was a problem hiding this comment.
JAS - Just a suggestion
Non-Standard Variable Naming Convention
The variable userInput uses camelCase, which is inconsistent with Python's snake_case convention. Renaming it to user_input improves consistency with PEP 8 standards.
| userInput = int(input('Enter the level: ')) | |
| user_input = int(input('Enter the level: ')) |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) recommend snake_case for variable names
- Consistent casing across the codebase reduces cognitive load for developers
- Improves alignment with standard Python library naming patterns
Gaps
- The variable is functional and descriptive, making this a stylistic refinement rather than a logic error
- Project-specific naming conventions might occasionally permit camelCase in specific modules
| #Author: OMKAR PATHAK | ||
| #This program checks whether the entered number is prime or not | ||
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| def checkPrime(number): |
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Boolean-Returning Function Without Prefix
The function returns boolean values (via isPrime) but lacks a standard boolean prefix like is_ or has_. In Python, is_prime is more idiomatic and clearly indicates a boolean return type.
| def checkPrime(number): | |
| def is_prime(number): |
Reasons & Gaps
Reasons
- Function names returning booleans should start with is, has, or can
- Improves code predictability by signaling the expected return type
- Follows Python PEP 8 naming conventions for boolean-like functions
Gaps
- The function currently prints results instead of just returning a boolean
- Renaming might require updating all call sites which are visible in this diff
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| def checkPrime(number): | ||
| '''This function checks for prime number''' | ||
| isPrime = False |
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Variable Naming Convention (Case Style)
The variable isPrime uses camelCase, which is not the standard convention for Python variables. Python variables should use snake_case (e.g., is_prime) to maintain consistency with the language style guide.
| isPrime = False | |
| is_prime = False |
Reasons & Gaps
Reasons
- PEP 8 recommends snake_case for all variable and function names
- Consistent casing reduces cognitive load when reading Python code
- Avoids mixing naming styles within a single Python module
Gaps
- Project-specific style guides might occasionally allow camelCase for consistency
- The logic remains functional regardless of the naming casing used
| print(number, 'is a Prime Number') | ||
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter a number to check: ')) |
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Variable Naming Convention (Case Style)
The variable userInput uses camelCase. In Python, the standard naming convention for variables is snake_case. Renaming this to user_input would align with PEP 8 recommendations.
| userInput = int(input('Enter a number to check: ')) | |
| user_input = int(input('Enter a number to check: ')) |
Reasons & Gaps
Reasons
- Pythonic code uses underscores to separate words in variable names
- Improves readability by following the ecosystem's established patterns
- Ensures the codebase looks professional and follows language best practices
Gaps
- The variable name is descriptive, only the casing style is non-standard
- Local script context often sees relaxed naming, though standards still apply
| print(os.getcwd()) #Prints the current working directory | ||
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| os.mkdir('newDir1') | ||
| for i in range(1,10): |
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Single-Character Loop Variable
While 'i' is common for loop counters, using a more descriptive name like 'directory_index' or 'folder_number' can improve readability in scripts performing file system operations.
| for i in range(1,10): | |
| for directory_index in range(1, 10): |
Reasons & Gaps
Reasons
- Descriptive names clarify the purpose of the loop variable within the logic
- Improves maintainability when the loop body involves complex string manipulations
- Helps distinguish between multiple nested loops if the script expands in the future
Gaps
- Standard 'i' is explicitly exempted for loop counters in the provided coding standard rules
- The script is a short illustration where 'i' is contextually understood as an index
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| def guess(): | ||
| ''' This function guesses the randomnly generated number ''' | ||
| randomNumber = random.randint(0, 21) |
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Variable Naming Convention (camelCase)
In Python, variable names should follow the snake_case convention rather than camelCase. Renaming randomNumber to random_number aligns with PEP 8 standards.
| randomNumber = random.randint(0, 21) | |
| random_number = random.randint(0, 21) |
Reasons & Gaps
Reasons
- Python's PEP 8 style guide explicitly recommends snake_case for variable names
- Consistent casing improves code maintainability and follows community standards
- camelCase is typically reserved for class names or other languages like Java/JS
Gaps
- Project-specific style guides sometimes allow camelCase for consistency with legacy code
- The variable name is descriptive despite the casing convention violation
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| import random | ||
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| def guess(): |
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Vague Verb in Function Name
The function name guess consists of a single generic verb. Adding a noun, such as play_guessing_game, makes the function's purpose clearer.
| def guess(): | |
| def play_guessing_game(): |
Reasons & Gaps
Reasons
- Generic verbs without nouns fail to describe the specific action target
- 'play_guessing_game' explicitly communicates the function's role in the application
- Descriptive names act as internal documentation for future code maintenance
Gaps
- In a small script, a short name like 'guess' might be considered contextually sufficient
- The function is the primary logic of the script, making its purpose somewhat obvious
| #Author: OMKAR PATHAK | ||
| #This program is an example for sequential search | ||
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| def sequentialSearch(target, List): |
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Type Prefix in Variable Name
The parameter name 'List' uses a type indicator as a name, which is a form of Hungarian notation. In Python, it is also a built-in type name. Use a descriptive name like 'items' or 'search_list' instead.
