Python Coding FAQs — Technical and Informative Questions and Answers

8 min readDec 15, 2023

1. What is Python?

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components. Python’s simple, easy-to-learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. All these features make Python and ideal language for Python Development.

During Python Development, Python is also used as a scripting or glue language to connect existing components. Its high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development. Python’s simple, easy-to-learn syntax emphasizes readability and therefore reduces the cost of program maintenance during the Python Development process. Python supports modules and packages, which encourages program modularity and code reuse — crucial aspects for Python Development of large projects and applications.

2. What are the main features of Python?

Interpreted Language: Python is an interpreted language, which means you do not need to compile your code before running it. You can write and execute Python code interactively.
Object Oriented: Python fully supports Object Oriented Programming features like classes, inheritance, polymorphism, and encapsulation.
Easy to Learn: Python has an easy-to-read syntax and is easy to learn. It uses English keywords frequently, which makes it easier to remember.
Dynamic Typing: Variables in Python do not need explicit declaration. The type is automatically determined by the value assigned to the variable.
Large Standard Library: Python comes bundled with a large standard library, known as the Python Standard Library, which contains modules for common tasks like string processing, numeric operations, date/time utilities, network programming, etc.
Extensive Libraries: Python has an extensive collection of additional third-party libraries like NumPy, Pandas, SciPy, scikit-learn, etc that provide functionality like numerical analysis, machine learning, data science, etc.
Cross-Platform: Python code can run on Linux, Windows, macOS, and more without any changes to the code.
Free and Open Source: Python is freely available for anyone to download, use, modify, and distribute at no cost. It is also an open-source language.

3. What are Python namespaces?

A namespace in Python refers to a set of unique names (variables, classes, functions, etc.) that live in a module, class, or any other type of object or datatype. Namespaces allow organizing names so there are no collisions between names. The main Python namespaces are:

Built-in Namespace: Contains names like abs(), print(), len(), etc. Predefined in Python.
Global Namespace: Outermost namespace in a Python program/module. Contains all global names declared in a module.
Local Namespace: Contains names declared inside a function body and other blocks by default and lasts for the duration of the function.
Module Namespace: Namespace associated with a Python module. Names defined at the module level go in the module namespace.
Class Namespace: Namespaces created for each class contain its attributes and methods.
Enclosing Namespace: Namespaces associated with functions and classes contain names from local and global namespaces.

4. What are modules in Python?

Modules in Python are Python code files with .py extension. They contain reusable Python code that can be imported and used in other Python programs. Some key points about modules in Python:

Modules allow breaking programs into reusable, importable pieces.
Python code is organized into modules to maintain logical ordering.
Modules help avoid name clashes between various Python objects (classes, functions, variables) defined across projects.
Common Python operations like open(), print() etc exist as built-in modules.

Example module creation:

# mymodule.py
def func1():
  print("func1 called")
x = 5

This module can then be imported and used:

import mymodule
mymodule.func1()
print(mymodule.x)

Modules are fundamental to Python programming as they help manage large Python programs and libraries.

5. What are Python Packages?

Python packages are namespaces containing multiple Python modules. Packages are used to structure Python’s module namespace by using “namespaces” containing multiple packages and modules. Some key characteristics of packages in Python:

Python packages are simply directories of Python module files.
Package directory must contain an init.py file which allows placing Python modules within them.
init.py can be left empty or contain package initialization code.
Packages can hold sub packages as well as regular modules.

Example structure:

algos/
  __init__.py
  sorting.py
  searching.py
  linear/
    __init__.py
    regression.py

Packages help organize Python code into logical groupings and provide a mechanism for modular programming in Python. They help manage large programs by dividing code into manageable modules and submodules.

6. What are Python Functions?

Functions are a fundamental building block in Python. Some key points about Python functions:

Functions allow to group of a series of instructions to perform a specific task.
All Python code needs to be within a function namespace — either in a function or at the global namespace.
Python functions are defined using the ‘def’ keyword followed by name and parameters:

def func_name(parameters):
  # function body

Parameters are optional and functions can return values using return statements.
Functions can also have default parameter values, variable number of arguments, etc.
Recursive functions can call themselves.
Functions are invoked/called by their name followed by parentheses with arguments:

func_name(arg1, arg2)

Function objects in Python are first-class objects and can be passed around referenced variables.

Functions are essential in Python to break programs into logical, reusable units and enable modular programming.

7. What are Python Classes?

Classes are fundamental data types in Python used to represent user-defined objects. Some key aspects of classes in Python:

Classes are declared using the class keyword and use the camel case naming convention by default.
Attributes and behaviors are defined inside the class using methods and member variables.

class ClassName:
  # Class Attributes
  attribute1 = value1  
  # Constructor
  def __init__(self, arg1, arg2):
    self.attr1 = arg1
    self.attr2 = arg2
  # Method  
  def method(self):
    # Method body

Objects are instances of a class, created using the class name as a factor.
Classes support inheritance — derived classes inherit behaviors of base classes.
Polymorphism is supported — methods can be overridden in derived classes.
Encapsulation is supported using public, protected, and private attributes/methods.

Classes are fundamental to OOP in Python — they help organize code by modeling real-world problem domains into objects.

