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Source channel @githubtrending · Post #15382 · Jan 1
#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples
Search: #modulefinder
@djangoproject · Post #154 · 09/04/2016, 12:14 PM
https://docs.python.org/2/library/modulefinder.html This #module provides a #ModuleFinder class that can be used to determine the set of modules imported by a script. modulefinder.py can also be run as a script, giving the filename of a Python script as its argument, after which a report of the imported modules will be printed.
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@djangoproject · Post #145 · 09/02/2016, 03:28 AM
https://docs.python.org/3/library/modulefinder.html This module provides a #ModuleFinder class that can be used to determine the set of #modules#imported by a #script. modulefinder.py can also be run as a script, giving the #filename of a Python script as its argument, after which a report of the imported modules will be printed.