gRPC

Mentors: Student: Naresh Ramesh

<p>gRPC Python currently has a constellation of scripts written to build the project, but it has a lot of limitations in terms of speed and maintainability. Bazel is the open-sourced variant of Google's internal system, Blaze, which is an ideal replacement for building such projects in a fast and declarative fashion. But Bazel in itself is still in active development, especially in terms of Python (amongst a few others).</p> <p>This project aims to fill this gap and attempt to build gRPC Python with Bazel. Although filed under gRPC, this project also targets contribution to Bazel for Python.</p>

Mentors: Student: Thunderboltsid

<p>Python is, originally, a specification for a programming language. This specification has been implemented differently in different implementations of the <a href="https://docs.python.org/3/reference/" target="_blank">language specification</a>.</p> <p>A small, and by no means exhaustive, list of some major python implementations is:</p> <ul> <li><a href="https://www.python.org/" target="_blank">CPython</a>: The reference implementation</li> <li><a href="http://www.jython.org/" target="_blank">Jython</a>: Python implemented in Java</li> <li><a href="http://pythonnet.sourceforge.net/" target="_blank">Python for .NET</a>: CPython implementation that enables .NET library usage</li> <li><a href="http://ironpython.net/" target="_blank">IronPython</a>: Python implemented in .NET</li> <li><a href="http://pypy.org/" target="_blank">PyPy</a>: Python implemented completely in Python</li> <li><a href="https://bitbucket.org/stackless-dev/stackless/wiki/Home" target="_blank">Stackless</a>: Replaces the dependency for the C call stack with it's own stack</li> </ul> <p>The project intends to add support for latest CPython versions (3.4, 3.5, and 3.6) and latest PyPy version (5.3) to the GRPC Python library as well as pave way for supporting other Python variants down the line.</p>

Mentors: Student: stephensturdevant

<p>New serverless-computing platforms such as Google Cloud Functions, AWS Lambda, and OpenLambda provide RPC handling to cloud customers. The RPC handlers are inherently ephemeral; these services do not guarantee the persistence of state between invocations, so serverless-computing must be used in conjunction with a cloud database. We propose building an RPC-aware storage engine that runs alongside these serverless-computing platforms. There are several opportunities for tight integration: (1) client RPC calls introduce new, meaningful consistency boundaries; (2) RPC schedulers aware of database replicas can make better locality decisions; and (3) coordinating handler pausing with database change batches would improve performance. Our database will coordinate with handler workers via gRPC calls.</p>