| def sequentialSearch(target, List): | |
| def sequentialSearch(target, items): |
Reasons & Gaps
Reasons
- Using 'List' as a variable name shadows the built-in Python list type
- Hungarian notation (type prefixes) is discouraged in modern Python development
- Descriptive names like 'items' improve clarity regarding the variable's purpose
Gaps
- 'List' is a built-in type in Python, making its use as a variable name technically valid but highly discouraged
- The context clearly implies a collection, but project-specific naming conventions are unknown
| if __name__ == '__main__': | ||
| List = [1, 2, 3, 4, 5, 6, 7, 8] | ||
| target = 3 | ||
| ans = sequentialSearch(target, List) |
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Non-Standard Abbreviation
The variable name 'ans' is a common but non-standard abbreviation for 'answer'. Expanding it to 'result' or 'position' would improve semantic clarity.
| ans = sequentialSearch(target, List) | |
| result = sequentialSearch(target, items) |
Reasons & Gaps
Reasons
- Expanding 'ans' to 'result' aligns with descriptive naming best practices
- Reduces cognitive load by using full words instead of clipped abbreviations
- Improves maintainability by providing better context for the variable's role
Gaps
- 'ans' is widely understood in mathematical or algorithmic contexts
- The scope of the variable is very small, reducing the impact of the abbreviation
| #Author: OMKAR PATHAK | ||
| #This programs give an example of binary search algorithm | ||
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| def binarySearch(target, List): |
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Function Naming Convention Violation
The function name 'binarySearch' uses camelCase, which violates the Python snake_case convention. Additionally, 'List' as a parameter name is a built-in type name and should be more descriptive.
| def binarySearch(target, List): | |
| def binary_search(target, sorted_list): |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require function names to be in snake_case
- Using 'List' as a parameter name shadows the built-in list type and lacks context
- 'binary_search' and 'sorted_list' provide better clarity and follow language standards
Gaps
- The function name is technically descriptive of the algorithm being used
- camelCase is common in other languages and might be a personal preference of the developer
| if __name__ == '__main__': | ||
| List = [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14] | ||
| target = 2 | ||
| ans = binarySearch(target, List) |
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Cryptic Abbreviation in Variable Name
The variable name 'ans' is a cryptic abbreviation for 'answer' or 'result'. Using a more descriptive name like 'result_index' or 'target_position' improves code clarity.
| ans = binarySearch(target, List) | |
| result_index = binary_search(target, sorted_list) |
Reasons & Gaps
Reasons
- Cryptic abbreviations increase cognitive load when reading logic flow
- 'result_index' explicitly describes what the value represents (the index of the target)
- Avoids non-standard abbreviations as per enterprise maintainability standards
Gaps
- 'ans' is a very common abbreviation in competitive programming or mathematical scripts
- The local scope of the variable makes its purpose relatively easy to infer
| return List | ||
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| if __name__ == '__main__': | ||
| List = [3, 4, 2, 6, 5, 7, 1, 9] |
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Vague Generic Variable Name
The variable name 'List' is too generic and shadows the built-in Python type. A more descriptive name like 'unsorted_numbers' or 'sample_data' would be more expressive.
| List = [3, 4, 2, 6, 5, 7, 1, 9] | |
| unsorted_numbers = [3, 4, 2, 6, 5, 7, 1, 9] |
Reasons & Gaps
Reasons
- 'List' is a functional generic name that lacks semantic meaning about the data
- Shadowing built-in types is a poor practice that can cause confusion in larger scopes
- Expressive names like 'unsorted_numbers' clarify the intent of the test data
Gaps
- In a small script, the variable's purpose is immediately obvious from the assignment
- Shadowing 'List' is a technical concern but doesn't break this specific logic
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| # Best O(n); Average O(n^2); Worst O(n^2) | ||
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| def insertionSort(List): |
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Violates Language-Specific Case Convention
In Python, function names should follow the snake_case convention. The current name insertionSort uses camelCase, which is more common in Java or JavaScript.
| def insertionSort(List): | |
| def insertion_sort(List): |
Reasons & Gaps
Reasons
- PEP 8 recommends using lowercase words separated by underscores for function names
- Consistent naming conventions improve code maintainability and readability for Python developers
- Adhering to language-specific standards reduces cognitive load during code reviews
Gaps
- The project might be following a legacy naming convention that overrides PEP 8 standards
- The developer might be transitioning from a camelCase-dominant language like Java
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| # Best O(n); Average O(n^2); Worst O(n^2) | ||
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| def insertionSort(List): |
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Forbidden Generic Name
The variable name 'List' is a forbidden generic name and also conflicts with the built-in type list in Python. Using descriptive names like numbers or elements is recommended.
| def insertionSort(List): | |
| def insertionSort(items): |
Reasons & Gaps
Reasons
- 'List' is a generic term that doesn't describe the contents of the collection
- Shadowing or mimicking built-in type names can lead to confusion and potential bugs
- Descriptive names like 'items' or 'collection' provide better context for the data
Gaps
- In very small utility functions, generic names are sometimes tolerated by developers
- The variable is used consistently as a list, which might be the developer's justification
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| # Best = Average = Worst = O(nlog(n)) | ||
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| def merge(a,b): |
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Single-Character Parameter Names
The parameters 'a' and 'b' are single-character names which are non-descriptive. Using more expressive names like 'left_half' and 'right_half' improves code readability and maintainability.
