SDK Overview

hydra-sdk is the umbrella crate for Hydra’s public API. Add it to your Cargo.toml:

[dependencies]
hydra-sdk = "6"

It re-exports every type needed to parse networks, run simulations, query results, run post-simulation analytics, and generate reports — with all internal dependency versions pre-pinned.

Modules and Key Types

Session API

The primary entry point. Import Simulation to parse, run, and query a network.

Type / function	Purpose
`Simulation`	Creates and drives a simulation session
`SessionError`	Error type returned by all session methods
`SimWarning` / `WarningKind`	Non-fatal diagnostics produced during a run
`NodeQuantity`	Enum of per-node result variables (Head, GaugePressure, Demand, Quality)
`LinkQuantity`	Enum of per-link result variables (Flow, MeanVelocity, UnitHeadLoss, FrictionFactor, Quality, Status, Setting)
`NodeResult` / `LinkResult`	Batch result containers
`ResultRanges`	Min/max envelopes across all nodes/links/time
`HydSnapshot`	Single-step hydraulic state snapshot
`PumpEnergy`	Per-pump energy and efficiency metrics
`FlowBalance` / `MassBalance`	Network-wide accounting at simulation end
`WritableSimulation`	Trait required by the I/O writers

Analytics

Post-simulation analysis functions that operate on a saved .out file.

Type / function	Purpose
`compute_demand_reliability_from_out`	Per-junction demand reliability metrics
`compute_service_compliance_from_out`	Per-node pressure compliance metrics
`DemandReliabilityReport` / `DemandReliabilitySummary`	Demand reliability results
`ServiceComplianceReport` / `ServiceComplianceSummary`	Pressure compliance results
`DemandReliabilityNode` / `ServiceComplianceNode`	Per-node entries within each report’s `nodes` list
`DemandReliabilityOptions`	Options for reliability computation (deficit tolerance)
`compute_demand_reliability_from_out_with_options`	Reliability variant taking explicit `DemandReliabilityOptions`
`ServiceComplianceThresholds`	Min/max pressure thresholds for compliance check

Data Model

The full network data model, mirroring the EPANET .inp structure.

Type	Purpose
`Network`	Top-level container returned by `io::parse`
`Node` / `NodeKind`	Polymorphic node (Junction, Reservoir, Tank)
`Link` / `LinkKind`	Polymorphic link (Pipe, Pump, Valve)
`Pattern` / `Curve`	Time patterns and XY curves
`SimulationOptions`	All `[OPTIONS]` and `[TIMES]` settings
`QualityMode`	Chemical, age, or source-trace quality mode
`FlowUnits` / `HeadLossFormula`	Unit system and head-loss formula enums
`ValidationError`	Structural network validation errors

I/O

#![allow(unused)]
fn main() {
use hydra_sdk::io;
}

Function / module	Purpose
`io::parse(&bytes)`	Parse EPANET `.inp` bytes into a `Network`, failing if the result would not be simulable. Match `io::ReadError::ForeignDialect` separately: it means the bytes are another engine’s model, not a bad file — see Foreign `.inp` dialects
`io::parse_tolerant(&bytes)`	Parse and return the `Network` with its validation errors instead of failing — for editors and inspectors that must show an invalid model. A non-empty error list means it must not be simulated
`io::write_inp(&network)`	Serialise a `Network` back to `.inp` bytes
`io::rpt_writer::build_text_report(&sim)`	Build a plain-text `.rpt` report string
`io::rpt_writer::build_json_report(&sim)`	Build a JSON report string
`io::out_writer::write_binary_output(&mut w, &sim, input_file, report_file, units)`	Write EPANET-compatible `.out` binary
`io::out_reader`	Read and inspect existing `.out` files
`io::compute_network_digest`	Stable content digest of a `Network` (also re-exported at the crate root)

Engine Identity

#![allow(unused)]
fn main() {
use hydra_sdk::common;
}

Every Hydra engine publishes an immutable descriptor. Applications resolve a project’s stored engine key against the registry rather than hardcoding names, colours, or file filters. See Engines for the current roster and what Planned means in practice.

Type / function	Purpose
`common::ENGINES`	Every engine compiled into this distribution, in presentation order
`common::engine_by_key(key)`	Resolve a key to its descriptor, or an `UnknownEngineError`
`common::EngineDescriptor`	`key`, `label`, `pill`, `accent`, `summary`, `status`, `import`
`common::EngineStatus`	`Available` or `Planned` — a planned engine is registered but has no implementation
`common::ImportFormat`	A source-model format the engine reads: `label` plus `extensions`

import is a file-picker filter, never a validity test — wds and uds both claim .inp with incompatible contents, so only the owning engine’s parser can decide whether a file really is its model.

Reports

#![allow(unused)]
fn main() {
use hydra_sdk::{report, report_catalog, produce_report_block};
}

Report generation is split in two: the engine produces neutral content fragments, and report turns them into documents. The report layer knows nothing about engines.

Type / function	Purpose
`report_catalog()`	The engine’s block catalog — queryable without running a simulation
`report_block_options(id, network)`	The options a given block accepts, with labels, defaults, and bounds — enough to build an editor without hardcoding them. Advisory: an unknown id or a block with nothing to configure yields an empty list rather than an error
`produce_report_block(id, out_path, network, options)`	Materialise one block for a completed run
`report::ReportTemplate`	An ordered list of block references plus a document title (JSON)
`report::assemble(template, catalog, context, produce)`	Pair a template with a producer to build a render-ready document
`report::render_txt` / `render_csv` / `render_html`	Deterministic renderers — identical inputs give byte-identical output
`report::render_pdf`	Typeset PDF; behind hydra-sdk’s `report-pdf` feature, and the only renderer that can fail (`PdfError`)
`common::BlockDescriptor` / `Fragment`	The catalog entry and produced-content types the two halves exchange

Also re-exported

Beyond the tables above, hydra-sdk re-exports several supporting items:

Version constants — HYDRA_VERSION and the per-subsystem HYDRA_*_VERSION strings.
Runtime estimation — estimate_simulation_runtime, estimate_simulation_runtime_from_summary, and RuntimeEstimate. The millisecond-level forms estimate_simulation_runtime_millis_from_summary and classify_simulation_runtime_millis are also available when you want the raw prediction or the bucketing separately.
Threshold binning — threshold_bands(values, edges) counts values into the bands defined by ascending edges, with the outer two unbounded so nothing is dropped. It is the same binning the wds.*-thresholds report blocks use, so an interface presenting that view counts identically.
Threshold binning — threshold_bands, the shared band-counting used by the *-thresholds report blocks, so an interface presenting the same view counts identically.

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