Files
jgrusewski 5b9995c6f5 chore(services): drop unused declared deps (cargo-machete cleanup)
Remove dependencies declared in 5 service Cargo.toml files that no
source code in those services references (verified by grepping for
use statements). Reduces dep-graph fan-out and unnecessary recompiles.

  services/api/Cargo.toml             −16 deps  (async-trait, bytes,
                                                 const-oid, hdrhistogram,
                                                 hex, http-body, hyper,
                                                 hyper-util, num-traits,
                                                 rust_decimal, tokio-stream,
                                                 tower-layer, tower-service,
                                                 tracing-subscriber,
                                                 trading_engine, zeroize.
                                                 + json feature added to
                                                 reqwest since trading_engine
                                                 was enabling it transitively)
  services/trading_service/Cargo.toml −11 deps
  services/backtesting_service/Cargo.toml −17 deps
  services/trading_agent_service/Cargo.toml −6 deps
  services/ml_training_service/Cargo.toml −4 deps

False positives kept (cargo-machete misses these because they're only
referenced in tonic-generated proto code, not in hand-written src):
  - prost            (`::prost::Message` derive in build.rs-generated code)
  - tonic-prost      (`tonic_prost::ProstCodec::default()` in generated tonic
                     clients/servers)

cargo check --workspace passes.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 01:37:49 +02:00
..

ml_training_service

Model training orchestration and lifecycle management for DQN, PPO, TFT, Mamba2, TLOB, and Liquid models with progress tracking and artifact storage.

Key Types

  • MlTrainingServiceImpl -- main gRPC service
  • JobTracker -- training job state machine
  • CheckpointManager -- model artifact persistence

Features

  • minimal (default) -- minimal ML feature set for financial models
  • gpu -- SIMD GPU acceleration (requires CUDA)
  • mock-data -- mock training data (testing, bypasses database)

Configuration

  • GRPC_PORT -- gRPC listen port
  • DATABASE_URL -- PostgreSQL for job metadata and training history
  • Prometheus metrics on port 9094

Testing

SQLX_OFFLINE=true cargo test -p ml_training_service --lib