Practice Python Memory Optimization MCQ questions with detailed explanations and clear answer validation. These MCQs help you revise core concepts, compare close options, and improve accuracy for interviews, certification exams, and technical screening rounds. Use this updated 2026 set to strengthen fundamentals and confidence.
Q51. Which statement about small int cache is most accurate?
Select an answer to check.
Answer: Small ints are cached by CPython.
Here, Small ints are cached by CPython. is the right choice. Implementation detail. It aligns directly with what the question asks about which statement about small int cache is most. Competing choices sound plausible, but they miss the key condition.
Q52. How is small int cache best characterized?
Select an answer to check.
Answer: Small ints are cached by CPython.
In this case, Small ints are cached by CPython. is correct. Implementation detail. It aligns directly with what the question asks about how is small int cache best characterized. Competing choices sound plausible, but they miss the key condition.
Q53. Which option best describes memory profiling in Python?
Select an answer to check.
Answer: tracemalloc, memray, scalene.
The best option here is tracemalloc, memray, scalene.. Find allocation hotspots. It aligns directly with what the question asks about which option best describes memory profiling in python. Competing choices sound plausible, but they miss the key condition.
Q54. What is the primary purpose of memory profiling?
Select an answer to check.
Answer: tracemalloc, memray, scalene.
For this question, tracemalloc, memray, scalene. is correct. Find allocation hotspots. It aligns directly with what the question asks about what is the primary purpose of memory profiling. Competing choices sound plausible, but they miss the key condition.
Q55. Which statement about memory profiling is most accurate?
Select an answer to check.
Answer: tracemalloc, memray, scalene.
tracemalloc, memray, scalene. is the correct answer here. Find allocation hotspots. It aligns directly with what the question asks about which statement about memory profiling is most accurate. Competing choices sound plausible, but they miss the key condition.
Q56. How is memory profiling best characterized?
Select an answer to check.
Answer: tracemalloc, memray, scalene.
Here, tracemalloc, memray, scalene. is the right choice. Find allocation hotspots. This matches the core idea being tested around how is memory profiling best characterized. Competing choices sound plausible, but they miss the key condition.
Q57. Which option best describes pandas dtypes in Python?
Select an answer to check.
Answer: Use float32/int8/categorical to save memory.
In this case, Use float32/int8/categorical to save memory. is correct. Big savings on large frames. This matches the core idea being tested around which option best describes pandas dtypes in python. Competing choices sound plausible, but they miss the key condition.
Q58. What is the primary purpose of pandas dtypes?
Select an answer to check.
Answer: Use float32/int8/categorical to save memory.
The best option here is Use float32/int8/categorical to save memory.. Big savings on large frames. This matches the core idea being tested around what is the primary purpose of pandas dtypes. Competing choices sound plausible, but they miss the key condition.
Q59. Which statement about pandas dtypes is most accurate?
Select an answer to check.
Answer: Use float32/int8/categorical to save memory.
For this question, Use float32/int8/categorical to save memory. is correct. Big savings on large frames. This matches the core idea being tested around which statement about pandas dtypes is most accurate. Competing choices sound plausible, but they miss the key condition.
Q60. How is pandas dtypes best characterized?
Select an answer to check.
Answer: Use float32/int8/categorical to save memory.
Use float32/int8/categorical to save memory. is the correct answer here. Big savings on large frames. This matches the core idea being tested around how is pandas dtypes best characterized. Competing choices sound plausible, but they miss the key condition.
Q61. Which option best describes category dtype in Python?
Select an answer to check.
Answer: Stores repeated strings as categorical codes.
Here, Stores repeated strings as categorical codes. is the right choice. Memory + speed gains. That is exactly the concept behind which option best describes category dtype in python in this context. Competing choices sound plausible, but they miss the key condition.
Q62. What is the primary purpose of category dtype?
Select an answer to check.
Answer: Stores repeated strings as categorical codes.
In this case, Stores repeated strings as categorical codes. is correct. Memory + speed gains. That is exactly the concept behind what is the primary purpose of category dtype in this context. Competing choices sound plausible, but they miss the key condition.
