HelixDB Docs

Find Weighted Shortest Paths with Dijkstra’s Algorithm

ShortestPathDijkstras finds the optimal shortest path in weighted graphs using Dijkstra’s algorithm. It supports sophisticated weight calculations that can reference edge properties, source node properties, and destination node properties, making it incredibly flexible for real-world routing scenarios.

::ShortestPathDijkstras<EdgeType>(weight_expression)
::To(target_id)

When using the SDKs or curling the endpoint, the query name must match what is defined in the queries.hx file exactly.

How It Works

Dijkstra’s algorithm:

Starts at the source node with distance 0
Explores neighbors, calculating cumulative path weights
Always processes the node with the smallest known distance next
Guarantees finding the optimal shortest path for non-negative weights

All weights must be non-negative. Negative weights can produce incorrect results or infinite loops.

When to Use ShortestPathDijkstras

Use Dijkstra when you need:

Weighted paths: Edges have different costs (distance, time, bandwidth)
Custom calculations: Combine multiple properties into path weights
Multi-factor routing: Consider traffic, reliability, cost simultaneously
Property-based weights: Use node or edge properties in calculations
Flexibility: Maximum control over what defines “shortest”

Weight Expressions

Weight expressions can reference:

_::{property} - Edge property
_::FromN::{property} - Source node property
_::ToN::{property} - Destination node property
Mathematical functions: ADD, MUL, DIV, SUB, POW, SQRT, etc.

Example 1: Simple property-based weight

QUERY FindShortestRoute(start_id: ID, end_id: ID) =>
    result <- N<City>(start_id)
        ::ShortestPathDijkstras<Road>(_::{distance})
        ::To(end_id)
    RETURN result

QUERY CreateCity(name: String, population: I64) =>
    city <- AddN<City>({ name: name, population: population })
    RETURN city

QUERY CreateRoad(from_id: ID, to_id: ID, distance: F64, traffic_level: F64) =>
    road <- AddE<Road>({ distance: distance, traffic_level: traffic_level })::From(from_id)::To(to_id)
    RETURN road

N::City {
    name: String,
    population: I64
}

E::Road {
    From: City,
    To: City,
    Properties: {
        distance: F64,
        traffic_level: F64
    }
}

Here’s how to run the query using the SDKs or curl

from helix.client import Client

client = Client(local=True, port=6969)

# Create cities
cities = {}
city_data = [
    ("Los Angeles", 4000000),
    ("San Diego", 1400000),
    ("Phoenix", 1600000),
    ("Las Vegas", 650000),
]

for name, population in city_data:
    result = client.query("CreateCity", {"name": name, "population": population})
    cities[name] = result["city"]["id"]

# Create road network with distances
roads = [
    ("Los Angeles", "San Diego", 120.0, 0.7),
    ("Los Angeles", "Las Vegas", 270.0, 0.5),
    ("San Diego", "Phoenix", 355.0, 0.4),
    ("Las Vegas", "Phoenix", 297.0, 0.6),
]

for from_city, to_city, distance, traffic in roads:
    client.query("CreateRoad", {
        "from_id": cities[from_city],
        "to_id": cities[to_city],
        "distance": distance,
        "traffic_level": traffic
    })

# Find shortest route by distance
result = client.query("FindShortestRoute", {
    "start_id": cities["Los Angeles"],
    "end_id": cities["Phoenix"]
})

print(f"Shortest route from LA to Phoenix:")
print(f"Path: {' -> '.join([node['name'] for node in result['result']['path']])}")
print(f"Total distance: {result['result']['total_weight']:.1f} miles")
print(f"Hops: {result['result']['hop_count']}")

use helix_rs::{HelixDB, HelixDBClient};
use serde_json::json;
use std::collections::HashMap;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = HelixDB::new(Some("http://localhost"), Some(6969), None);

