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Python Standard Library Interview Questions

Comprehensive python standard library interview questions and answers for Python. Prepare for your next job interview with expert guidance.

29 Questions Available

Questions Overview

1. What are the key functions in the collections module and their use cases?

Basic

2. How do you use the datetime module for time zone aware operations?

Moderate

3. What are the main features of the itertools module?

Moderate

4. How do you use the os module for system operations?

Basic

5. What features does the json module provide for data serialization?

Basic

6. How do you use re module for regular expressions?

Moderate

7. What are the key features of the concurrent.futures module?

Advanced

8. How do you use the logging module effectively?

Moderate

9. What functionality does the pathlib module offer?

Moderate

10. How do you use the functools module for function manipulation?

Advanced

11. What features does the argparse module provide?

Moderate

12. How do you use the sqlite3 module for database operations?

Moderate

13. What are the key features of the asyncio module?

Advanced

14. How do you use the contextlib module?

Advanced

15. What functionality does the csv module provide?

Basic

16. How do you use the threading module?

Advanced

17. What features does the random module offer?

Basic

18. How do you use the pickle module for serialization?

Moderate

19. What are the key features of the sys module?

Moderate

20. How do you use the shutil module?

Moderate

21. What functionality does the urllib module provide?

Moderate

22. How do you use the time module effectively?

Basic

23. What features does the enum module offer?

Moderate

24. How do you use the subprocess module?

Advanced

25. What are the key features of the statistics module?

Moderate

26. How do you use the multiprocessing module?

Advanced

27. What functionality does the tempfile module provide?

Moderate

28. How do you use the operator module?

Moderate

29. What features does the platform module offer?

Basic

1. What are the key functions in the collections module and their use cases?

Basic

Collections module provides specialized container types: defaultdict (automatic default values), Counter (counting hashable objects), deque (double-ended queue), namedtuple (tuple with named fields), OrderedDict (ordered dictionary pre-3.7). Each optimized for specific use cases and performance requirements.

2. How do you use the datetime module for time zone aware operations?

Moderate

datetime module handles dates and times. Use datetime.datetime with tzinfo for timezone awareness, pytz for reliable timezone handling. Methods: astimezone(), replace(tzinfo=), timezone conversions. Consider DST transitions, UTC conversions.

3. What are the main features of the itertools module?

Moderate

itertools provides functions for efficient iteration: combinations(), permutations(), product() for combinatorics; cycle(), repeat() for infinite iterators; chain(), islice() for iterator manipulation. Memory efficient for large datasets.

4. How do you use the os module for system operations?

Basic

os module provides OS-independent interface for operating system operations. Functions: os.path for path manipulation, os.environ for environment variables, os.walk for directory traversal. Consider platform differences, security implications.

5. What features does the json module provide for data serialization?

Basic

json module handles JSON encoding/decoding. Methods: dumps()/loads() for strings, dump()/load() for files. Supports custom serialization with default/object_hook. Handle encoding issues, pretty printing, security considerations.

6. How do you use re module for regular expressions?

Moderate

re module provides regular expression operations: compile(), match(), search(), findall(). Supports patterns, groups, flags. Consider using raw strings (r'pattern'), pre-compilation for performance. Handle different regex patterns and flags.

7. What are the key features of the concurrent.futures module?

Advanced

concurrent.futures provides high-level interface for asynchronous execution: ThreadPoolExecutor for I/O-bound tasks, ProcessPoolExecutor for CPU-bound tasks. Supports map(), submit(), as_completed(). Handle thread/process management, exceptions.

8. How do you use the logging module effectively?

Moderate

logging provides flexible event logging: different levels (DEBUG to CRITICAL), handlers, formatters. Configure using basicConfig() or dictConfig(). Consider log rotation, formatting, handling in different environments.

9. What functionality does the pathlib module offer?

Moderate

pathlib provides object-oriented interface for file system paths. Path class methods: glob(), mkdir(), touch(), resolve(). More readable than os.path, handles platform differences. Consider migration from os.path.