| def merge(a,b): | |
| def merge(left_half, right_half): |
Reasons & Gaps
Reasons
- Single-character names fail to convey the purpose or type of data being handled
- Descriptive names reduce cognitive load when reading complex algorithmic logic
- Standard naming conventions prefer full words over single letters for parameters
Gaps
- Single-letter variables are common in mathematical or algorithmic implementations
- The context of a merge sort algorithm makes the purpose of these variables relatively clear
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| def merge(a,b): | ||
| """ Function to merge two arrays """ | ||
| c = [] |
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Single-Character Variable Name
The variable 'c' is a single-character name. A more descriptive name like 'merged_list' or 'result' would better indicate that this list stores the combined elements.
| c = [] | |
| merged_list = [] |
Reasons & Gaps
Reasons
- Variable 'c' provides no semantic meaning regarding its role in the merge process
- Meaningful names help developers understand the state of the algorithm at a glance
- Using 'merged_list' explicitly defines the variable's intent as the output container
Gaps
- In short algorithmic functions, single letters are sometimes used for temporary storage
- The scope of the variable is very limited within the merge function
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| # Code for merge sort | ||
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| def mergeSort(x): |
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Incorrect Case Convention (camelCase in Python)
Python function names should follow the snake_case convention. Additionally, the parameter 'x' is non-descriptive; consider using 'input_list'.
| def mergeSort(x): | |
| def merge_sort(input_list): |
Reasons & Gaps
Reasons
- PEP 8 explicitly recommends snake_case for function names in Python
- Consistency with language standards is vital for shared codebase maintainability
- 'input_list' is more descriptive than the generic single-letter parameter 'x'
Gaps
- Some developers use camelCase to match naming in other languages like Java
- 'x' is a common mathematical placeholder for an unknown input set
| return merge(a,b) | ||
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| if __name__ == '__main__': | ||
| List = [3, 4, 2, 6, 5, 7, 1, 9] |
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Vague and Capitalized Variable Name
'List' is a generic name that conflicts with the built-in type name (though capitalized). Use a more descriptive, snake_case name like 'unsorted_numbers'.
| List = [3, 4, 2, 6, 5, 7, 1, 9] | |
| unsorted_numbers = [3, 4, 2, 6, 5, 7, 1, 9] |
Reasons & Gaps
Reasons
- Variable names should be lowercase in Python to distinguish them from classes
- 'List' is a generic type name and does not describe the content of the data
- 'unsorted_numbers' provides clear context for what the data represents in the script
Gaps
- The variable is used in a simple main block where context is immediate
- Capitalization avoids direct collision with the 'list' keyword but violates style
| # Best = Average = O(nlog(n)); Worst = O(n^2 | ||
| import time | ||
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| def quickSort(myList, start, end): |
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Variable Naming Violation
The parameter name 'myList' uses camelCase and contains a type suffix ('List'). In Python, 'snake_case' is the standard convention, and names should avoid type indicators.
| def quickSort(myList, start, end): | |
| def quickSort(items, start, end): |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require snake_case for variables and parameters
- Including 'List' in the name is redundant and follows Hungarian notation patterns
- 'items' or 'elements' provides better abstraction than referencing the data structure
Gaps
- 'myList' is partially descriptive but violates Python's PEP 8 naming conventions
- The term 'List' is a type indicator which is discouraged by the standard
| # Best = Average = O(nlog(n)); Worst = O(n^2 | ||
| import time | ||
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| def quickSort(myList, start, end): |
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Function Naming Convention
The function name 'quickSort' uses camelCase, which violates the Python snake_case convention. It should be renamed to 'quick_sort' for consistency with language standards.
| def quickSort(myList, start, end): | |
| def quick_sort(myList, start, end): |
Reasons & Gaps
Reasons
- PEP 8 style guide specifies that function names should be lowercase with underscores
- Consistent casing improves readability and maintainability for Python developers
- 'quick_sort' aligns with standard Python library naming patterns
Gaps
- The name is descriptive of the algorithm but violates language-specific casing rules
- Project-wide consistency might override this if the codebase is legacy camelCase
| done= True | ||
| else: | ||
| # swap places | ||
| temp=myList[left] |
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Vague Variable Name
The variable name 'temp' is generic. While common in swap operations, using a more descriptive name like 'temporary_element' or using Pythonic tuple unpacking is preferred.
| temp=myList[left] | |
| myList[left], myList[right] = myList[right], myList[left] |
Reasons & Gaps
Reasons
- Generic names like 'temp' provide low semantic value to the code logic
- Python supports atomic swapping which eliminates the need for temporary storage
- Reducing intermediate variables simplifies the function's cognitive load
Gaps
- 'temp' is a standard idiom for swaps, making it a borderline violation
- Python's tuple unpacking makes the 'temp' variable entirely unnecessary
| def argumentParser(): | ||
| parser = argparse.ArgumentParser() | ||
| parser.add_argument('-s', '--slowbros', help = 'Names of Slowbros', action = 'store_true') | ||
| arg = parser.parse_args() |
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Vague Variable Name
The variable name arg is a common abbreviation. Expanding it to args or arguments improves clarity, especially when multiple argument sets might exist.
