The ICP community has released version 2.2.1 of icp-py-core, the Python agent library that allows developers to interact with Internet Computer canisters. The update introduces multiple improvements designed to make development smoother, faster, and more secure.
The new release adds HTTP/2 support, enabling automatic multiplexing and lower latency for canister calls. Developers can expect quicker responses and more efficient network usage, particularly for applications handling multiple simultaneous requests. This improvement is expected to benefit both small projects and larger, more complex dApps relying on Python backends.
Error handling has been expanded with 11 structured error classes, allowing for more precise debugging and easier identification of issues during development. This makes it simpler for developers to isolate and fix problems, reducing downtime and improving overall application reliability.
The library now fully supports API v4 and v3, including sharded canister ranges and v4 call endpoints. This allows developers to interact with distributed canisters more efficiently, streamlining workflows for applications that require access to multiple canisters or sharded datasets.
Security has been strengthened with enhanced certificate and delegation verification, ensuring that applications built with icp-py-core maintain a high level of integrity and trust when communicating with canisters. These improvements help protect against potential attack vectors and give developers confidence in the safety of their applications.
The release highlights the role of the ICP community in maintaining and improving key development tools. Community contributions remain essential in keeping the library up to date and aligned with the evolving needs of developers building on the Internet Computer.
Developers using Python for ICP projects now have a more robust toolset, making it easier to build scalable, secure, and high-performance applications. The update reflects the broader trend of maturing developer infrastructure within the ICP ecosystem, supporting a growing range of use cases from experimentation to production-grade applications.
ICP enthusiasts and Python developers are encouraged to explore the new features, provide feedback, and contribute to the ongoing development of the library, ensuring that icp-py-core continues to meet the needs of the community.
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