Databricks-GenAI-Assoc Application Development Practice Question
A developer is creating a Databricks notebook to prototype a GenAI application. They need to install the `databricks-langchain` library to use LangChain integrations with Databricks. Which command should they use in the notebook?
⚠ Common exam trap
The trap here is using outdated installation methods like `dbutils.library.installPyPI` or shell commands, which are not recommended in current Databricks runtimes.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
%pip install databricks-langchain
In Databricks notebooks, the `%pip install` magic command is the recommended way to install Python libraries. It ensures the package is installed in the notebook's isolated environment and is immediately available for import. Using `%pip` with `databricks-langchain` correctly sets up the LangChain integrations needed for the GenAI application.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
%conda install databricks-langchain
Why it's wrong here
`%conda install` is used for Conda packages, but `databricks-langchain` is a PyPI package. While Conda can install PyPI packages sometimes, it is not the recommended method and may not resolve dependencies correctly. The `%pip` command is preferred in Databricks notebooks for Python packages.
- ✗
dbutils.library.installPyPI("databricks-langchain")
Why it's wrong here
`dbutils.library.installPyPI` is deprecated in newer Databricks runtimes. While it was used historically, it is not the current best practice. The `%pip` command is now recommended for installing Python packages in notebooks, providing better dependency management and isolation.
- ✗
!pip install databricks-langchain
Why it's wrong here
Using `!pip install` runs pip as a shell command, which can install the package but does not integrate with the notebook's environment management. It may lead to inconsistencies, especially in shared clusters. The `%pip` magic is designed for this purpose and ensures proper isolation.
- ✓
%pip install databricks-langchain
Why this is correct
The `%pip install` magic command is the standard way to install Python packages in Databricks notebooks. It ensures the package is installed in the notebook's environment and available for import. This is the correct command to install the `databricks-langchain` library, which provides LangChain integrations for Databricks.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-GenAI-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-GenAI-Assoc exam.