hurl-orchestra 0.6.0

Run hurl test files in dependency order using frontmatter metadata

Hurl Orchestrator

A dependency-aware task runner for Hurl. It allows you to treat API requests as a Directed Acyclic Graph (DAG), managing complex authentication flows and resource creation without redundant executions or manual variable passing.

Getting Started

Install the package and verify that hurl is available on your PATH.

pip install hurl-orchestra
hurl --version

Run the orchestrator from the current directory:

hurl-orchestra

Or point it at a specific test folder:

hurl-orchestra ./tests

For a quick diagram of your DAG instead of execution, use:

hurl-orchestra --diagram ./tests

Core Philosophy

• Explicit over Implicit: Every dependency must be declared. This ensures that if a test fails, you know exactly which parent requirement was not met.
• Namespaced Variables: Outputs are tied to the ID of the node that produced them (auth_token), preventing variable collisions in large suites.
• Reusable Logic: Run the same Hurl file multiple times with different identities (e.g., admin_login vs user_login) using the alias syntax.

---

1. Setup

Requirements

• Python 3.11+
• Hurl installed and available on your PATH

Install

pip install hurl-orchestra

Project Structure

Place your .hurl files in a directory. You can optionally include a .env file for global variables.

tests/
├── .env                # Global variables (base_url, etc.)
├── auth.hurl           # Reusable auth logic
└── create_user.hurl    # Depends on auth

---

2. Defining Hurl Files

Each .hurl file uses YAML frontmatter to define its place in the graph.

Creating and formatting a .hurl file

A .hurl file consists of:

• Optional YAML frontmatter wrapped in --- markers
• The Hurl request and assertions body

Required frontmatter fields:

• id — unique node name for this test
• outputs — list of capture names this test publishes
• deps — list of upstream node IDs or alias definitions
• priority — optional integer that influences ordering within a ready wave

Example file structure:

---
id: my_test
outputs: [token, session_id]
deps: [auth]
priority: 1
---
GET https://api.example.com/resource
Authorization: Bearer {{auth_token}}
HTTP 200

Aliases let you reuse the same template under multiple names and run each alias separately:

---
id: admin_flow
deps:
  - auth: admin_login
  - auth: user_login
---
GET https://api.example.com/admin
Authorization: Bearer {{admin_login_token}}

The Producer (auth.hurl)

Define an id and a list of outputs you want to share with other tests.

---
id: auth
outputs: [token]
---
POST https://api.com/login
[Captures]
token: jsonpath "$.token"
HTTP 200

The Consumer (profile.hurl)

List the id of the producer in deps. Access the variable using the {id}_{variable} syntax.

---
id: get_profile
deps: [auth]
---
GET https://api.com/profile
Authorization: Bearer {{auth_token}}
HTTP 200

---

3. Running

hurl-orchestra                          # runs against the current directory
hurl-orchestra ./tests                  # runs against a specific directory
hurl-orchestra auth.hurl profile.hurl   # run specific files only

Passing Hurl Flags

Any flag that Hurl itself accepts can be passed directly and it will be forwarded to every invocation:

hurl-orchestra ./tests --verbose
hurl-orchestra ./tests --variable host=localhost --retry 3
hurl-orchestra auth.hurl profile.hurl --variable env=staging

This works the same as calling hurl with those flags — the orchestrator passes them through verbatim.

Running Specific Files

When you pass .hurl files directly, the orchestrator still respects their deps, outputs, and all other frontmatter — only the file discovery step changes. Files you list are the only ones loaded as templates, so any deps they declare must also be among the files you pass.

If the diagram output file already exists, use --diagram-overwrite to replace it.

# Runs auth.hurl first (because profile.hurl depends on it), then profile.hurl
hurl-orchestra auth.hurl profile.hurl

Reports

After every run, the orchestrator writes a zip archive containing the raw hurl JSON reports for every node that executed. Each node gets its own subdirectory inside the zip, named after its ID.

report.zip
├── auth/
│   ├── report.json
│   └── store/
└── create_user/
    ├── report.json
    └── store/

The zip is written even if the run fails, so partial results are preserved for debugging. Use --report-zip to change the output filename:

hurl-orchestra ./tests --report-zip ci-run.zip

Visualising the DAG

Pass --diagram to generate a Markdown file with a Mermaid flowchart instead of running tests:

hurl-orchestra --diagram ./tests                      # writes diagram.md
hurl-orchestra --diagram ./tests --diagram-output pipeline.md
hurl-orchestra --diagram auth.hurl profile.hurl --diagram-output -  # stdout
hurl-orchestra --diagram ./tests --diagram-output diagram.md --diagram-overwrite

The output file contains:

• Flowchart — all nodes with edges showing dependency direction. Node labels include the output count and, when non-zero, the priority.

---

4. Advanced Features

Rerunning Dependencies (Aliasing)

If you need to run the same logic twice (e.g., to get two different tokens), use the template: alias syntax in your deps.

---
id: admin_test
deps:
  - auth: admin_login  # Runs auth.hurl as "admin_login"
  - auth: user_login   # Runs auth.hurl as "user_login"
---
GET /admin
Authorization: {{admin_login_token}}

Execution Priority

By default, nodes at the same dependency level run in an unspecified order. Use priority to control that order without adding artificial dependencies.

Value	Effect
positive (e.g. 2)	runs earlier than nodes with lower or no priority
0 (default)	neutral
negative (e.g. -1)	runs later than neutral nodes

Example: you have a create, a search, and a delete that are all independent. Without priority they could run in any order — if delete runs first it breaks search.

---
id: create
priority: 1   # runs first
---

---
id: search
# priority defaults to 0
---

---
id: delete
priority: -1  # runs last
---

Priority only affects ordering within the same wave. It never overrides actual deps — a node always waits for its dependencies regardless of its priority value.

Global Environment (.env)

The orchestrator automatically detects a .env file in the test directory. Variables defined here are available to all Hurl files without being declared in the frontmatter.

# .env
base_url=https://staging.api.com

---

5. Execution Flow

When you run hurl-orchestra, the tool performs the following steps:

1. Discovery: Scans for all .hurl files and reads their metadata.
2. Graph Construction: Builds an execution map. If you used an alias, it "clones" that template into a unique node.
3. Validation: Ensures there are no circular dependencies (e.g., A depends on B, and B depends on A).
4. Execution:
   • Processes nodes wave by wave — each wave contains all nodes whose dependencies are satisfied.
   • Within each wave, nodes are sorted by priority (highest first).
   • Captures output variables into a shared pool.
   • Injects required variables into downstream tests via Hurl's --variable flag.
   • Stops immediately if any test fails to prevent cascade failures.

---

6. Troubleshooting

"Circular dependency detected"

Your deps create an infinite loop. Check your frontmatter to ensure you aren't accidentally requiring a file that eventually requires the current file.

"FAILED: node_id"

The orchestrator will output the stderr from the Hurl binary. This usually means an assertion failed within the .hurl file itself or a network error occurred.

"Node depends on missing node"

Ensure the id in your deps matches the id defined in the target Hurl file's frontmatter (or its filename stem if no id is provided).