8. What are file operations in Python?

Python provides many built-in functions and methods to perform common file-related operations like:

Opening files: open(file, mode=’r’) returns a file object. Common modes are ‘r’ read, ‘w’ write, ‘a’ append, etc.

Reading Files: file.read() reads the entire file content, file.readline() reads line by line.
Writing Files: file.write(string) writes to file, file.writelines(list) writes multiple lines.
Closing Files: file.close() closes the file and flushes to disk.
Renaming/Deletion: os.rename(src, dst) renames, os.remove(file) deletes files.
Checking Path/File Attributes: os.path.exists(path), os.path.getsize(file)
Iterating Over Files: os.listdir(path) lists directory contents.
Pickle (Serialization): pickle.dump(obj, file) writes Python object to file as bytes.

Python provides robust, high-level file I/O capabilities using built-in functions and file object methods. This makes file processing very simple in Python.

9. What are Python Exceptions?

Exceptions are errors that occur during the execution of a Python program. Some key points about exceptions in Python:

Errors detected during execution are instances of built-in exception classes.
Common exceptions are ZeroDivisionError, FileNotFoundError, KeyError etc.
try/except blocks are used to handle exceptions gracefully using exception handling.

try:
  # block of code that may raise exception
except ExceptionType:
  # handler forExceptionType

Broad exceptions can be caught using bare except.
Multiple exceptions can be handled in a single except block separated by commas.
Code after finally block executes regardless of the try-except outcome.
User-defined exceptions can be created by inheriting from BaseException.
Raise keyword manually raises exceptions.

Proper exception handling ensures programs don’t crash and provides a defense against errors. It is crucial for robust Python programs.

10. What are Python Decorators?

Decorators in Python provide a way to modify or extend existing functions or classes. Key aspects:

Decorators are functions that take another function as an argument, add/modify functionality, and return it.
Decorators use the ‘@’ symbol before a function definition.

@my_decorator 
def func():
  pass

Is equivalent to func = my

11. What are Python Iterators?

Iterators in Python allow iterating over elements of an object sequentially without indexing. Some key aspects:

Iterators are objects returning data one element at a time. They are stateful objects keeping track of iteration progress.
Built-in objects supporting iteration include lists, tuples, dicts, files, etc. User-defined classes can also be iterable.
iter() function returns an iterator from a collection. next() advances the iterator to the next element.
for loop internally calls iter() and next() recycling iterator object till exception.
Generators are functions that return an iterator object. Commonly used for large data streaming.
Custom iterators can be implemented by defining iter() and next() methods.

Iterators are a powerful yet easy way to sequentially access elements without the memory overhead of lists.

12. What are Python lists?

Lists are the most versatile built-in data type in Python. Some key properties:

Lists are ordered collections of arbitrary objects referenced by indices.
Created using square brackets [] and elements separated by commas.
Heterogeneous — elements can be of any type.
Mutable — list elements can be added, accessed, modified, and removed.
Methods like append(), insert(), pop(), remove() etc modify lists.
Slices [start:stop:step] allow copying list elements efficiently.
The most commonly used data type after basic types like int, strings, etc.
Provides highly optimized implementations of common operations.
Lists are fundamental and indispensable data structures in Python for storing sequences.

13. What are Python Dictionaries?

Dictionaries in Python are unordered collections of key-value pairs. Some important properties:

Braces {} are used to denote dictionaries.
Items added using key:value syntax separated by commas.
Heterogeneous — keys can be of any immutable type, values any object.
Mutable — values can be added, changed or deleted using keys.
Methods like update(), get(), pop(), del etc modify dictionaries.
Faster than lists for element access as keys are hashed.
Commonly used as associative arrays or maps between values.
Can also be used to represent JSON data or Python objects.

Due to their fast access and flexibility, dictionaries are widely used in Python applications.

14. What are Python Conditional Statements?

Conditional statements in Python are used to control program flow based on some conditions being True or False:

if statement — blocks of code are executed conditionally if condition is True.
if-else statement — one of two blocks is executed depending on the if condition.
elif blocks can be added to execute one of many conditions.
Nested-if statements can be used for complex conditional logic.

Example:

if condition1:
  # do something
elif condition2:
  # do something 
else: 
  # default

Boolean operators like and, or not, etc are used in conditions.
Conditional expressions use the ternary operator an if condition else b.

Conditional execution is crucial for decision-making in programs based on varying input data/states.

15. How to debug Python Code?

Some common debugging techniques in Python:

Print Statements: Add print() to output values of variables during execution.
Logging: More organized via logging module to log messages on console/files.
Debugger: Integrated IDE debuggers like in VSCode, and PyCharm allow stepping through code.
Assertion Statements: Used to validate conditions using assert. Fail fast if false.
Exception Handling: Print/log exception instances to identify the error origin.
Logging Level Control: DEBUG, INFO, WARNING, etc set logging granularity.
Debugging Modules: pdb, ipdb, pdbpp provide debugging capabilities.
Profiling: cProfile helps identify bottlenecks by profiling execution times.
Unit Testing: Write tests covering different scenarios and use debugging when tests fail.

Having mastery over debugging skills is crucial when developing complex programs in Python.