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129 changes: 129 additions & 0 deletions hello1.py
Original file line number Diff line number Diff line change
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import random
import pdb

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Module pdb imported at line 2 risks debug statements in production

The module pdb is imported on line 2 for debugging purposes but left in the checked-in code. This increases the risk of unintentional debugger activation in production, which can halt execution and expose internals. Remove the pdb import and all related debug calls before deployment.

import sys as sys
import os
import subprocess
import abc

# from django.db.models.expressions import RawSQL

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Commented import RawSQL unused in module, cluttering at import section

The import statement RawSQL from django.db.models.expressions on line 8 is commented out yet remains in the code. This commented code adds unnecessary clutter and decreases readability, potentially confusing developers about its purpose. Remove the commented lines to clean up and maintain the codebase.


AWS_SECRET_KEY = "d6s$f9g!j8mg7hw?n&2"

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Hardcoded AWS_SECRET_KEY found in the source file

A hardcoded secret AWS_SECRET_KEY is present in the source code. Storing secrets in code is a major security risk, as it can be exposed through version control history to unauthorized individuals, leading to compromised AWS resources. Secrets should be managed via a secure vault or environment variables.

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Hardcoded secret AWS_SECRET_KEY found in source code

A secret key is hardcoded in the source file. This is a significant security risk, as it exposes sensitive credentials to anyone with access to the codebase. Secrets should be managed through a secure vault or environment variables, not stored in code.

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Hardcoded sensitive credential AWS_SECRET_KEY found in source code

A hardcoded AWS secret key is present in the codebase. This is a significant security risk, as it exposes sensitive credentials to anyone with access to the source code. Secrets should be managed through a secure vault or environment variables, not stored in code.

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Hardcoded AWS_SECRET_KEY found in source code

The AWS_SECRET_KEY is hardcoded in the source file. This is a major security risk, as it exposes sensitive credentials to anyone with access to the codebase. Secrets should be loaded from a secure vault or environment variables.



class BaseNumberGenerator:
"""Declare a method -- `get_number`."""

def __init__(self):
self.limits = (1, 10)

def get_number(self, min_max):
raise NotImplemented

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NotImplemented is raised instead of NotImplementedError

The code raises NotImplemented, which is a special singleton value used in rich comparison methods to indicate that the operation is not implemented for the given types. The correct exception to raise for an unimplemented method is NotImplementedError.

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Variable error raised with unsupported None or object type at line 20

The variable error is assigned None initially, then potentially assigned exceptions conditionally, and finally raised on line 20. Raising a variable that can be None or not an instance of Exception causes a TypeError. Replace by raising exception objects directly within conditional blocks to avoid unsupported raises.

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Function get_number() raises invalid exception NotImplemented at line 20

The function get_number() raises NotImplemented on line 20, which is not a valid exception type and will result in a TypeError. This causes the program to crash unexpectedly and breaks expected exception handling. Replace raise NotImplemented with raise NotImplementedError or use return NotImplemented if signalling unimplemented operation is desired.


def smethod():
"""static method-to-be"""

smethod = staticmethod(smethod)

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Method smethod defined without @staticmethod decorator in class

The method smethod is declared on line 25 and converted to a static method via assignment instead of using the @staticmethod decorator. This reduces code readability and clarity regarding method type. Replace the assignment with the @staticmethod decorator above smethod for clearer and more modern syntax.


def cmethod(cls, something):
"""class method-to-be"""

cmethod = classmethod(cmethod)

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Function cmethod assigned as classmethod without @classmethod decorator at line 30

The function cmethod on line 30 is converted to a class method by assignment instead of using the @classmethod decorator. This reduces code readability and deviates from modern Python best practices. Replace the assignment with the explicit @classmethod decorator above the method definition for clarity and consistency.

Comment on lines +22 to +30

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Outdated syntax is used to define static and class methods

The functions smethod and cmethod are converted to static and class methods using outdated syntax (staticmethod(smethod)). The modern and more readable approach is to use the @staticmethod and @classmethod decorators directly above the method definition. This improves code clarity and maintainability.

