Tianyi Cui
f0f9b294dd
Document dsh as the only application launcher across architecture, CLI, SDK, app-boot, Python package, contributor, tutorial, and example references. Explain explicit home selection, profile and patch precedence, persistent external plugin installation, the Node-free runtime path, and the absence of complete-config or ~/.dsh fallbacks. Record the Python profile-runtime decision and update the active naming, installed-wheel, and SEA packaging notes with precise supersession. Regenerate the configuration catalog and module graph after deleting the carrier, update both reviewed languages and pairing records, and classify the retained standalone Cordis files as lower-level test fixtures rather than launch interfaces.
3.8 KiB
deepseek-harness-runtime-bin
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Platform runtime wheel for the DeepSeek Harness Python SDK. It packages the normal dsh CLI and its closed Node dependency tree into a native executable, so SDK use requires no system Node.js. This package publishes wheels only.
Installed commands and artifacts
The wheel installs a dsh console command and the deepseek_harness_runtime Python module. dsh forwards its arguments to the bundled executable and requires a non-empty DSH_HOME; it never falls back to ~/.dsh.
Production executables are named deepseek-harness-sdk-runtime-<platform>-<arch> under the module's runtime/ directory. Linux and macOS wheels include a target-native -rg sidecar; macOS also includes -spawn-helper for node-pty. Published targets are Linux x64, Linux arm64, and macOS arm64. The wheel tag and payload must match exactly.
Repository builds also materialize a dev-only runtime/node/ carrier. It runs node runtime/node/node_modules/@deepseek-ai/dsh/lib/bin.js on system Node 22.19 or newer. It is never selected automatically and is excluded from wheels and sdists.
Both carriers execute the same dsh grammar and profiles. The private dsh-python-runtime-closure manifest defines the packaged dependency closure; there is no Python-specific Node application or checked-in default cordis.yml.
Python module API
bundled_package_dir() -> Pathreturns the installed module-data root and verifies its release metadata.bundled_runtime_path() -> Pathreturns the current platform executable and verifies required sidecars.resolve_bundled_launch_args(mode=None) -> tuple[str, ...]returns the executable argv by default. Explicitmode="node"orDSH_RUNTIME_MODE=nodeselects the repo-only Node carrier.main()implements the installeddshconsole command and rejects an absent or blankDSH_HOMEbefore replacing the Python process.
Unsupported platforms and missing executables or sidecars raise FileNotFoundError with the build and installation routes. Unknown runtime modes raise ValueError.
Packaged profile resolution
dsh initializes shipped profiles under the explicit home, composes their bundle patches, and loads bundled plugins from the executable's virtual filesystem. Because operating-system symlinks cannot enter that filesystem, packaged launches maintain small real ESM proxy packages under $DSH_HOME/profiles/node_modules. Each proxy mirrors explicit runtime exports, records the original package identity, and re-exports the virtual module URL. Built-in rows and external plugin peers therefore share one Cordis/module instance. Native shared libraries are packaged with native addons, while ripgrep and the macOS PTY helper remain executable sidecars.
External profile management uses dsh plugin --profile <name> .... That command requires pnpm on PATH; ordinary SDK/profile execution does not.
Build and distribution
From the repository root, pnpm exec tsx scripts/build-exe-for-python-sdk.ts verifies the closure, builds packages, deploys a symlink-free tree, packages the selected target, and syncs the executable and sidecars into this module. scripts/build-python-release.py stages release-shaped wheels at the root repository version and pins deepseek-harness-sdk to the exact runtime version.
The installed-wheel smoke creates a clean virtual environment outside the checkout, proves distribution and executable provenance, then exercises default and customized SDK profiles, external plugins, MCP, native tools, direct JSON-RPC, committed snapshots, and the real provider on trusted runs. See the Python contributor workflow and installed-wheel testing decision.