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ds-service: Yet Another Data Structure Server

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ds-service is a small, in-memory data structure server that is accessible via gRPC.

ds-service runs a single server process that holds shared state in memory and lets many distributed clients and workers coordinate using it.

Presently, it provides six data structures:

  • A key-value store -- a shared string -> bytes store for passing data between processes.
  • A task queue -- a priority-based work queue that distributes tasks to workers and tracks their state.
  • A journal store -- append-only, ordered logs of binary entries.
  • A time series store -- append-only series of timestamped floating-point values.
  • Named mutexes -- worker-owned locks for coordinating exclusive resource access across workers.
  • Counters -- named monotonic counters that hand out successive integers.

Each of these is a separate key space with its own set of RPCs.

Architecture

  • Server (cpp/ds-service.cpp) -- a C++23 gRPC service. All state lives in memory, with a separate lock guarding each top-level data structure. Operations on one structure are serialized, while operations on different structures may run concurrently. Each RPC touches a single structure, so no request ever holds more than one lock. State is not persisted; that is, when the server stops all data is lost.
  • Client (python/ds_service_client/) -- a Python 3.12+ client library that wraps the generated gRPC stubs and translates gRPC status codes into Python exceptions (KeyError, ValueError, TimeoutError, the task-queue-specific NoTaskAvailable and TaskStateError, and MutexNotHeld).
  • Interface (misc/ds-service.proto) -- the protobuf/gRPC contract shared by both sides.

Additional Information

Document What it covers
Data structure reference Every RPC, its arguments and error statuses, and the exact semantics of each data structure.
How to build the server Requirements, the Conan + CMake build, installing, running, and the static musl build.
How to use the Python client Installing, connecting, the gRPC-status-to-exception mapping, and usage examples.
How to run the tests The pytest integration suite, pointing it at the binary, and what the fixtures provide.
Developer notes Working on ds-service itself: the generated code workflow, the conventions a change is checked against, versioning, and known limitations.

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