Filter interviews by
A medium python program
Optimizing code for better performance and efficiency
Use built-in functions and libraries for faster execution
Minimize unnecessary loops and conditions
Avoid redundant code and optimize data structures
Implement caching or memoization for repetitive computations
Optimizing Python code involves improving efficiency and performance.
Use built-in functions and libraries instead of writing custom code
Avoid unnecessary loops and nested loops for better performance
Optimize data structures and algorithms for faster execution
Numpy is a powerful library for numerical operations in Python, with efficient array operations and mathematical functions.
Use vectorized operations instead of loops for better performance.
Avoid unnecessary copying of arrays to save memory.
Utilize broadcasting to perform operations on arrays of different shapes.
Use numpy functions like np.sum(), np.mean(), np.max(), etc. for efficient calculations.
Optimize code by prof
posted on 8 Apr 2022
Byte code is a low-level code that is executed by the Python interpreter. Filter function is used to filter elements from an iterable.
Byte code is a compiled code that is generated from Python source code.
It is a platform-independent code that can be executed on any system with a Python interpreter.
Filter function takes an iterable and a function as input and returns a new iterable with elements for which the function ...
Python uses automatic memory management through a combination of reference counting and garbage collection.
Python uses reference counting to keep track of the number of references to an object.
When the reference count reaches zero, the object is immediately deallocated.
Python also employs a garbage collector to handle cyclic references and objects with circular dependencies.
The garbage collector identifies and collects...
Sets are unordered collections of unique elements, while tuples are ordered collections of elements.
Sets are defined by curly braces {} and tuples are defined by parentheses ()
Sets do not allow duplicate elements, while tuples can contain duplicate elements
Sets are mutable, meaning their elements can be added, removed, or modified, while tuples are immutable
Sets are commonly used for membership testing and eliminating ...
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