    // Create cities
    let mut cities: HashMap<String, String> = HashMap::new();
    let city_data = vec![
        ("Los Angeles", 4000000),
        ("San Diego", 1400000),
        ("Phoenix", 1600000),
        ("Las Vegas", 650000),
    ];

    for (name, population) in &city_data {
        let result: serde_json::Value = client.query("CreateCity", &json!({
            "name": name,
            "population": population,
        })).await?;
        cities.insert(name.to_string(), result["city"]["id"].as_str().unwrap().to_string());
    }

    // Create road network with distances
    let roads = vec![
        ("Los Angeles", "San Diego", 120.0, 0.7),
        ("Los Angeles", "Las Vegas", 270.0, 0.5),
        ("San Diego", "Phoenix", 355.0, 0.4),
        ("Las Vegas", "Phoenix", 297.0, 0.6),
    ];

    for (from_city, to_city, distance, traffic) in &roads {
        let _road: serde_json::Value = client.query("CreateRoad", &json!({
            "from_id": cities[*from_city],
            "to_id": cities[*to_city],
            "distance": distance,
            "traffic_level": traffic,
        })).await?;
    }

    // Find shortest route by distance
    let result: serde_json::Value = client.query("FindShortestRoute", &json!({
        "start_id": cities["Los Angeles"],
        "end_id": cities["Phoenix"],
    })).await?;

    println!("Shortest route from LA to Phoenix: {result:#?}");

    Ok(())
}

package main

import (
    "fmt"
    "log"

    "github.com/HelixDB/helix-go"
)

func main() {
    client := helix.NewClient("http://localhost:6969")

    // Create cities
    cities := make(map[string]string)
    cityData := []struct {
        name       string
        population int64
    }{
        {"Los Angeles", 4000000},
        {"San Diego", 1400000},
        {"Phoenix", 1600000},
        {"Las Vegas", 650000},
    }

    for _, city := range cityData {
        var result map[string]any
        if err := client.Query("CreateCity", helix.WithData(map[string]any{
            "name":       city.name,
            "population": city.population,
        })).Scan(&result); err != nil {
            log.Fatalf("CreateCity failed: %s", err)
        }
        cities[city.name] = result["city"].(map[string]any)["id"].(string)
    }

    // Create road network with distances
    roads := []struct {
        from, to    string
        distance    float64
        trafficLevel float64
    }{
        {"Los Angeles", "San Diego", 120.0, 0.7},
        {"Los Angeles", "Las Vegas", 270.0, 0.5},
        {"San Diego", "Phoenix", 355.0, 0.4},
        {"Las Vegas", "Phoenix", 297.0, 0.6},
    }

    for _, road := range roads {
        var r map[string]any
        if err := client.Query("CreateRoad", helix.WithData(map[string]any{
            "from_id":       cities[road.from],
            "to_id":         cities[road.to],
            "distance":      road.distance,
            "traffic_level": road.trafficLevel,
        })).Scan(&r); err != nil {
            log.Fatalf("CreateRoad failed: %s", err)
        }
    }

    // Find shortest route by distance
    var result map[string]any
    if err := client.Query("FindShortestRoute", helix.WithData(map[string]any{
        "start_id": cities["Los Angeles"],
        "end_id":   cities["Phoenix"],
    })).Scan(&result); err != nil {
        log.Fatalf("FindShortestRoute failed: %s", err)
    }

    fmt.Printf("Shortest route from LA to Phoenix: %#v\n", result)
}

import HelixDB from "helix-ts";

async function main() {
    const client = new HelixDB("http://localhost:6969");

    // Create cities
    const cities: Record<string, string> = {};
    const cityData = [
        { name: "Los Angeles", population: 4000000 },
        { name: "San Diego", population: 1400000 },
        { name: "Phoenix", population: 1600000 },
        { name: "Las Vegas", population: 650000 },
    ];

    for (const city of cityData) {
        const result = await client.query("CreateCity", city);
        cities[city.name] = result.city.id;
    }