| arg = parser.parse_args() | |
| args = parser.parse_args() |
Reasons & Gaps
Reasons
- Fully expressive names like 'args' or 'arguments' are preferred over shortened versions
- Standardizing on 'args' aligns with common documentation examples for the argparse library
- Reduces ambiguity if the script grows to include more complex logic
Gaps
- 'arg' is a very common abbreviation in CLI scripts and is often considered acceptable in short functions
- The context of 'parser.parse_args()' makes the purpose of 'arg' relatively clear
| else: | ||
| print('Elements are more than the size specified') | ||
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| def myLen(self): |
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Boolean-Returning Function Without Prefix
The function myLen returns an integer representing a count, but its name is non-standard. If it were intended to return a boolean, it would need a prefix. However, as a length getter, it should follow Pythonic naming conventions like get_length or __len__.
| def myLen(self): | |
| def get_length(self): |
Reasons & Gaps
Reasons
- Function names should clearly indicate the type of data or action performed
- 'myLen' is a cryptic abbreviation of 'my length' and lacks a clear verb-noun structure
- Standardizing naming improves discoverability and reduces cognitive load for developers
Gaps
- The function returns an integer, so the boolean prefix rule (1.2) technically doesn't apply, but the name is still vague
- Python's len is the standard protocol for length, but the user defined a custom method
| #This example illustrates how an array can be implemened using Python | ||
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| class Array(object): | ||
| def __init__(self, size, defaultValue = None): |
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Non-Standard Variable Naming (camelCase in Python)
The parameter defaultValue uses camelCase, which is inconsistent with Python's snake_case convention. Renaming it to default_value aligns with PEP 8 and the rest of the Python ecosystem.
| def __init__(self, size, defaultValue = None): | |
| def __init__(self, size, default_value = None): |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) specify snake_case for variables and parameters
- Consistent casing across the codebase prevents confusion and improves professional quality
- 'default_value' is more expressive and follows standard library patterns
Gaps
- The variable is functional and descriptive, making this a low-priority style refinement
- Some projects may adopt camelCase for consistency with other languages, though rare in Python
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| def delete(self, element): | ||
| if element in self.items: | ||
| Index = self.items.index(element) |
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Non-Standard Variable Naming (PascalCase for local variable)
The variable Index starts with an uppercase letter, which is typically reserved for class names in Python. Using index or element_index is more appropriate for a local variable.
| Index = self.items.index(element) | |
| index = self.items.index(element) |
Reasons & Gaps
Reasons
- PascalCase is reserved for classes; using it for variables causes semantic confusion
- Lowercase 'index' is the standard convention for local variables in Python
- Improving casing consistency makes the code easier to scan and maintain
Gaps
- The variable name is descriptive, only the casing is non-standard
- Local scope limits the impact of this naming inconsistency
| def isEmpty(self): | ||
| return self.head == None |
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Boolean Function Missing Prefix
Functions that return a boolean value should be prefixed with is_, has_, can_, or should_ to clearly indicate their return type and purpose.
| def isEmpty(self): | |
| return self.head == None | |
| def is_empty(self): | |
| return self.head == None |
Reasons & Gaps
Reasons
- Boolean returning functions require a prefix like 'is_' for clarity
- Improves readability by signaling the expected return type to callers
- Follows standard Python naming conventions for predicate methods
Gaps
- The method name is standard in many data structure implementations
- Python convention prefers snake_case over camelCase for method names
| return self.head == None | ||
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| def add(self, element): | ||
| temp = Node(element) |
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Forbidden Generic Name
The variable name 'temp' is a forbidden generic name. Use a more descriptive name that reflects the object's role, such as 'new_node'.
| temp = Node(element) | |
| new_node = Node(element) |
Reasons & Gaps
Reasons
- 'temp' is explicitly listed as a forbidden generic name in standards
- Descriptive names like 'new_node' clarify the variable's intent
- Reduces cognitive load when reading data structure manipulation logic
Gaps
- 'temp' is widely used in linked list logic for temporary nodes
- The scope is very limited, reducing the risk of confusion
| def search(self,item): | ||
| current = self.head | ||
| found = False | ||
| while current != None and not found: | ||
| if current.getData() == item: | ||
| found = True | ||
| else: | ||
| current = current.getNext() | ||
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| return found |
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Boolean Function Missing Prefix
This function returns a boolean value but lacks a standard boolean prefix like is_ or has_. Renaming to has_item or is_present is recommended.
| def search(self,item): | |
| current = self.head | |
| found = False | |
| while current != None and not found: | |
| if current.getData() == item: | |
| found = True | |
| else: | |
| current = current.getNext() | |
| return found | |
| def has_item(self, item): |
Reasons & Gaps
Reasons
- Functions returning booleans should use prefixes like 'is_' or 'has_'
- 'search' implies finding an object, while the return is a boolean
- Prefixing makes the API more intuitive for conditional statements
Gaps
- 'search' is a common verb for this action in data structures
- The return type is clearly boolean but the verb doesn't imply it
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| import socket | ||
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| ClientSocket = socket.socket() |
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Variable Naming Convention
The variable name 'ClientSocket' uses PascalCase, which is inconsistent with Python's snake_case convention for variables. Renaming it to 'client_socket' improves consistency and readability.
