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Answer: Include a requirements.txt file in the notebook directory and share the entire directory.
The most efficient and reliable approach is to include a requirements.txt file in the notebook directory and share the entire directory. This method specifies all necessary libraries and their versions, allowing the colleague to install them using `pip install -r requirements.txt`. This ensures a consistent and reproducible environment, minimizing setup and dependency issues. Other options either rely on the colleague having pre-installed libraries (which is impractical and error-prone), export the notebook without dependencies (requiring manual library installation), or use DBC files that embed dependencies within the notebook, making them large and difficult to manage.
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In a collaborative Databricks project, a data scientist wishes to share a notebook with a colleague, ensuring the notebook can be executed without any dependency issues. What is the most effective action the data scientist should take?
A
Share the notebook link and ensure that all libraries are pre-installed in the colleague's environment.
B
Include a requirements.txt file in the notebook directory and share the entire directory.
C
Export the notebook as a Databricks Archive (DBC) file.
D
Use the 'Export' feature in the notebook toolbar to create an HTML file.
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