    // Create road network with distances
    const roads = [
        { from: "Los Angeles", to: "San Diego", distance: 120.0, traffic: 0.7 },
        { from: "Los Angeles", to: "Las Vegas", distance: 270.0, traffic: 0.5 },
        { from: "San Diego", to: "Phoenix", distance: 355.0, traffic: 0.4 },
        { from: "Las Vegas", to: "Phoenix", distance: 297.0, traffic: 0.6 },
    ];

    for (const road of roads) {
        await client.query("CreateRoad", {
            from_id: cities[road.from],
            to_id: cities[road.to],
            distance: road.distance,
            traffic_level: road.traffic,
        });
    }

    // Find shortest route by distance
    const result = await client.query("FindShortestRoute", {
        start_id: cities["Los Angeles"],
        end_id: cities["Phoenix"],
    });

    console.log("Shortest route from LA to Phoenix:");
    console.log("Path:", result.result.path.map((n: any) => n.name).join(" -> "));
    console.log("Total distance:", result.result.total_weight.toFixed(1), "miles");
    console.log("Hops:", result.result.hop_count);
}

main().catch((err) => {
    console.error("Query failed:", err);
});

# Create cities
LA_ID=$(curl -X POST http://localhost:6969/CreateCity \
  -H 'Content-Type: application/json' \
  -d '{"name":"Los Angeles","population":4000000}' | jq -r '.city.id')

SD_ID=$(curl -X POST http://localhost:6969/CreateCity \
  -H 'Content-Type: application/json' \
  -d '{"name":"San Diego","population":1400000}' | jq -r '.city.id')

PHX_ID=$(curl -X POST http://localhost:6969/CreateCity \
  -H 'Content-Type: application/json' \
  -d '{"name":"Phoenix","population":1600000}' | jq -r '.city.id')

LV_ID=$(curl -X POST http://localhost:6969/CreateCity \
  -H 'Content-Type: application/json' \
  -d '{"name":"Las Vegas","population":650000}' | jq -r '.city.id')

# Create roads
curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$LA_ID\",\"to_id\":\"$SD_ID\",\"distance\":120.0,\"traffic_level\":0.7}"

curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$LA_ID\",\"to_id\":\"$LV_ID\",\"distance\":270.0,\"traffic_level\":0.5}"

curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$SD_ID\",\"to_id\":\"$PHX_ID\",\"distance\":355.0,\"traffic_level\":0.4}"

curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$LV_ID\",\"to_id\":\"$PHX_ID\",\"distance\":297.0,\"traffic_level\":0.6}"

# Find shortest route
curl -X POST http://localhost:6969/FindShortestRoute \
  -H 'Content-Type: application/json' \
  -d "{\"start_id\":\"$LA_ID\",\"end_id\":\"$PHX_ID\"}"

Example 2: Traffic-aware routing with multi-context weights

QUERY FindTrafficAwareRoute(start_id: ID, end_id: ID) =>
    result <- N<City>(start_id)
        ::ShortestPathDijkstras<Road>(MUL(_::{distance}, _::FromN::{traffic_factor}))
        ::To(end_id)
    RETURN result

QUERY CreateCityWithTraffic(name: String, traffic_factor: F64) =>
    city <- AddN<City>({ name: name, traffic_factor: traffic_factor })
    RETURN city

QUERY CreateRoad(from_id: ID, to_id: ID, distance: F64) =>
    road <- AddE<Road>({ distance: distance })::From(from_id)::To(to_id)
    RETURN road

N::City {
    name: String,
    traffic_factor: F64  // Multiplier: 1.0 = normal, 2.0 = heavy traffic
}

E::Road {
    From: City,
    To: City,
    Properties: {
        distance: F64
    }
}

Here’s how to run the query using the SDKs or curl

from helix.client import Client

client = Client(local=True, port=6969)

# Create cities with traffic factors
cities = {}
city_data = [
    ("Downtown", 2.5),      # Heavy traffic
    ("Suburbs", 1.0),       # Normal traffic
    ("Industrial", 1.2),    # Light traffic
    ("Airport", 1.8),       # Moderate traffic
]

for name, traffic_factor in city_data:
    result = client.query("CreateCityWithTraffic", {
        "name": name,
        "traffic_factor": traffic_factor
    })
    cities[name] = result["city"]["id"]