| ClientSocket = socket.socket() | |
| client_socket = socket.socket() |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require variable names to be in snake_case
- Consistent casing reduces cognitive load and follows community standards
- PascalCase is reserved for class names in Python to avoid confusion
Gaps
- PascalCase is sometimes used for global constants, though snake_case is still preferred for variables in Python
- The variable is functional and the intent is clear despite the casing violation
| except socket.error as e: | ||
| print(str(e)) | ||
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| Response = ClientSocket.recv(1024) |
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Variable Naming Convention
The variable name 'Response' uses PascalCase. In Python, variables should follow the snake_case convention (e.g., 'response') to align with standard style guides.
| Response = ClientSocket.recv(1024) | |
| response = client_socket.recv(1024) |
Reasons & Gaps
Reasons
- PEP 8 recommends snake_case for all variable and function names
- Using PascalCase for variables can lead to confusion with class definitions
- Standardizing naming styles across the codebase improves long-term maintainability
Gaps
- The variable name is descriptive of its content, only the casing is non-standard
- Local scope usage makes the impact on maintainability relatively low
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| Response = ClientSocket.recv(1024) | ||
| while True: | ||
| Input = input('Say Something: ') |
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Variable Naming Convention
The variable name 'Input' uses PascalCase and shadows the built-in 'input' function name (case-insensitively). Using 'user_input' is more idiomatic and avoids potential confusion.
| Input = input('Say Something: ') | |
| user_input = input('Say Something: ') |
Reasons & Gaps
Reasons
- Variable names should be lowercase with words separated by underscores
- Avoid naming variables similarly to built-in functions to prevent developer error
- 'user_input' provides better semantic clarity than the generic 'Input'
Gaps
- While 'Input' (capitalized) doesn't technically shadow the lowercase 'input' builtin, it is visually confusing
- The context of the loop makes the purpose of the variable obvious
| def __init__(self): | ||
| self.head = None | ||
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| def isEmpty(self): |
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Boolean Function Prefix Missing
Functions returning boolean values should be prefixed with is_, has_, can_, or should_. In Python, is_empty is the standard naming convention for this logic.
| def isEmpty(self): | |
| def is_empty(self): |
Reasons & Gaps
Reasons
- Boolean functions require a prefix like 'is_' to clarify return type
- Improves readability by signaling the function returns a truth value
- Aligns with Python naming conventions for predicate functions
Gaps
- The current name 'isEmpty' is common in other languages like Java
- The logic is perfectly clear despite the missing prefix
| self.next = Next | ||
| self.previous = Previous | ||
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| def getNext(self): |
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Python Naming Convention Violation
Method names in Python should follow the snake_case convention. 'getNext' should be renamed to 'get_next' to align with PEP 8 standards.
| def getNext(self): | |
| def get_next(self): |
Reasons & Gaps
Reasons
- PEP 8 specifies that function and method names should be lowercase
- Words in names should be separated by underscores to improve clarity
- Consistent casing reduces cognitive load during code reviews
Gaps
- CamelCase is often used by developers coming from Java/C++ backgrounds
- The function purpose is clear despite the casing style
| #This program illustrates an example of singly linked list | ||
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| class Node(object): | ||
| def __init__(self, data, Next = None, Previous = None): |
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Non-Standard Parameter Casing
Parameters 'Next' and 'Previous' use PascalCase, which is unconventional for Python arguments. Using lowercase 'next_node' or 'previous_node' is more idiomatic.
| def __init__(self, data, Next = None, Previous = None): | |
| def __init__(self, data, next_node = None, previous_node = None): |
Reasons & Gaps
Reasons
- Python parameters should be lowercase to distinguish from classes
- PascalCase for arguments violates standard Python style guidelines
- Using descriptive names like 'next_node' avoids shadowing built-ins
Gaps
- Parameter names are understandable even with unconventional casing
- 'next' is a built-in Python function, so 'next_node' is preferred over 'next'
| def getData(self): | ||
| return self.data | ||
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| def setData(self, newData): |
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Python Naming Convention Violation
Method names and parameters should use snake_case. 'setData' and 'newData' should be 'set_data' and 'new_data' respectively.
| def setData(self, newData): | |
| def set_data(self, new_data): |
Reasons & Gaps
Reasons
- Standardizes method naming across the Python codebase
- Follows PEP 8 recommendations for function and variable names
- Improves visual consistency with other snake_case elements
Gaps
- The setter pattern is clear but the naming style is non-idiomatic
- Project-specific conventions might allow camelCase for consistency
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| class Stack(object): | ||
| def __init__(self, size): | ||
| self.index = [] |
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Vague Variable Name
The variable name 'index' is vague in the context of a Stack implementation. Since it stores the actual elements of the stack, a more descriptive name like 'items' or 'elements' is recommended.
