Tag: maintainability
Improper error handling can enable attacks and lead to unwanted behavior.
Swallowing exceptions, without re-throwing or logging them, is a bad practice.
Not setting seeds for the random number generators in Pytorch can lead to reproducibility issues.
Classes with low class cohesion contain unrelated operations which make them difficult to understand and less likely to be used.
Do not pass generic exception.
Non-deterministic ops might return different outputs when run with the same inputs.
Using outdated multiprocessing API calls and parameters is not recommended.
Default values in Python are created exactly once, when the function is defined. If that object is changed, subsequent calls to the function will refer to the changed object, leading to confusion.
Violating PEP8 programming recommendations might make code difficult to read and can introduce ambiguity.
Complex code can be difficult to read and hard to maintain.
The Debug feature should not be enabled or overridden.
Using the get
method from the dict
class without default values can cause runtime exceptions.
Incorrect use of API leads to ambiguity and inconsistency
list
replication using replication operator creates references to the existing objects, not copies, which could introduce bugs.
Detects if nondeterministic tensorflow APIs are used.
Best practices to improve the maintainability of notebooks.
This code uses deprecated methods, which suggests that it has not been recently reviewed or maintained.
Detects if a random seed is set before random number generation.
Catching and re-throwing an exception without further actions is redundant and wasteful.
Response metadata was not checked to verify that it is not None
.
Global variables can be dangerous and cause bugs because they can be simultaneously accessed from multiple sections of a program.
Methods that return multiple values can be difficult to read and prone to error.
Overriding environment variables that are reserved by AWS Lambda might lead to unexpected behavior.
Directly modifying the __dict__
object might cause undesirable behavior due to symbol table modification.
Inefficient regular expression patterns can lead to catastrophic backtracking.