---
title: "How can I keep DeepSeek's Python suggestions within our existing dependencies?"  
description: "How can I keep DeepSeek's Python suggestions within our existing dependencies?"  
author: "Kacper Jankowski"  
published: 2026-10-18  
updated: 2026-10-18  
canonical: https://www.mindstick.com/forum/162585/how-can-i-keep-deepseek-s-python-suggestions-within-our-existing-dependencies  
category: "AI-Assisted Python Development"  
tags: ["DeepSeek", "python", "Dependency Management"]  
reading_time: 1 minute  

---

# How can I keep DeepSeek's Python suggestions within our existing dependencies?

I'm asking DeepSeek to help with a Python service that has a locked dependency set. Some suggestions import packages we don't use; others reference methods that aren't available in our installed versions. The code can look reasonable until someone tries to run it.

Adding a package requires a separate review, so “install this library” isn't an acceptable default.

1. Would you provide the full lockfile, or a shorter list of direct dependencies and their versions?
2. For version-sensitive APIs, is a small extract from the installed package's documentation more useful than naming the version alone?
3. How would you check for new imports without rejecting valid Python standard-library modules or our own internal packages?

I'm looking for a lightweight workflow for **validating AI-generated Python dependencies**, not just stronger prompt wording. We can run proposed changes in a disposable environment with no network access, but I'd like to catch obvious dependency problems before running the test suite.


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Original Source: https://www.mindstick.com/forum/162585/how-can-i-keep-deepseek-s-python-suggestions-within-our-existing-dependencies

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