# Create roads (base distances)
roads = [
    ("Downtown", "Suburbs", 10.0),
    ("Downtown", "Industrial", 8.0),
    ("Suburbs", "Airport", 15.0),
    ("Industrial", "Airport", 12.0),
]

for from_city, to_city, distance in roads:
    client.query("CreateRoad", {
        "from_id": cities[from_city],
        "to_id": cities[to_city],
        "distance": distance
    })

# Find traffic-aware route
# Weight = distance * source_traffic_factor
# Avoids routes starting from high-traffic areas
result = client.query("FindTrafficAwareRoute", {
    "start_id": cities["Downtown"],
    "end_id": cities["Airport"]
})

print(f"Traffic-aware route from Downtown to Airport:")
print(f"Path: {' -> '.join([node['name'] for node in result['result']['path']])}")
print(f"Effective distance: {result['result']['total_weight']:.1f}")

use helix_rs::{HelixDB, HelixDBClient};
use serde_json::json;
use std::collections::HashMap;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = HelixDB::new(Some("http://localhost"), Some(6969), None);

    // Create cities with traffic factors
    let mut cities: HashMap<String, String> = HashMap::new();
    let city_data = vec![
        ("Downtown", 2.5),
        ("Suburbs", 1.0),
        ("Industrial", 1.2),
        ("Airport", 1.8),
    ];

    for (name, traffic_factor) in &city_data {
        let result: serde_json::Value = client.query("CreateCityWithTraffic", &json!({
            "name": name,
            "traffic_factor": traffic_factor,
        })).await?;
        cities.insert(name.to_string(), result["city"]["id"].as_str().unwrap().to_string());
    }

    // Create roads
    let roads = vec![
        ("Downtown", "Suburbs", 10.0),
        ("Downtown", "Industrial", 8.0),
        ("Suburbs", "Airport", 15.0),
        ("Industrial", "Airport", 12.0),
    ];

    for (from_city, to_city, distance) in &roads {
        let _road: serde_json::Value = client.query("CreateRoad", &json!({
            "from_id": cities[*from_city],
            "to_id": cities[*to_city],
            "distance": distance,
        })).await?;
    }

    // Find traffic-aware route
    let result: serde_json::Value = client.query("FindTrafficAwareRoute", &json!({
        "start_id": cities["Downtown"],
        "end_id": cities["Airport"],
    })).await?;

    println!("Traffic-aware route: {result:#?}");

    Ok(())
}

package main

import (
    "fmt"
    "log"

    "github.com/HelixDB/helix-go"
)

func main() {
    client := helix.NewClient("http://localhost:6969")

    // Create cities with traffic factors
    cities := make(map[string]string)
    cityData := []struct {
        name          string
        trafficFactor float64
    }{
        {"Downtown", 2.5},
        {"Suburbs", 1.0},
        {"Industrial", 1.2},
        {"Airport", 1.8},
    }

    for _, city := range cityData {
        var result map[string]any
        if err := client.Query("CreateCityWithTraffic", helix.WithData(map[string]any{
            "name":           city.name,
            "traffic_factor": city.trafficFactor,
        })).Scan(&result); err != nil {
            log.Fatalf("CreateCityWithTraffic failed: %s", err)
        }
        cities[city.name] = result["city"].(map[string]any)["id"].(string)
    }

    // Create roads
    roads := []struct {
        from, to string
        distance float64
    }{
        {"Downtown", "Suburbs", 10.0},
        {"Downtown", "Industrial", 8.0},
        {"Suburbs", "Airport", 15.0},
        {"Industrial", "Airport", 12.0},
    }

    for _, road := range roads {
        var r map[string]any
        if err := client.Query("CreateRoad", helix.WithData(map[string]any{
            "from_id":  cities[road.from],
            "to_id":    cities[road.to],
            "distance": road.distance,
        })).Scan(&r); err != nil {
            log.Fatalf("CreateRoad failed: %s", err)
        }
    }