| self.index = [] | |
| self.items = [] |
Reasons & Gaps
Reasons
- 'index' usually refers to a position in a list, not the list container itself
- Using 'items' or 'elements' clearly communicates that the variable holds the stack data
- Improves maintainability by aligning variable names with their functional purpose
Gaps
- The term 'index' might be a specific internal naming choice by the developer
- In very small classes, generic names are sometimes tolerated if the scope is narrow
| else: | ||
| print('Stack is already empty!') | ||
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| def isEmpty(self): |
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Boolean Function Missing Prefix
Functions that return a boolean value should be prefixed with 'is_', 'has_', or 'can_'. In Python, 'is_empty' is the idiomatic snake_case naming convention for this check.
| def isEmpty(self): | |
| def is_empty(self): |
Reasons & Gaps
Reasons
- Boolean-returning functions require a prefix to clarify they are predicates
- Python convention (PEP 8) dictates snake_case for function and method names
- Standardizing naming patterns reduces cognitive load during code reviews
Gaps
- CamelCase is sometimes used in Python projects following legacy or Java-like styles
- The function name is technically understandable despite the missing prefix and case style
| ''' Checks whether the stack is empty ''' | ||
| return len(self.index) == [] | ||
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| def isFull(self): |
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Incorrect Case Convention
Python methods should use snake_case. Additionally, while 'is' is present, 'is_full' is the standard naming convention for boolean checks in Python.
| def isFull(self): | |
| def is_full(self): |
Reasons & Gaps
Reasons
- Violates PEP 8 naming convention which requires snake_case for methods
- Consistent naming across the class improves readability and professional quality
- Helps distinguish between standard methods and framework-specific overrides
Gaps
- The 'is' prefix is present, satisfying the boolean prefix requirement partially
- Project-specific style guides might allow camelCase for consistency with other languages
| else: | ||
| print('Stack is already empty!') | ||
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| def stackSize(self): |
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Non-Standard Method Naming
The method name 'stackSize' uses camelCase, which is not idiomatic in Python. It should be renamed to 'get_size' or 'size' using snake_case.
| def stackSize(self): | |
| def get_size(self): |
Reasons & Gaps
Reasons
- Python naming conventions require snake_case for all function and method names
- Including 'stack' in the method name is redundant as it is a method of the Stack class
- 'get_size' or 'size' is more concise and follows standard object-oriented patterns
Gaps
- 'stackSize' is descriptive, so the violation is primarily stylistic (case convention)
- Some developers prefer including the class name in methods, though it is redundant
| ARRAY_SIZE = 10000000 # Size of our array | ||
| DIVISIONS = 10 # N-ary count | ||
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| def Main(): |
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Violates Language-Specific Case Convention
In Python, function names should follow the snake_case convention. The current name 'Main' uses PascalCase, which is typically reserved for class names in Python.
| def Main(): | |
| def main(): |
Reasons & Gaps
Reasons
- Python's PEP 8 style guide explicitly requires snake_case for function names
- PascalCase for functions can be confused with class constructors by other developers
- Consistency with language standards improves codebase maintainability and readability
Gaps
- 'Main' is a common entry point name in other languages like Java or C#
- The developer might be following a personal style rather than PEP 8 standards
| DIVISIONS = 10 # N-ary count | ||
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| def Main(): | ||
| myArray = [] |
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Vague but Functional Generic Name
The variable name 'myArray' is generic and includes the data type in the name. A more descriptive name like 'search_array' or 'numbers_list' would better reflect its purpose in the N-ary search logic.
| myArray = [] | |
| search_array = [] |
Reasons & Gaps
Reasons
- Including the type 'Array' in the name is redundant and violates clean code principles
- 'myArray' does not describe the content or the role of the data being stored
- Descriptive names reduce cognitive load when reading complex algorithmic logic
Gaps
- 'myArray' is functional and common in educational or algorithm demonstration code
- The context of a search algorithm makes the purpose of the array relatively clear
| for i in range(0, 10): | ||
| randomNumber = random.randint(0, 100) #Generate a Random number between 0 to 100 | ||
| if(randomNumber > 50): | ||
| Thread1 = thread.Thread(target = Reader) |
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Non-Standard Case Convention
Variable names in Python should use snake_case. Thread1 should be renamed to thread_1 or a more descriptive name to follow PEP 8.
| Thread1 = thread.Thread(target = Reader) | |
| reader_thread = thread.Thread(target = Reader) |
Reasons & Gaps
Reasons
- PascalCase is reserved for Class names in Python per PEP 8 guidelines
- Using snake_case for instances prevents confusion with class definitions
- Descriptive names like 'reader_thread' clarify the thread's specific role
Gaps
- PascalCase is sometimes used for instances to mirror class names
- The numbering '1' is functional but less descriptive than 'reader_thread'
| import random | ||
| from collections import Counter | ||
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| someWords = '''apple banana mango strawberry orange grape pineapple apricot lemon coconut watermelon |
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Non-Standard Variable Naming
The variable name 'someWords' uses camelCase, which is non-standard for Python variables. Following PEP 8, it should be renamed to 'fruit_list' or 'word_list' using snake_case to be more descriptive and idiomatic.