Q63. Which statement about category dtype is most accurate?
Select an answer to check.
Answer: Stores repeated strings as categorical codes.
The best option here is Stores repeated strings as categorical codes.. Memory + speed gains. That is exactly the concept behind which statement about category dtype is most accurate in this context. Competing choices sound plausible, but they miss the key condition.
Q64. How is category dtype best characterized?
Select an answer to check.
Answer: Stores repeated strings as categorical codes.
For this question, Stores repeated strings as categorical codes. is correct. Memory + speed gains. That is exactly the concept behind how is category dtype best characterized in this context. Competing choices sound plausible, but they miss the key condition.
Q65. Which option best describes pyarrow-backed pandas in Python?
Select an answer to check.
Answer: Arrow-based dtypes via pandas.
Arrow-based dtypes via pandas. is the correct answer here. More efficient strings/null. That is exactly the concept behind which option best describes pyarrow-backed pandas in python in this context. Competing choices sound plausible, but they miss the key condition.
Q66. What is the primary purpose of pyarrow-backed pandas?
Select an answer to check.
Answer: Arrow-based dtypes via pandas.
Here, Arrow-based dtypes via pandas. is the right choice. More efficient strings/null. It fits the requirement in the prompt about what is the primary purpose of pyarrow-backed pandas. Competing choices sound plausible, but they miss the key condition.
Q67. Which statement about pyarrow-backed pandas is most accurate?
Select an answer to check.
Answer: Arrow-based dtypes via pandas.
In this case, Arrow-based dtypes via pandas. is correct. More efficient strings/null. It fits the requirement in the prompt about which statement about pyarrow-backed pandas is most accurate. Competing choices sound plausible, but they miss the key condition.
Q68. How is pyarrow-backed pandas best characterized?
Select an answer to check.
Answer: Arrow-based dtypes via pandas.
The best option here is Arrow-based dtypes via pandas.. More efficient strings/null. It fits the requirement in the prompt about how is pyarrow-backed pandas best characterized. Competing choices sound plausible, but they miss the key condition.
Q69. Which option best describes chunked CSV reading in Python?
Select an answer to check.
Answer: read_csv(chunksize=...) for streaming.
For this question, read_csv(chunksize=...) for streaming. is correct. Process in pieces. It fits the requirement in the prompt about which option best describes chunked csv reading in. Competing choices sound plausible, but they miss the key condition.
Q70. What is the primary purpose of chunked CSV reading?
Select an answer to check.
Answer: read_csv(chunksize=...) for streaming.
read_csv(chunksize=...) for streaming. is the correct answer here. Process in pieces. It fits the requirement in the prompt about what is the primary purpose of chunked csv. Competing choices sound plausible, but they miss the key condition.
Q71. Which statement about chunked CSV reading is most accurate?
Select an answer to check.
Answer: read_csv(chunksize=...) for streaming.
Here, read_csv(chunksize=...) for streaming. is the right choice. Process in pieces. This is the most accurate statement for which statement about chunked csv reading is most. Competing choices sound plausible, but they miss the key condition.
Q72. How is chunked CSV reading best characterized?
Select an answer to check.
Answer: read_csv(chunksize=...) for streaming.
In this case, read_csv(chunksize=...) for streaming. is correct. Process in pieces. This is the most accurate statement for how is chunked csv reading best characterized. Competing choices sound plausible, but they miss the key condition.
Q73. Which option best describes Dask out-of-core in Python?
Select an answer to check.
Answer: Spill partitions to disk as needed.
The best option here is Spill partitions to disk as needed.. Bigger-than-memory ops. This is the most accurate statement for which option best describes dask out-of-core in python. Competing choices sound plausible, but they miss the key condition.
Q74. What is the primary purpose of Dask out-of-core?
Select an answer to check.
Answer: Spill partitions to disk as needed.