    // Find traffic-aware route
    var result map[string]any
    if err := client.Query("FindTrafficAwareRoute", helix.WithData(map[string]any{
        "start_id": cities["Downtown"],
        "end_id":   cities["Airport"],
    })).Scan(&result); err != nil {
        log.Fatalf("FindTrafficAwareRoute failed: %s", err)
    }

    fmt.Printf("Traffic-aware route: %#v\n", result)
}

import HelixDB from "helix-ts";

async function main() {
    const client = new HelixDB("http://localhost:6969");

    // Create cities with traffic factors
    const cities: Record<string, string> = {};
    const cityData = [
        { name: "Downtown", traffic_factor: 2.5 },
        { name: "Suburbs", traffic_factor: 1.0 },
        { name: "Industrial", traffic_factor: 1.2 },
        { name: "Airport", traffic_factor: 1.8 },
    ];

    for (const city of cityData) {
        const result = await client.query("CreateCityWithTraffic", city);
        cities[city.name] = result.city.id;
    }

    // Create roads
    const roads = [
        { from: "Downtown", to: "Suburbs", distance: 10.0 },
        { from: "Downtown", to: "Industrial", distance: 8.0 },
        { from: "Suburbs", to: "Airport", distance: 15.0 },
        { from: "Industrial", to: "Airport", distance: 12.0 },
    ];

    for (const road of roads) {
        await client.query("CreateRoad", {
            from_id: cities[road.from],
            to_id: cities[road.to],
            distance: road.distance,
        });
    }

    // Find traffic-aware route
    const result = await client.query("FindTrafficAwareRoute", {
        start_id: cities["Downtown"],
        end_id: cities["Airport"],
    });

    console.log("Traffic-aware route from Downtown to Airport:");
    console.log("Path:", result.result.path.map((n: any) => n.name).join(" -> "));
    console.log("Effective distance:", result.result.total_weight.toFixed(1));
}

main().catch((err) => {
    console.error("Query failed:", err);
});

# Create cities with traffic factors
DOWNTOWN_ID=$(curl -X POST http://localhost:6969/CreateCityWithTraffic \
  -H 'Content-Type: application/json' \
  -d '{"name":"Downtown","traffic_factor":2.5}' | jq -r '.city.id')

SUBURBS_ID=$(curl -X POST http://localhost:6969/CreateCityWithTraffic \
  -H 'Content-Type: application/json' \
  -d '{"name":"Suburbs","traffic_factor":1.0}' | jq -r '.city.id')

INDUSTRIAL_ID=$(curl -X POST http://localhost:6969/CreateCityWithTraffic \
  -H 'Content-Type: application/json' \
  -d '{"name":"Industrial","traffic_factor":1.2}' | jq -r '.city.id')

AIRPORT_ID=$(curl -X POST http://localhost:6969/CreateCityWithTraffic \
  -H 'Content-Type: application/json' \
  -d '{"name":"Airport","traffic_factor":1.8}' | jq -r '.city.id')

# Create roads
curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$DOWNTOWN_ID\",\"to_id\":\"$SUBURBS_ID\",\"distance\":10.0}"

curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$DOWNTOWN_ID\",\"to_id\":\"$INDUSTRIAL_ID\",\"distance\":8.0}"

curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$SUBURBS_ID\",\"to_id\":\"$AIRPORT_ID\",\"distance\":15.0}"

curl -X POST http://localhost:6969/CreateRoad \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$INDUSTRIAL_ID\",\"to_id\":\"$AIRPORT_ID\",\"distance\":12.0}"

# Find traffic-aware route
curl -X POST http://localhost:6969/FindTrafficAwareRoute \
  -H 'Content-Type: application/json' \
  -d "{\"start_id\":\"$DOWNTOWN_ID\",\"end_id\":\"$AIRPORT_ID\"}"

Example 3: Complex multi-factor weight calculation

QUERY FindOptimalRoute(start_id: ID, end_id: ID) =>
    result <- N<Location>(start_id)
        ::ShortestPathDijkstras<Route>(
            ADD(
                MUL(_::{distance}, 0.4),
                ADD(
                    MUL(_::FromN::{traffic_factor}, 0.3),
                    MUL(SUB(1, _::{reliability}), 0.3)
                )
            )
        )
        ::To(end_id)
    RETURN result