| someWords = '''apple banana mango strawberry orange grape pineapple apricot lemon coconut watermelon | |
| fruit_list = '''apple banana mango strawberry orange grape pineapple apricot lemon coconut watermelon |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require snake_case for variable names
- 'fruit_list' provides better semantic clarity regarding the contents of the string
- Consistent naming styles improve maintainability across the Python ecosystem
Gaps
- The variable name is functional and understandable in the local context of a small script
- 'someWords' is partially descriptive but lacks the specific domain context of 'fruits'
| print() | ||
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| playing = True | ||
| letterGuessed = '' |
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Non-Standard Variable Naming
The variable 'letterGuessed' uses camelCase. In Python, variables should follow the snake_case convention. Renaming it to 'guessed_letters' would be more idiomatic and descriptive of the collection.
| letterGuessed = '' | |
| guessed_letters = '' |
Reasons & Gaps
Reasons
- Adheres to PEP 8 standards which recommend snake_case for all variable names
- 'guessed_letters' (plural) better represents that the string accumulates multiple characters
- Improves code consistency with standard Python library and community practices
Gaps
- The variable name is clear in its intent despite the casing violation
- Small script scope makes the impact of non-standard naming relatively low
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| if __name__ == '__main__': | ||
| print('Guess the word! HINT: word is a name of a fruit') | ||
| for i in word: |
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Single-Character Variable Name
The variable 'i' is used to iterate over characters in a word. While 'i' is acceptable for integer indices, using 'char' or 'letter' is more descriptive when iterating over a string's content.
| for i in word: | |
| for letter in word: |
Reasons & Gaps
Reasons
- Descriptive names for loop variables improve readability of the loop body
- 'letter' explicitly defines the data type and purpose within the fruit-word context
- Avoids confusion with standard integer index counters typically represented by 'i'
Gaps
- Single letters are often used in short loops, though usually reserved for integers
- The context of the loop is very small, making the purpose of 'i' immediately obvious
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| import hashlib | ||
| BLOCKSIZE = 65536 # Block read size if file is big enough | ||
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' |
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Non-Standard Variable Naming (camelCase in Python)
The variable name 'fileToOpen' uses camelCase, which is not the standard convention for Python. Following PEP 8, variable names should use snake_case to maintain consistency with the Python ecosystem.
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' | |
| file_to_open = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) prescribe snake_case for variable names
- Consistent casing improves code maintainability and readability for Python developers
- camelCase is typically reserved for other languages like Java or JavaScript
Gaps
- Project-specific style guides might occasionally override PEP 8 for legacy compatibility
- The variable name is descriptive, only the casing style is technically non-compliant
| BLOCKSIZE = 65536 # Block read size if file is big enough | ||
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' | ||
| hasher = hashlib.md5() | ||
| with open(fileToOpen, 'rb') as afile: |
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Vague Variable Name
The variable name 'afile' is somewhat generic. Using a more descriptive name like 'input_file' or 'target_file' clarifies the role of the file object within the context of the hashing operation.
| with open(fileToOpen, 'rb') as afile: | |
| with open(file_to_open, 'rb') as input_file: |
Reasons & Gaps
Reasons
- 'afile' is a generic name that adds little semantic value to the code
- Descriptive names like 'input_file' better communicate the variable's purpose
- Enhancing name clarity reduces cognitive load when reading the file operations
Gaps
- 'afile' is a common short-hand in small scripts and is partially descriptive
- The scope of the variable is limited to the 'with' block, reducing ambiguity
| fileToOpen = '/home/omkarpathak/Documents/GITs/Python-Programs/Scripts/howto.txt' | ||
| hasher = hashlib.md5() | ||
| with open(fileToOpen, 'rb') as afile: | ||
| buf = afile.read(BLOCKSIZE) |
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Non-Standard Abbreviation
The variable 'buf' is a common abbreviation for 'buffer'. Expanding it to 'buffer' or 'data_block' improves readability and follows the preference for fully expressive names.
| buf = afile.read(BLOCKSIZE) | |
| buffer = input_file.read(BLOCKSIZE) |
Reasons & Gaps
Reasons
- Standardizing on full words like 'buffer' prevents non-standard abbreviation use
- Expressive names help distinguish between different types of data containers
- Aligning with 'buffer' makes the code more accessible to junior developers
Gaps
- 'buf' is a widely recognized technical abbreviation in low-level I/O operations
- Some developers prefer short names for temporary buffers in tight loops
| def encrypt(message, key): | ||
| ''' This function lets you to encrypt your message based on a key ''' | ||
| encrypted = '' | ||
| for chars in message: |
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Non-Standard Abbreviation in Variable Name
The variable name 'chars' uses a plural form for a single character iteration. Using 'char' or 'character' is more precise and follows standard naming conventions.
| for chars in message: | |
| for char in message: |
Reasons & Gaps
Reasons
- Using plural names for single items in a loop can cause confusion about the variable type
- 'char' is the standard technical abbreviation for a single character in most languages
- Improving naming consistency reduces cognitive load during code reviews
Gaps
- 'chars' is a common pluralization and might be considered acceptable by some teams
- The context of iterating over a string makes the purpose of the variable clear despite the naming
| encrypted = '' | ||
| for chars in message: | ||
| if chars in LETTERS: | ||
| num = LETTERS.find(chars) |
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Vague Variable Name
The variable name 'num' is generic. A more descriptive name like 'letter_index' or 'char_position' would better reflect that this value represents a position within the alphabet.
