This PCAP practice question tests your understanding of modules and packages. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A Python package 'analytics' contains a subpackage 'models' with module 'regression.py'. Inside 'regression.py', there is a function 'linear_fit' that depends on 'numpy'. The developer wants to ensure that 'numpy' is imported only once and available throughout the package. Where should the import 'import numpy as np' be placed?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
In the '__init__.py' of the 'analytics' top-level package.
Option C is correct because placing 'import numpy as np' in the '__init__.py' of the 'analytics' top-level package ensures that numpy is imported once when the package is first loaded, making it available to all subpackages and modules within the package. This leverages Python's module caching mechanism, where the import is executed only once and the module object is stored in sys.modules, preventing redundant imports and ensuring consistent access across the package.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
In the '__init__.py' of the 'models' subpackage.
Why it's wrong here
Then numpy is only accessible from models subpackage, not from other parts of analytics.
✗
In each module that uses numpy, add 'import numpy as np'.
Why it's wrong here
This works but repeats the import; no shared namespace across package.
✓
In the '__init__.py' of the 'analytics' top-level package.
Why this is correct
Makes numpy accessible as analytics.np and imported once.
Related concept
Read the scenario before looking for a memorised answer.
✗
In a separate file 'common_imports.py' and import that file everywhere.
Why it's wrong here
Unnecessary complexity; not standard.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Python Institute often tests the misconception that imports should be placed in the subpackage '__init__.py' or in each module individually, but the key is that the top-level '__init__.py' is executed once when the package is first imported, making it the correct location for package-wide shared imports.
Detailed technical explanation
How to think about this question
When Python imports a package, it executes the '__init__.py' file of that package, and any imports made there are stored in the package's namespace, making them accessible as attributes of the package (e.g., analytics.np). This is a common pattern for providing shared dependencies, and it relies on Python's module caching in sys.modules to ensure the import runs only once, even if the package is imported multiple times. In real-world scenarios, this approach is used in large projects like NumPy itself, where core dependencies are imported in the top-level '__init__.py' to streamline access and avoid scattered imports.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Modules and Packages — This question tests Modules and Packages — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: In the '__init__.py' of the 'analytics' top-level package. — Option C is correct because placing 'import numpy as np' in the '__init__.py' of the 'analytics' top-level package ensures that numpy is imported once when the package is first loaded, making it available to all subpackages and modules within the package. This leverages Python's module caching mechanism, where the import is executed only once and the module object is stored in sys.modules, preventing redundant imports and ensuring consistent access across the package.
What should I do if I get this PCAP question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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