protoplasm 5.3.0

Utilities for working with Protobuf & gRPC in Python.

Protoplasm

Utilities for working with Protobuf & gRPC in Python, e.g; compiling Python 3 Dataclasses from compiled proto-message-python code and casting between the two, quickly initializing large/nested Protobuf object, simplifying gRPC service interfaces etc.

IMPORTANT

Update this README file after moving from CCP's internal code repo to Github.

Protoplasm 4

• Unify the unary functionality of Protoplasm 2 with the streaming functionality of Protoplasm 3
  • The two turn out to be completely incompatible and API shattering
  • Protoplasm 4 must incorporate BOTH functionalities wile being backwards compatible enough for both Protoplasm 2 and 3 projects to be able to migrate to 4
  • The key here is detecting the stream keyword in protos that denote streaming input and/or output
• Add piled up functionality/utility/QoL improvements/bugs that's been on The List™ for a while
  • Cast to/from base64 encoded strings
  • Utilize the __all__ directive to isolate import * side effects
  • Integrate the Neobuf Builder CLI (from various other projects) into Protoplasm and generalize it
  • Address the "None is default value" issue
  • Explore the pros/cons of making non-existing Message/Object attributes return Empty or EmptyDict to simplify nested attribute fetching...?
• Refactor and restructure the package properly
  • Separate the 4 main roles of the package logically
    1. Cross-piling *.proto to *_pb2.py and *_pb2_grpc.py
    2. Cross-piling *_pb2.py to *_dc.py Neobuf Dataclasses
    3. Generating *_api.py interfaces
    4. Generating gRPC implementation of Services

Troubleshooting

• I get TypeError: Plain typing.NoReturn is not valid as type argument
  • Upgrade to Python 3.9. This TypeError arises from a bug in Python 3.7

Clever bits to document...

• Code Generation (e.g. foo.proto) + how to build
  • Dataclasses -> foo_dc.py + how to use (+ DataclassBase freebies)
    • Extending Dataclasses (a no-no for pb2 files apparently)
  • Service API -> foo_api.py + how to use and implement
    • Automatic parameter unpacking
    • Return value packing
    • Raising protoplasm.errors.api.* on errors or non-ok returns
    • Using protoplasm.decorators for param and type checking
    • The takes_context decorator and how to use it
  • GRPC DC Service Servicer -> foo_dc_grpc.py + how to use
• Utilities
  • Proto <-> dict <-> Dataclass casters
  • The mkproto and mkdataclass helpers
  • The unpack_dataclass_request and pack_dataclass_response helpers