Comment on lines +22 to +30

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Static and class methods are defined in an outdated way

The smethod and cmethod are defined and then converted to static and class methods using staticmethod() and classmethod() calls. The modern and more readable approach is to use the @staticmethod and @classmethod decorators directly above the method definitions.



class RandomNumberGenerator:
"""Generate random numbers."""

def limits(self):
return self.limits

def get_number(self, min_max=[1, 10]):

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Mutable list [1, 10] is used as a default argument

The get_number method uses a mutable list [1, 10] as a default argument. This is dangerous because the default list is created only once and will be modified in place if the caller mutates it. Subsequent calls without providing the argument will use the modified list, leading to unexpected behavior.

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Mutable default argument min_max=[1, 10] is used in a function definition

The function get_number uses a mutable list [1, 10] as a default argument for min_max. This list is created only once when the function is defined. If the list is modified in any call, the modification will persist for all subsequent calls, leading to unexpected behavior.

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Method get_number lacks @staticmethod decorator impacting class instances

The method get_number on line 39 does not use the instance (self) but is defined as an instance method. This causes unnecessary bound method creation for every class instance, wasting memory and CPU time. Add @staticmethod decorator above get_number to optimize performance.

"""Get a random number between min and max."""
assert all([isinstance(i, int) for i in min_max])

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Assert statement assert all([isinstance(i, int) for i in min_max]) in get_number() risks removal on optimization

The assert statement on line 41 in the get_number() method performs an internal check for integer types but is removed when Python code is run with optimization flags like -O. This leads to potential silent failures or unexpected behavior in production. Replace the assert with an explicit conditional check and raise an appropriate exception to ensure the check is always enforced.

return random.randint(*min_max)


def main(options: dict = {}) -> str:

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Mutable dictionary {} is used as a default argument

The main function uses a mutable dictionary {} as a default argument. This is risky because the default dictionary is created only once. If it's modified by any call to the function, that modification will persist for all subsequent calls that use the default, leading to unpredictable behavior.

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A mutable dictionary is used as a default function argument

The default argument for options is a mutable dictionary. This can lead to unexpected behavior, as modifications to options in one call will persist and affect subsequent calls that rely on the default. Use None as the default and initialize a new dictionary inside the function.

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Mutable default argument options: dict = {} is used in a function definition

The function main uses a mutable dictionary {} as a default argument for options. This dictionary is created only once. Any modification to options within the function will be carried over to subsequent calls, which can lead to unpredictable behavior and bugs that are hard to trace.

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Function main uses a mutable dictionary as a default argument

The default argument options is a dictionary, which is a mutable type. If the function were to modify options, the mutation would persist across calls, which can lead to unexpected and buggy behavior. Default arguments should use immutable types.

pdb.set_trace()
Comment on lines +2 to +46

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Debugger pdb is imported and set_trace() is called

The code imports the pdb module and contains a call to pdb.set_trace(). This is a debugging statement that will pause the execution of the program, waiting for interactive user input. Leaving debugger entry points in production code can lead to unexpected hangs and potential security risks.

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Debugger pdb.set_trace() is present in the code

The pdb.set_trace() function is used, which starts a debugger session. If this code is deployed to a production environment, it can halt the application and expose a debugging shell, which is a major security risk. Debugging code should be removed before deployment.

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Debugger breakpoint pdb.set_trace() left in the code

A debugger breakpoint pdb.set_trace() is present in the code. This should be removed from production code as it can expose sensitive information and allow an attacker to halt execution and inspect the application's state if they can trigger it.

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A pdb.set_trace() call is present in the code

The code contains a call to pdb.set_trace(), which will pause execution and start a debugger. If this code is deployed to a production environment, it could halt the application and expose a debugging shell, creating a security risk.

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Use of pdb.set_trace() causes unintended program halts

The code calls pdb.set_trace() on line 46, which triggers a breakpoint stopping execution and entering debug mode unexpectedly. This disrupts normal program flow and may expose debugging internals or stall production applications.

Remove or comment out all pdb.set_trace() calls before committing code to prevent unintended debug halts in production environments.

if "run" in options:
value = options["run"]
else:
value = "default_value"

if type(value) != str:
raise Exception()
else:
value = iter(value)

sorted(value, key=lambda k: len(k))

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The result of the sorted() function call is not used

The result of sorted(value, ...) is not assigned to any variable, and since sorted() returns a new list without modifying the input, this line has no effect. The original value (which is an iterator) is consumed but the sorted result is lost.