QUERY CreateLocation(name: String, traffic_factor: F64) =>
    location <- AddN<Location>({ name: name, traffic_factor: traffic_factor })
    RETURN location

QUERY CreateRoute(from_id: ID, to_id: ID, distance: F64, reliability: F64) =>
    route <- AddE<Route>({ distance: distance, reliability: reliability })::From(from_id)::To(to_id)
    RETURN route

N::Location {
    name: String,
    traffic_factor: F64  // Current traffic multiplier
}

E::Route {
    From: Location,
    To: Location,
    Properties: {
        distance: F64,
        reliability: F64     // 0.0 to 1.0 (1.0 = perfectly reliable)
    }
}

Here’s how to run the query using the SDKs or curl

from helix.client import Client

client = Client(local=True, port=6969)

# Create locations with traffic factors
locations = {}
location_data = [
    ("Station A", 1.2),
    ("Station B", 0.8),
    ("Station C", 1.5),
    ("Station D", 1.0),
]

for name, traffic_factor in location_data:
    result = client.query("CreateLocation", {
        "name": name,
        "traffic_factor": traffic_factor
    })
    locations[name] = result["location"]["id"]

# Create routes with distance and reliability
# Weight = 0.4*distance + 0.3*traffic + 0.3*(1-reliability)
routes = [
    ("Station A", "Station B", 100.0, 0.95),
    ("Station A", "Station C", 80.0, 0.70),
    ("Station B", "Station D", 120.0, 0.90),
    ("Station C", "Station D", 90.0, 0.85),
]

for from_loc, to_loc, distance, reliability in routes:
    client.query("CreateRoute", {
        "from_id": locations[from_loc],
        "to_id": locations[to_loc],
        "distance": distance,
        "reliability": reliability
    })

# Find optimal route considering distance, traffic, and reliability
result = client.query("FindOptimalRoute", {
    "start_id": locations["Station A"],
    "end_id": locations["Station D"]
})

print(f"Optimal route from Station A to Station D:")
print(f"Path: {' -> '.join([node['name'] for node in result['result']['path']])}")
print(f"Composite weight: {result['result']['total_weight']:.2f}")
print(f"(40% distance + 30% traffic + 30% unreliability)")

use helix_rs::{HelixDB, HelixDBClient};
use serde_json::json;
use std::collections::HashMap;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = HelixDB::new(Some("http://localhost"), Some(6969), None);

    // Create locations with traffic factors
    let mut locations: HashMap<String, String> = HashMap::new();
    let location_data = vec![
        ("Station A", 1.2),
        ("Station B", 0.8),
        ("Station C", 1.5),
        ("Station D", 1.0),
    ];

    for (name, traffic_factor) in &location_data {
        let result: serde_json::Value = client.query("CreateLocation", &json!({
            "name": name,
            "traffic_factor": traffic_factor,
        })).await?;
        locations.insert(name.to_string(), result["location"]["id"].as_str().unwrap().to_string());
    }

    // Create routes with distance and reliability
    let routes = vec![
        ("Station A", "Station B", 100.0, 0.95),
        ("Station A", "Station C", 80.0, 0.70),
        ("Station B", "Station D", 120.0, 0.90),
        ("Station C", "Station D", 90.0, 0.85),
    ];

    for (from_loc, to_loc, distance, reliability) in &routes {
        let _route: serde_json::Value = client.query("CreateRoute", &json!({
            "from_id": locations[*from_loc],
            "to_id": locations[*to_loc],
            "distance": distance,
            "reliability": reliability,
        })).await?;
    }

    // Find optimal route
    let result: serde_json::Value = client.query("FindOptimalRoute", &json!({
        "start_id": locations["Station A"],
        "end_id": locations["Station D"],
    })).await?;

    println!("Optimal route: {result:#?}");

    Ok(())
}

package main

import (
    "fmt"
    "log"

    "github.com/HelixDB/helix-go"
)

func main() {
    client := helix.NewClient("http://localhost:6969")