| num = LETTERS.find(chars) | |
| letter_index = LETTERS.find(chars) |
Reasons & Gaps
Reasons
- 'num' does not convey the semantic meaning of the value being an alphabet index
- Descriptive names help distinguish between different numeric values in the same scope
- 'letter_index' explicitly identifies the relationship between the variable and the LETTERS string
Gaps
- 'num' is technically accurate as it holds an integer index
- In short algorithmic blocks, generic names for indices are sometimes tolerated
| def main(): | ||
| message = str(input('Enter your message: ')) | ||
| key = int(input('Enter you key [1 - 26]: ')) | ||
| choice = input('Encrypt or Decrypt? [E/D]: ') |
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Vague Variable Name
The variable 'choice' is functional but generic. Renaming it to 'operation_mode' or 'user_action' provides better context regarding what the user is choosing.
| choice = input('Encrypt or Decrypt? [E/D]: ') | |
| operation_mode = input('Encrypt or Decrypt? [E/D]: ') |
Reasons & Gaps
Reasons
- 'operation_mode' describes the intent of the variable within the cipher logic
- Generic names like 'choice' can become ambiguous as the complexity of the main function grows
- Specific naming aligns better with domain-relevant terminology for application flow
Gaps
- 'choice' is a very common name for user input variables in simple scripts
- The prompt string immediately following the variable makes the context obvious
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| import socket,sys | ||
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| def connect(host): |
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Vague Verb in Function Name
The function name 'connect' is a generic verb that doesn't fully describe the action. Since it performs a port scan, a name like 'scan_ports' or 'check_host_ports' is more appropriate.
| def connect(host): | |
| def scan_ports(host): |
Reasons & Gaps
Reasons
- Generic verbs like 'connect' lack the specific noun required for clarity
- 'scan_ports' explicitly defines the function's intent to iterate over multiple ports
- Improved naming acts as internal documentation for the script's behavior
Gaps
- The function name is technically accurate as it attempts to connect to ports
- Context within a port scanner script makes the purpose relatively clear
| print('Couldn\'t connect to Server') | ||
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| if __name__ == '__main__': | ||
| userInput = input('Enter the Server address(URL) to check for open ports: ') |
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Language-Specific Case Convention Violation
In Python, variable names should follow the snake_case convention. 'userInput' uses camelCase, which is inconsistent with PEP 8 standards.
| userInput = input('Enter the Server address(URL) to check for open ports: ') | |
| user_input = input('Enter the Server address(URL) to check for open ports: ') |
Reasons & Gaps
Reasons
- PEP 8 explicitly recommends snake_case for variable and function names in Python
- Consistent casing prevents confusion when integrating with other Python libraries
- Adhering to language idioms is a core part of professional software development
Gaps
- CamelCase is functional and common for developers coming from Java/JavaScript backgrounds
- The variable name itself is descriptive and clear despite the casing style
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| if __name__ == '__main__': | ||
| userInput = input('Enter the Server address(URL) to check for open ports: ') | ||
| remoteServerIP = socket.gethostbyname(userInput) |
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Language-Specific Case Convention Violation
The variable 'remoteServerIP' uses camelCase and contains an uppercase abbreviation 'IP'. Python standards prefer snake_case like 'remote_server_ip'.
| remoteServerIP = socket.gethostbyname(userInput) | |
| remote_server_ip = socket.gethostbyname(user_input) |
Reasons & Gaps
Reasons
- Snake_case is the standard convention for Python variables to ensure readability
- Mixing casing styles (camelCase vs snake_case) makes the codebase harder to scan
- Standardizing on 'remote_server_ip' aligns with the Python ecosystem's best practices
Gaps
- 'IP' is a standard technical abbreviation and often kept uppercase in many styles
- The name is highly descriptive and unlikely to cause functional issues
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| from multiprocessing import Process, Pipe | ||
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| def parentData(parent): |
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Non-Descriptive Function Name
The function name 'parentData' is vague and uses camelCase, which is not idiomatic for Python. A more descriptive name like 'send_parent_data' or 'handle_parent_pipe_communication' in snake_case would better reflect its purpose.
| def parentData(parent): | |
| def send_parent_data(parent): |
Reasons & Gaps
Reasons
- Function names should explicitly state the action performed using a verb-noun pattern
- Python convention (PEP 8) requires snake_case for function and variable names
- 'parentData' does not clearly communicate that it sends data through a pipe
Gaps
- The function name is partially descriptive but lacks a clear verb indicating action
- Project-specific naming conventions might allow camelCase, though PEP 8 discourages it
| parent.send(['Hello']) | ||
| parent.close() | ||
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| def childData(child): |
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Non-Descriptive Function Name
The function name 'childData' is vague and uses camelCase. Renaming it to 'send_child_data' using snake_case would improve clarity and follow Python naming standards.
| def childData(child): | |
| def send_child_data(child): |
Reasons & Gaps
Reasons
- Descriptive names reduce cognitive load by explaining the function's intent
- Standardizing on snake_case ensures consistency with the Python ecosystem
- 'send_child_data' explicitly defines the operation being performed on the pipe
Gaps
- The name is contextually understandable within this small script but lacks a strong verb
- Naming consistency with the previous function is maintained but both are non-standard
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