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The return value of sorted() is not used or assigned

The result of the sorted() function is not assigned to any variable. sorted() returns a new sorted list and does not modify the original iterable. As a result, this line of code has no effect, and the value iterable remains unsorted. This is likely a bug.

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The result of the sorted() function is not used

The sorted() function returns a new sorted list, but the result is not assigned to any variable or used in any way. The original value (which is an iterator) is not modified. This line of code has no effect on the program's execution.

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Lambda expression lambda k: len(k) used unnecessarily in sorted on line 57

The lambda k: len(k) is used as a key function in the sorted call on line 57 but simply wraps the built-in len function. This adds unnecessary complexity and reduces readability. Replace the lambda with the direct use of len by passing key=len to sorted, improving clarity and debugging.


f = open("/tmp/.deepsource.toml", "r")

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File created at a predictable path in a public directory

A file is created at a predictable path /tmp/.deepsource.toml. Using hardcoded paths in world-writable directories like /tmp is insecure. An attacker could pre-create this file (or a symlink) to control its contents or permissions, potentially leading to unauthorized access or denial of service.

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Local variable filename shadows global filename causing confusion in file handling

The local variable filename in the read_file(filename) function shadows the global filename defined at line 1, making the global variable inaccessible within the function. This can lead to confusion and bugs when the variable usage is ambiguous. Rename the global variable using UPPER_CASE or restructure like moving globals to main() context to avoid such shadowing.

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File is opened with open() and closed with close() instead of using a with block

A file is opened but not closed using a with statement. If an exception occurs between open() and close(), the file handle may not be closed properly, leading to resource leaks. The with statement ensures that the file is closed automatically, even if errors occur.

f.write("config file.")
Comment on lines +59 to +60

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Attempting to write to a file opened in read-only mode

The file /tmp/.deepsource.toml is opened in read mode ("r"), but the code then attempts to write to it using f.write(). This will raise an io.UnsupportedOperation: not writable exception at runtime, causing the program to crash. The file should be opened in a write-compatible mode like "w".

Comment on lines +59 to +60

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File is opened in read-only mode but is then written to

The file is opened in read mode ("r"), but then f.write() is called. This will raise an io.UnsupportedOperation error at runtime because writing is not allowed in read mode. The mode should be changed to one that allows writing, such as "w" or "w+".

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Attempting to write to a file opened in read-only mode

The file is opened in read mode ("r"), but the code then attempts to write to it using f.write(). This will raise an io.UnsupportedOperation: not writable exception at runtime, causing the program to crash. The file should be opened in a write-compatible mode like "w" or "w+".

Comment on lines +59 to +60

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Attempting to write to a file opened in read-only mode

The file at /tmp/.deepsource.toml is opened in read mode ("r"), but the code then attempts to write to it with f.write(). This will raise an io.UnsupportedOperation error at runtime. The file should be opened in a write-compatible mode (e.g., "w", "a", "w+").

f.close()
Comment on lines +59 to +61

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File is not opened using a with statement for safe handling

The file is opened using open() and closed with f.close(), but this pattern is not robust. If an exception occurs between these two calls, the file handle may not be closed, leading to resource leaks. The with open(...) as f: statement should be used to ensure the file is closed automatically.



def moon_chooser(moon, moons=["europa", "callisto", "phobos"]):

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Mutable list is used as a default argument for moons

The moon_chooser function uses a mutable list as a default argument for moons. This list is created only once. Each time the function is called with a new moon, it appends to the same list, causing the list of moons to grow unexpectedly across function calls.

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A mutable list is used as a default function argument

The default argument for moons is a mutable list. This list will be modified in-place across different calls to moon_chooser, causing unexpected behavior. Subsequent calls will see the moon values appended from previous calls, which is likely not the intended logic.

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Mutable default argument moons=[...] is used in a function definition

The function moon_chooser uses a mutable list as a default argument for moons. This list is created once and shared across all calls to the function. Since the function appends to this list, each call will affect the moons list for all subsequent calls, leading to unexpected results.