10. How do you use the functools module for function manipulation?

Advanced

functools provides tools for functional programming: partial() for partial application, lru_cache() for caching, reduce() for reduction operations. Includes wraps() for preserving function metadata. Consider performance implications.

11. What features does the argparse module provide?

Moderate

argparse handles command-line argument parsing: argument types, help messages, subcommands. Supports required/optional arguments, default values, custom actions. Consider user interface design, error handling.

12. How do you use the sqlite3 module for database operations?

Moderate

sqlite3 provides SQLite database interface: connection management, cursor operations, parameter substitution. Supports transactions, custom row factories. Consider connection lifecycle, error handling, SQL injection prevention.

13. What are the key features of the asyncio module?

Advanced

asyncio provides infrastructure for async/await code: event loops, coroutines, tasks. Supports async I/O operations, concurrency. Handle task scheduling, synchronization primitives, error handling.

14. How do you use the contextlib module?

Advanced

contextlib provides utilities for context managers: @contextmanager decorator, ExitStack for multiple contexts. Supports resource management, cleanup operations. Consider error handling, nested contexts.

15. What functionality does the csv module provide?

Basic

csv handles CSV file operations: reading, writing, different dialects. Supports DictReader/DictWriter for named columns. Handle different formats, encoding issues, custom dialects. Consider large file handling.

16. How do you use the threading module?

Advanced

threading provides high-level threading interface: Thread class, synchronization primitives (Lock, Event). Handle thread creation, synchronization, communication. Consider thread safety, deadlock prevention.

17. What features does the random module offer?

Basic

random provides pseudo-random number generation: randint(), choice(), shuffle(). Supports different distributions, seeding. Consider cryptographic needs (use secrets instead), reproducibility requirements.

18. How do you use the pickle module for serialization?

Moderate

pickle handles Python object serialization: dump()/load() for files, dumps()/loads() for bytes. Consider security implications, version compatibility. Handle custom object serialization, protocol versions.

19. What are the key features of the sys module?

Moderate

sys provides system-specific parameters/functions: sys.path for module search, sys.argv for command arguments, sys.stdin/stdout/stderr for I/O. Handle interpreter interaction, system limitations.

20. How do you use the shutil module?

Moderate

shutil provides high-level file operations: copyfile(), rmtree(), make_archive(). Supports file copying, removal, archiving. Handle permissions, recursive operations, platform differences.

21. What functionality does the urllib module provide?

Moderate

urllib handles URL operations: request handling, parsing, encoding. Modules: request for HTTP, parse for URL parsing, error for exceptions. Consider error handling, security, timeout configuration.

22. How do you use the time module effectively?

Basic

time provides time-related functions: time() for timestamps, sleep() for delays, strftime() for formatting. Handle different time representations, platform differences. Consider timezone implications.

23. What features does the enum module offer?

Moderate

enum provides enumeration support: Enum class, auto() for automatic values. Supports unique/non-unique values, custom behavior. Consider type safety, value comparison, serialization needs.

24. How do you use the subprocess module?

Advanced

subprocess manages external processes: run(), Popen for process control. Handle command execution, I/O redirection, process communication. Consider security, platform differences, error handling.

25. What are the key features of the statistics module?

Moderate

statistics provides statistical functions: mean(), median(), mode(), stdev(). Supports different types of averages, variance calculations. Consider numerical stability, data types, population vs sample.

26. How do you use the multiprocessing module?

Advanced

multiprocessing provides process-based parallelism: Process class, Pool for worker pools. Handle process creation, communication, synchronization. Consider GIL bypass, resource sharing, cleanup.

27. What functionality does the tempfile module provide?

Moderate

tempfile handles temporary files/directories: TemporaryFile, NamedTemporaryFile, TemporaryDirectory. Supports secure creation, automatic cleanup. Consider platform differences, cleanup guarantees.

28. How do you use the operator module?

Moderate

operator provides function equivalents of operators: itemgetter(), attrgetter() for data access, add(), mul() for arithmetic. Useful in functional programming, sorting. Consider performance implications.

29. What features does the platform module offer?

Basic

platform provides system information: system(), machine(), python_version(). Access hardware, OS details, Python environment. Consider cross-platform compatibility, information security.

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