For this question, Spill partitions to disk as needed. is correct. Bigger-than-memory ops. This is the most accurate statement for what is the primary purpose of dask out-of-core. Competing choices sound plausible, but they miss the key condition.
Q75. Which statement about Dask out-of-core is most accurate?
Select an answer to check.
Answer: Spill partitions to disk as needed.
Spill partitions to disk as needed. is the correct answer here. Bigger-than-memory ops. This is the most accurate statement for which statement about dask out-of-core is most accurate. Competing choices sound plausible, but they miss the key condition.
Q76. How is Dask out-of-core best characterized?
Select an answer to check.
Answer: Spill partitions to disk as needed.
Here, Spill partitions to disk as needed. is the right choice. Bigger-than-memory ops. It aligns directly with what the question asks about how is dask out-of-core best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q77. Which option best describes Polars lazy in Python?
Select an answer to check.
Answer: Plan + execute with optimizations.
In this case, Plan + execute with optimizations. is correct. Streaming and optimization. It aligns directly with what the question asks about which option best describes polars lazy in python. The remaining choices fail because they don’t satisfy the full definition.
Q78. What is the primary purpose of Polars lazy?
Select an answer to check.
Answer: Plan + execute with optimizations.
The best option here is Plan + execute with optimizations.. Streaming and optimization. It aligns directly with what the question asks about what is the primary purpose of polars lazy. The remaining choices fail because they don’t satisfy the full definition.
Q79. Which statement about Polars lazy is most accurate?
Select an answer to check.
Answer: Plan + execute with optimizations.
For this question, Plan + execute with optimizations. is correct. Streaming and optimization. It aligns directly with what the question asks about which statement about polars lazy is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q80. How is Polars lazy best characterized?
Select an answer to check.
Answer: Plan + execute with optimizations.
Plan + execute with optimizations. is the correct answer here. Streaming and optimization. It aligns directly with what the question asks about how is polars lazy best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q81. Which option best describes avoiding copy in Python?
Select an answer to check.
Answer: Use views/inplace where safe.
Here, Use views/inplace where safe. is the right choice. Beware aliasing bugs. This matches the core idea being tested around which option best describes avoiding copy in python. The remaining choices fail because they don’t satisfy the full definition.
Q82. What is the primary purpose of avoiding copy?
Select an answer to check.
Answer: Use views/inplace where safe.
In this case, Use views/inplace where safe. is correct. Beware aliasing bugs. This matches the core idea being tested around what is the primary purpose of avoiding copy. The remaining choices fail because they don’t satisfy the full definition.
Q83. Which statement about avoiding copy is most accurate?
Select an answer to check.
Answer: Use views/inplace where safe.
The best option here is Use views/inplace where safe.. Beware aliasing bugs. This matches the core idea being tested around which statement about avoiding copy is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q84. How is avoiding copy best characterized?
Select an answer to check.
Answer: Use views/inplace where safe.
For this question, Use views/inplace where safe. is correct. Beware aliasing bugs. This matches the core idea being tested around how is avoiding copy best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q85. Which option best describes __post_init__ in dataclasses in Python?
Select an answer to check.
Answer: Init after dataclass __init__ runs.
Init after dataclass __init__ runs. is the correct answer here. Compute derived fields. This matches the core idea being tested around which option best describes __post_init__ in dataclasses in. The remaining choices fail because they don’t satisfy the full definition.
Q86. What is the primary purpose of __post_init__ in dataclasses?
Select an answer to check.
Answer: Init after dataclass __init__ runs.
Here, Init after dataclass __init__ runs. is the right choice. Compute derived fields. That is exactly the concept behind what is the primary purpose of __post_init__ in in this context. The remaining choices fail because they don’t satisfy the full definition.
Q87. Which statement about __post_init__ in dataclasses is most accurate?
Select an answer to check.
Answer: Init after dataclass __init__ runs.
In this case, Init after dataclass __init__ runs. is correct. Compute derived fields. That is exactly the concept behind which statement about __post_init__ in dataclasses is most in this context. The remaining choices fail because they don’t satisfy the full definition.