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Function moon_chooser uses a mutable list as a default argument

The default argument moons is a list. It will be mutated by moons.append(moon) and this mutation will persist across calls to the function, leading to unexpected behavior. Default arguments should be immutable.

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Mutable default moons list causes state persistence across calls

The function moon_chooser uses a mutable default argument moons initialized to a list. This list is shared across all calls, so appending moon modifies it permanently, causing unexpected side effects and bugs in subsequent calls.

Replace the default list with None and initialize inside the function: use moons=None, then if moons is None: moons = [] to ensure a fresh list on every call.

if moon is not None:
moons.append(moon)

return random.choice(moons)


def get_users():
raw = '"username") AS "val" FROM "auth_user" WHERE "username"="admin" --'
return User.objects.annotate(val=RawSQL(raw, []))

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Use of RawSQL with a concatenated string poses a SQL injection risk

The code uses RawSQL to execute a raw SQL query fragment. While the current implementation uses a hardcoded string, this pattern is extremely dangerous as it's susceptible to SQL injection if any part of the raw string were to be constructed from user input. Using parameterized queries is the standard defense.

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Use of RawSQL with a concatenated string can lead to SQL injection

The function get_users uses RawSQL to execute a raw SQL query string. While the string is hardcoded in this instance, this pattern is extremely dangerous and highly susceptible to SQL injection if any part of the string becomes variable. Avoid RawSQL with string formatting.

Comment on lines +72 to +73

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Use of RawSQL with a string literal demonstrates a dangerous pattern

The code uses RawSQL with a hardcoded SQL string. While not directly exploitable here because the string is not from user input, this pattern is extremely dangerous and highly susceptible to SQL injection if any part of the raw string is ever constructed from external data. Use parameterized queries instead.



def tar_something():
os.tempnam("dir1")

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Insecure function os.tempnam() is used for temporary file creation

The function os.tempnam() is used, which is insecure and has been deprecated. It is vulnerable to a race condition (TOCTOU) where an attacker can create a symbolic link with the same name as the temporary file between its creation and its use, potentially leading to unauthorized file access or modification.

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The deprecated function os.tempnam is used

The function os.tempnam is deprecated since Python 2.3 and is insecure. It's recommended to use the tempfile module, such as tempfile.mkstemp() for files or tempfile.mkdtemp() for directories, to create temporary files and directories securely and without warnings.

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Insecure and deprecated function os.tempnam is used

The function os.tempnam is deprecated and insecure. It is vulnerable to a race condition where an attacker can create a symbolic link with the generated temporary name before the application creates the file, potentially leading to file overwrites or information disclosure. Use the tempfile module instead.

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Use of insecure and deprecated function os.tempnam

The function os.tempnam is used, which is insecure and has been deprecated. It is vulnerable to a race condition where a malicious actor could create a symbolic link with the generated name before the program opens the file, potentially leading to file overwrites or other exploits. Use tempfile.mkstemp instead.

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os.tempnam is deprecated and insecure due to race conditions

os.tempnam is deprecated and vulnerable to a race condition (TOCTOU) where an attacker can create a symlink with the predicted temporary filename to a sensitive file, potentially causing it to be overwritten or modified by the application. Use the tempfile module for secure temporary file creation.

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Use of os.tempnam() allows symlink attacks in file creation

The os.tempnam() function creates temporary file names insecurely, enabling attackers to exploit symlink redirection vulnerabilities. This can lead to unauthorized file access or modification during tar_something() execution.

Replace os.tempnam() with safer alternatives like tempfile.NamedTemporaryFile() or use os.tmpfile() for secure, atomic temporary file creation.

subprocess.Popen("/bin/chown *", shell=True)

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subprocess.Popen is used with shell=True and a wildcard *

The command /bin/chown * is executed with shell=True. This is a command injection vulnerability. An attacker who can control filenames in the working directory could inject malicious arguments. For example, a file named "-R root" would change the command to /bin/chown -R root, escalating privileges.