    // Create locations with traffic factors
    locations := make(map[string]string)
    locationData := []struct {
        name          string
        trafficFactor float64
    }{
        {"Station A", 1.2},
        {"Station B", 0.8},
        {"Station C", 1.5},
        {"Station D", 1.0},
    }

    for _, loc := range locationData {
        var result map[string]any
        if err := client.Query("CreateLocation", helix.WithData(map[string]any{
            "name":           loc.name,
            "traffic_factor": loc.trafficFactor,
        })).Scan(&result); err != nil {
            log.Fatalf("CreateLocation failed: %s", err)
        }
        locations[loc.name] = result["location"].(map[string]any)["id"].(string)
    }

    // Create routes with distance and reliability
    routes := []struct {
        from, to    string
        distance    float64
        reliability float64
    }{
        {"Station A", "Station B", 100.0, 0.95},
        {"Station A", "Station C", 80.0, 0.70},
        {"Station B", "Station D", 120.0, 0.90},
        {"Station C", "Station D", 90.0, 0.85},
    }

    for _, route := range routes {
        var r map[string]any
        if err := client.Query("CreateRoute", helix.WithData(map[string]any{
            "from_id":     locations[route.from],
            "to_id":       locations[route.to],
            "distance":    route.distance,
            "reliability": route.reliability,
        })).Scan(&r); err != nil {
            log.Fatalf("CreateRoute failed: %s", err)
        }
    }

    // Find optimal route
    var result map[string]any
    if err := client.Query("FindOptimalRoute", helix.WithData(map[string]any{
        "start_id": locations["Station A"],
        "end_id":   locations["Station D"],
    })).Scan(&result); err != nil {
        log.Fatalf("FindOptimalRoute failed: %s", err)
    }

    fmt.Printf("Optimal route: %#v\n", result)
}

import HelixDB from "helix-ts";

async function main() {
    const client = new HelixDB("http://localhost:6969");

    // Create locations with traffic factors
    const locations: Record<string, string> = {};
    const locationData = [
        { name: "Station A", traffic_factor: 1.2 },
        { name: "Station B", traffic_factor: 0.8 },
        { name: "Station C", traffic_factor: 1.5 },
        { name: "Station D", traffic_factor: 1.0 },
    ];

    for (const loc of locationData) {
        const result = await client.query("CreateLocation", loc);
        locations[loc.name] = result.location.id;
    }

    // Create routes with distance and reliability
    const routes = [
        { from: "Station A", to: "Station B", distance: 100.0, reliability: 0.95 },
        { from: "Station A", to: "Station C", distance: 80.0, reliability: 0.70 },
        { from: "Station B", to: "Station D", distance: 120.0, reliability: 0.90 },
        { from: "Station C", to: "Station D", distance: 90.0, reliability: 0.85 },
    ];

    for (const route of routes) {
        await client.query("CreateRoute", {
            from_id: locations[route.from],
            to_id: locations[route.to],
            distance: route.distance,
            reliability: route.reliability,
        });
    }

    // Find optimal route
    const result = await client.query("FindOptimalRoute", {
        start_id: locations["Station A"],
        end_id: locations["Station D"],
    });

    console.log("Optimal route from Station A to Station D:");
    console.log("Path:", result.result.path.map((n: any) => n.name).join(" -> "));
    console.log("Composite weight:", result.result.total_weight.toFixed(2));
    console.log("(40% distance + 30% traffic + 30% unreliability)");
}

main().catch((err) => {
    console.error("Query failed:", err);
});

# Create locations
STATION_A_ID=$(curl -X POST http://localhost:6969/CreateLocation \
  -H 'Content-Type: application/json' \
  -d '{"name":"Station A","traffic_factor":1.2}' | jq -r '.location.id')

STATION_B_ID=$(curl -X POST http://localhost:6969/CreateLocation \
  -H 'Content-Type: application/json' \
  -d '{"name":"Station B","traffic_factor":0.8}' | jq -r '.location.id')