Q88. How is __post_init__ in dataclasses best characterized?
Select an answer to check.
Answer: Init after dataclass __init__ runs.
The best option here is Init after dataclass __init__ runs.. Compute derived fields. That is exactly the concept behind how is __post_init__ in dataclasses best characterized in this context. The remaining choices fail because they don’t satisfy the full definition.
Q89. Which option best describes frozen dataclasses in Python?
Select an answer to check.
Answer: Immutable for safer caching/hashing.
For this question, Immutable for safer caching/hashing. is correct. Hashable instances. That is exactly the concept behind which option best describes frozen dataclasses in python in this context. The remaining choices fail because they don’t satisfy the full definition.
Q90. What is the primary purpose of frozen dataclasses?
Select an answer to check.
Answer: Immutable for safer caching/hashing.
Immutable for safer caching/hashing. is the correct answer here. Hashable instances. That is exactly the concept behind what is the primary purpose of frozen dataclasses in this context. The remaining choices fail because they don’t satisfy the full definition.
Q91. Which statement about frozen dataclasses is most accurate?
Select an answer to check.
Answer: Immutable for safer caching/hashing.
Here, Immutable for safer caching/hashing. is the right choice. Hashable instances. It fits the requirement in the prompt about which statement about frozen dataclasses is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q92. How is frozen dataclasses best characterized?
Select an answer to check.
Answer: Immutable for safer caching/hashing.
In this case, Immutable for safer caching/hashing. is correct. Hashable instances. It fits the requirement in the prompt about how is frozen dataclasses best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q93. Which option best describes avoiding global state in Python?
Select an answer to check.
Answer: Reduce retention via globals.
The best option here is Reduce retention via globals.. Helps GC reclaim memory. It fits the requirement in the prompt about which option best describes avoiding global state in. The remaining choices fail because they don’t satisfy the full definition.
Q94. What is the primary purpose of avoiding global state?
Select an answer to check.
Answer: Reduce retention via globals.
For this question, Reduce retention via globals. is correct. Helps GC reclaim memory. It fits the requirement in the prompt about what is the primary purpose of avoiding global. The remaining choices fail because they don’t satisfy the full definition.
Q95. Which statement about avoiding global state is most accurate?
Select an answer to check.
Answer: Reduce retention via globals.
Reduce retention via globals. is the correct answer here. Helps GC reclaim memory. It fits the requirement in the prompt about which statement about avoiding global state is most. The remaining choices fail because they don’t satisfy the full definition.
Q96. How is avoiding global state best characterized?
Select an answer to check.
Answer: Reduce retention via globals.
Here, Reduce retention via globals. is the right choice. Helps GC reclaim memory. This is the most accurate statement for how is avoiding global state best characterized. The remaining choices fail because they don’t satisfy the full definition.
Q97. Which option best describes releasing references in Python?
Select an answer to check.
Answer: Explicit del/None in long-running loops.
In this case, Explicit del/None in long-running loops. is correct. Drops refs to large objects. This is the most accurate statement for which option best describes releasing references in python. The remaining choices fail because they don’t satisfy the full definition.
Q98. What is the primary purpose of releasing references?
Select an answer to check.
Answer: Explicit del/None in long-running loops.
The best option here is Explicit del/None in long-running loops.. Drops refs to large objects. This is the most accurate statement for what is the primary purpose of releasing references. The remaining choices fail because they don’t satisfy the full definition.
Q99. Which statement about releasing references is most accurate?
Select an answer to check.
Answer: Explicit del/None in long-running loops.
For this question, Explicit del/None in long-running loops. is correct. Drops refs to large objects. This is the most accurate statement for which statement about releasing references is most accurate. The remaining choices fail because they don’t satisfy the full definition.
Q100. How is releasing references best characterized?
Select an answer to check.
Answer: Explicit del/None in long-running loops.
Explicit del/None in long-running loops. is the correct answer here. Drops refs to large objects. This is the most accurate statement for how is releasing references best characterized. The remaining choices fail because they don’t satisfy the full definition.