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subprocess.Popen is used with shell=True which is a security risk

Using subprocess.Popen with shell=True is a security risk. The command string contains a wildcard * which will be expanded by the shell. An attacker who can control filenames in the current directory could inject malicious arguments, leading to arbitrary command execution.

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subprocess.Popen is used with shell=True and a wildcard character *

The function subprocess.Popen is called with shell=True and a command string containing a wildcard *. This can lead to command injection, as the shell will expand the wildcard. An attacker could create files with malicious names (e.g., ; rm -rf /) in the current directory to execute arbitrary commands.

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Use of shell=True with wildcard * allows command injection

The subprocess.Popen call uses shell=True with a command containing a wildcard *. An attacker who can control filenames in the current directory can inject arbitrary commands or arguments, leading to code execution. For example, a file named ; rm -rf / could be executed by the shell.

o.system("/bin/tar xvzf *")

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os.system is used with a command containing a wildcard *

The code calls o.system (presumably os.system), which executes a command via the shell. The command /bin/tar xvzf * contains a wildcard *, making it vulnerable to command injection. An attacker who can create files could inject malicious arguments, e.g., a file named "--use-compress-program=rm -rf /".

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Variable o is not defined when calling o.system()

The code attempts to call o.system(), but the variable o is not defined anywhere in the scope. This will cause a NameError at runtime, crashing the program. It's likely that os was intended instead of o. This is a critical bug that prevents the function from working.

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os.system is used to execute a shell command with a wildcard

The code uses o.system (presumably os.system) to execute a shell command containing a wildcard *. This is vulnerable to command injection, as an attacker controlling filenames in the directory could execute arbitrary code. os.system is deprecated in favor of subprocess.

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os.system is used with a command containing a wildcard character *

The function os.system is used with a command string containing a wildcard *. This is vulnerable to command injection. The shell expands *, allowing an attacker to execute arbitrary commands by creating files with specially crafted names in the target directory. os.system is inherently risky and should be avoided.

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Use of os.system with wildcard * allows command injection

The os.system call executes a command in a subshell, and the wildcard * is expanded by the shell. An attacker who can control filenames in the current directory can inject arbitrary commands, leading to code execution. This is also a bug since o is not defined.



def bad_isinstance(initial_condition, object, other_obj, foo, bar, baz):
if (
initial_condition
and (
isinstance(object, int)
or isinstance(object, float)
or isinstance(object, str)
)
and isinstance(other_obj, float)
and isinstance(foo, str)
or (isinstance(bar, float) or isinstance(bar, str))
and (isinstance(baz, float) or isinstance(baz, int))
):
Comment on lines +83 to +94

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Multiple isinstance checks are used instead of a single check with a tuple

The if condition uses multiple isinstance checks with or. This can be simplified by passing a tuple of types to a single isinstance call, which is more efficient and readable. For example, isinstance(object, (int, float, str)) is preferred over three separate checks.

pass


def check(x):
if x == 1 or x == 2 or x == 3:
print("Yes")
elif x != 2 or x != 3:

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The condition x != 2 or x != 3 is always true

The condition x != 2 or x != 3 will always evaluate to True for any number x. A number cannot be equal to both 2 and 3 simultaneously, so it must be not equal to at least one of them. This is a logical error and likely not the intended behavior.

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The condition x != 2 or x != 3 is always true

The condition x != 2 or x != 3 will always evaluate to True for any integer x. If x is 2, x != 3 is true. If x is 3, x != 2 is true. If x is any other number, both are true. This is a logical error and the code block will always be executed.

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The condition x != 2 or x != 3 is tautological and always evaluates to true

The condition x != 2 or x != 3 is always true for any value of x. If x is 2, x != 3 is true. If x is 3, x != 2 is true. If x is any other number, both are true. This is a logical error and the code block will always be executed if the preceding if is false.

