Génération de données de test avec Frappe Faker

Générez des enregistrements de test réalistes et liés pour tout DocType Frappe/ERPNext via la CLI bench faker. Créez des données de test pour le développement, les démos ou les reproductions locales, puis nettoyez en une commande.

Spar Skills Guide Bot
TestingIntermédiaire
1022/07/2026
Claude Code
#faker#frappe#erpnext#test-data#cli

Recommandé pour


name: faker-data description: Generate realistic, correctly-linked Frappe/ERPNext test records for any DocType using the bench faker CLI, then roll them back when done. Use when a test, demo, or local repro needs seed data and the site is missing it — e.g. "I need some Sales Orders", "seed data so I can test this API", "create test Employees in Chennai", or "populate the database to test this endpoint".

Frappe Faker — Generate Test Data from the CLI

Use this skill when you need realistic, linked Frappe/ERPNext test records for a specific DocType. Faker resolves the full dependency graph, generates all linked records via LLM, and inserts them in FK-safe order. Every run produces a Faker Batch ID that you can use to delete all generated records when testing is done.

Prerequisites

  • The Frappe Faker app must be installed on the site
  • Faker Settings must have a configured AI provider (check /app/faker-settings)
  • The RQ background worker is not needed — CLI runs synchronously in the terminal

Workflow

1. Inspect dependencies first

bench --site <site> faker plan --doctype "<DocType>"

This shows the full dependency tree without generating anything. Look for:

  • [Has data — will skip] — existing records will be reused; no generation needed
  • [Cyclic] — cycle detected; generation will still proceed
  • [Target] — the DocType you requested

Example output:

Dependency plan for: Salary Slip

Salary Slip  [Target]
  Salary Structure Assignment
    Employee
      Department  [Has data — will skip]
    Company  [Has data — will skip]
  Salary Structure

2. Generate records

bench --site <site> faker generate \
  --doctype "<DocType>" \
  --count <N> \
  --instructions "<free-text requirements>"

Options:

  • --count / -n — number of target doctype records (dependencies get min(count, 5))
  • --skip — comma-separated list of DocTypes to skip (e.g. --skip "Employee,Company")
  • --instructions — natural language constraints passed to the LLM
  • --no-fast-insert — use standard doc.insert() path (runs Python hooks; slower)

Example:

bench --site demo.localhost faker generate \
  --doctype "Salary Slip" --count 3 \
  --instructions "Employees are software engineers in Bangalore, monthly salary 80k-120k INR, use existing company"

Output:

Generating 3 record(s) for Salary Slip...

Batch: abc123def456  |  Created: 12  |  Failed: 0
  Department: 0 created  (skipped — has data)
  Employee: 3 created
  Salary Structure: 3 created
  Salary Structure Assignment: 3 created
  Salary Slip: 3 created

3. Run your tests

Use the generated records for whatever testing or API calls you need.

4. Clean up

bench --site <site> faker cleanup --batch <batch_id>

This deletes all records from the batch in reverse dependency order (FK-safe). Use the batch ID printed by faker generate.

bench --site demo.localhost faker cleanup --batch abc123def456
# → Deleted 12 record(s). Status: Rolled Back

Tips

  • Use --instructions liberally — the LLM respects free-text constraints like dates, locations, salary ranges, roles, and relationships between records
  • Skip doctypes with existing data — if your site already has Employees, use --skip "Employee" to reuse them and avoid duplication
  • Check for errors — if Failed > 0, re-run with a lower count or simpler instructions; per-record errors are logged in the output
  • Batch rollback is partial-crash-safe — if generation crashes mid-way, the batch still tracks all successfully inserted records; cleanup will roll back only what was tracked

Rollback from the UI

Open the Frappe Faker web app at /faker, go to History, click a run row, and use the Rollback button in the detail dialog to delete that batch's records without touching the terminal.

Skills similaires