STATION_C_ID=$(curl -X POST http://localhost:6969/CreateLocation \
  -H 'Content-Type: application/json' \
  -d '{"name":"Station C","traffic_factor":1.5}' | jq -r '.location.id')

STATION_D_ID=$(curl -X POST http://localhost:6969/CreateLocation \
  -H 'Content-Type: application/json' \
  -d '{"name":"Station D","traffic_factor":1.0}' | jq -r '.location.id')

# Create routes
curl -X POST http://localhost:6969/CreateRoute \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$STATION_A_ID\",\"to_id\":\"$STATION_B_ID\",\"distance\":100.0,\"reliability\":0.95}"

curl -X POST http://localhost:6969/CreateRoute \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$STATION_A_ID\",\"to_id\":\"$STATION_C_ID\",\"distance\":80.0,\"reliability\":0.70}"

curl -X POST http://localhost:6969/CreateRoute \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$STATION_B_ID\",\"to_id\":\"$STATION_D_ID\",\"distance\":120.0,\"reliability\":0.90}"

curl -X POST http://localhost:6969/CreateRoute \
  -H 'Content-Type: application/json' \
  -d "{\"from_id\":\"$STATION_C_ID\",\"to_id\":\"$STATION_D_ID\",\"distance\":90.0,\"reliability\":0.85}"

# Find optimal route
curl -X POST http://localhost:6969/FindOptimalRoute \
  -H 'Content-Type: application/json' \
  -d "{\"start_id\":\"$STATION_A_ID\",\"end_id\":\"$STATION_D_ID\"}"

Property Context Reference

Context	Description	Example
`_::{property}`	Edge property	`_::{distance}`
`_::FromN::{property}`	Source node property	`_::FromN::{traffic_factor}`
`_::ToN::{property}`	Destination node property	`_::ToN::{popularity}`

Available Mathematical Functions

Use these functions in weight expressions:

Arithmetic: ADD, SUB, MUL, DIV, MOD
Power: POW, SQRT, EXP, LN, LOG
Rounding: CEIL, FLOOR, ROUND, ABS
Trigonometric: SIN, COS, TAN
Constants: PI()

See Advanced Weight Expressions for more details.

Performance Considerations

Time Complexity: O((V + E) log V) using binary heap
Space Complexity: O(V) for distance tracking
Weight Calculation: Evaluated once per edge during exploration
Indexing: Index properties used in weight calculations for best performance

Complex weight expressions may impact query performance. Profile your queries and consider caching frequently-accessed property values.

Custom Weights

Deep dive into property contexts and weight patterns

Weight Expressions

Advanced mathematical weight calculations

ShortestPathAStar

Faster pathfinding with heuristics

Mathematical Functions

All available math functions

Getting Started

Schema

Writing Data

Reading Data

Search

Graph Traversals

Aggregation

Advanced Queries

Reference

ShortestPathDijkstras

Find Weighted Shortest Paths with Dijkstra’s Algorithm

How It Works

When to Use ShortestPathDijkstras

Weight Expressions

Example 1: Simple property-based weight

Example 2: Traffic-aware routing with multi-context weights

Example 3: Complex multi-factor weight calculation

Property Context Reference

Available Mathematical Functions

Performance Considerations

Custom Weights

Weight Expressions

ShortestPathAStar

Mathematical Functions

​Find Weighted Shortest Paths with Dijkstra’s Algorithm

​How It Works

​When to Use ShortestPathDijkstras

​Weight Expressions

​Example 1: Simple property-based weight

​Example 2: Traffic-aware routing with multi-context weights

​Example 3: Complex multi-factor weight calculation

​Property Context Reference

​Available Mathematical Functions

​Performance Considerations

​Related Topics

Custom Weights

Weight Expressions

ShortestPathAStar

Mathematical Functions

Find Weighted Shortest Paths with Dijkstra’s Algorithm

How It Works

When to Use ShortestPathDijkstras

Weight Expressions

Example 1: Simple property-based weight

Example 2: Traffic-aware routing with multi-context weights

Example 3: Complex multi-factor weight calculation

Property Context Reference

Available Mathematical Functions

Performance Considerations

Related Topics