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The condition x != 2 or x != 3 is always true

The condition x != 2 or x != 3 will always evaluate to True for any integer x. If x is 2, x != 3 is true. If x is 3, x != 2 is true. If x is any other number, both are true. The programmer likely intended to use and.

print("also true")

elif x in (2, 3) or x in (5, 4):
print("Here")

elif x == 10 or x == 20 or x == 30 and x == 40:

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Condition mixes or and and operators without parentheses, causing ambiguity

The condition mixes or and and operators without explicit parentheses. Due to operator precedence (and is evaluated before or), the logic is (x == 10) or (x == 20) or (x == 30 and x == 40). This is confusing and likely not the intended logic. Use parentheses to clarify intent.

print("Sweet!")

elif x == 10 or x == 20 or x == 30:

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Variable x compared repeatedly using or in if-elif statements at line 110

The variable x is compared with multiple values separately using or operators on line 110, causing verbose and less efficient code. This can reduce performance and readability when checking membership among several values. Replace the chained equality checks with if x in (10, 20, 30, 40): to improve clarity and speed.

print("Why even?")

def chained_comparison():
a = 1
b = 2
c = 3
return a < b and b < c

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Comparison a < b and b < c can be chained as a < b < c

The expression a < b and b < c is a valid but unpythonic way to check if b is between a and c. Python supports chained comparisons, which are more readable and efficient. The code can be simplified to a < b < c.

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A chained comparison is written in a verbose way

The chained comparison a < b and b < c can be simplified in Python. Python supports chained comparisons, which are more readable. This can be rewritten as a < b < c, which is more concise and idiomatic.

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Expression a < b and b < c in line 117 should use chained comparison for clarity

The boolean operation a < b and b < c is used on line 117, which can be simplified to a < b < c. Chained comparisons improve code readability and make conditions more concise. Refactor the return statement to use return a < b < c for clarity and cleaner code.


if __name__ == "__main__":
args = ["--disable", "all"]
f = open("/tmp/.deepsource.toml", "r")
f.write("config file.")
Comment on lines +121 to +122

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Attempting to write to a file opened in read-only mode

The file /tmp/.deepsource.toml is opened in read mode ("r"), but the code then attempts to write to it using f.write(). This will raise an io.UnsupportedOperation: not writable exception at runtime, causing the program to crash. The file should be opened in a write-compatible mode like "w".

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File object f opened in read mode but used with write() on line 122

The file f is opened in read mode ("r") on line 122 but immediately used with write(), which causes an IOError. This is a misuse of file modes leading to runtime exceptions that break program flow. Fix by opening the file with write mode ("w") to allow writing to the file as intended.

Comment on lines +60 to +122

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Attempting to write to a file opened in read mode

The code attempts to write to a file that was opened in read-only mode ("r"). This will raise an io.UnsupportedOperation: not writable exception at runtime, causing the program to crash. This error occurs in both the main function and the __main__ block.

f.close()
assert args is not None
for i in range(len(args)):

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Looping over range(len(args)) is not idiomatic Python

The code iterates using for i in range(len(args)), which is an unpythonic C-style loop. The idiomatic way to loop in Python is to iterate directly over the elements of the iterable, such as for item in args. This is more readable and less error-prone.

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Unpythonic loop using range(len(...)) to iterate

The loop for i in range(len(args)) is unpythonic. It is more idiomatic and readable to iterate directly over the elements of the list. Instead of accessing elements by index with args[i], you can use a direct loop variable.

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Unpythonic loop for i in range(len(args)) is used to iterate

A C-style for loop using range(len(args)) is used to iterate over a list. The Pythonic way to do this is to iterate directly over the elements of the list, which is more readable and efficient. If the index is needed, use enumerate.

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Range(len(args)) iteration used instead of enumerate() in loop at line 125

The code uses for i in range(len(args)) at line 125 to iterate over args by index. This style is less Pythonic and decreases readability. Replace with for i, arg in enumerate(args): to directly access the element and index, improving clarity and maintaining cleaner iteration.

has_truthy = True if args[i] else False

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Verbose boolean conversion True if ... else False is used

The expression True if args[i] else False is a verbose way to convert a value to a boolean. The more concise and idiomatic way to do this is to use the bool() constructor, i.e., bool(args[i]).

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Variable has_truthy assigned via redundant if expression in loop at line 126

The variable has_truthy is assigned using True if args[i] else False on line 126, which is a redundant if expression. This reduces code readability and may confuse maintainers. Simplify assignment by using has_truthy = bool(args[i]) for cleaner, more idiomatic code.

assert has_truthy is not None
if has_truthy:
break
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