Live Data Generator

Connect to AnyLog's shared data generator and ingest synthetic industrial data in minutes.

` wrapper, which would have rendered the changelog table at the top of the published page. Used this file’s correctly-wrapped version as the base. Flagged: proveit_data.py missing a destination arrow in the Architecture diagram; a real coverage gap where the generator can publish wind-turbine2 and full ProveIT (Enterprise A/B/C, 4 formats) but the AnyLog-side script reference only covers the original wind-turbine dataset and 2 of 3 ProveIT enterprises via 2 of 4 formats; fixed the final validation query’s mydb → test to match the generator’s actual default --db-name | | | 2026-07-20 | Eric Aquaronne | added change log | 2.0.2606 | | 2026-04-17 | | creation | | —>

AnyLog provides two tools that work together for testing and demos:

Python data generator (data_generator_main.py) — publishes synthetic industrial data via REST, MQTT, or OPC-UA
AnyLog .al scripts (data-generator/) — declare mapping policies and run msg client on the operator node to receive that data

Live MQTT broker

AnyLog runs a shared MQTT broker that continuously publishes data for all supported datasets. Connect your operator directly to skip running the Python generator locally.

Parameter	Value
Broker	`172.104.228.251`
Port	`1883`
Username	`anyloguser`
Password	`mqtt4AnyLog!`

How it works — end to end flow

[ Python generator ]          [ AnyLog Operator Node ]
  data_generator_main.py
         │
         │  MQTT / REST POST / PUT
         ▼
  ┌─────────────┐       1. process mapping/*.al   → declare mapping policy on blockchain
  │  MQTT broker │  →   2. process [dataset].al   → declare run msg client + subscribe
  │  (or REST)   │      3. get msg client          → verify streaming is active
  └─────────────┘       4. query data              → run client () sql ...

Step 1 — Mapping policy defines the schema: which fields map to which columns and types. Stored on the blockchain so any node in the network can use it.

Step 2 — run msg client connects to the broker, subscribes to the topic(s), and maps incoming JSON to the target database and table using the policy.

Step 3 — get msg client verifies the subscription is active and shows message counts.

Step 4 — Query data is immediately queryable once ingested.

deployment-scripts/data-generator — file reference

data-generator/
├── drone_telemetry.al          ← drone swarm telemetry (REST POST)
├── oil_rig_data.al             ← drilling metrics, 6 rigs, multiple topics
├── rand_data.al                ← simple timestamp/value (MQTT)
├── vessel_data.al              ← electric boat battery + charger data
├── wind_turbine_data.al        ← wind farm metrics across 10 turbines
├── mqtt_enterprise_c_sub.al    ← Enterprise C ProveIT data (MQTT)
├── opcua_enterprise_a.al       ← Enterprise A ProveIT data (OPC-UA)
└── mapping/
    ├── drone_mapping.al
    ├── rig_rig-data.al
    ├── vessel_BATTERY-PACK-DEVICE-LOGS.al
    ├── vessel_BATTERY-PACK-LOGS.al
    ├── vessel_CHARGER-DEVICE-LOGS.al
    ├── vessel_CHARGER-LOGS.al
    ├── vessel_VESSEL-POWER-LOGS.al
    ├── vessel_VESSEL-STATE-LOGS.al
    ├── wind_turbine_available-power.al
    ├── wind_turbine_blade-pitch.al
    ├── wind_turbine_energy.al
    └── wind_turbine_reactive-power.al

Coverage gap: the Python generator (below) can also publish wind-turbine2 and full ProveIT data (Enterprise A/B/C, across print/post/mqtt/opcua), but this file reference only has ingestion scripts for the original wind-turbine dataset and 2 of 3 ProveIT enterprises (Enterprise C via MQTT, Enterprise A via OPC-UA) — nothing here covers Enterprise B or ProveIT via REST POST. Confirm whether corresponding .al scripts exist elsewhere before assuming end-to-end coverage for those combinations.

Non-mapping scripts — process commands

File	Process command	Data source
`rand_data.al`	`process !local_scripts/data-generator/rand_data.al`	`anylog-demo` topic — timestamp + value
`oil_rig_data.al`	`process !local_scripts/data-generator/oil_rig_data.al`	`rig-data/*` topics — drilling metrics
`vessel_data.al`	`process !local_scripts/data-generator/vessel_data.al`	`vessel-data/DLT` + `vessel-data/DLB` — battery + charger
`wind_turbine_data.al`	`process !local_scripts/data-generator/wind_turbine_data.al`	`wind-turbine/*` topics — 10 turbines
`drone_telemetry.al`	`process !local_scripts/data-generator/drone_telemetry.al`	`drone-telemetry` topic — REST POST
`mqtt_enterprise_c_sub.al`	`process !local_scripts/data-generator/mqtt_enterprise_c_sub.al`	ProveIT Enterprise C
`opcua_enterprise_a.al`	`process !local_scripts/data-generator/opcua_enterprise_a.al`	ProveIT Enterprise A (OPC-UA)

Each script internally calls the relevant mapping/*.al files first, then declares run msg client.

Python data generator

Repo: AnyLog-co/Sample-Data-Generator (branch: data-generator2)

Architecture

Southbound (generates data)        Northbound (publishes)
──────────────────────────         ──────────────────────
random_data.py          ─────────► REST PUT
rig_data.py             ─────────► REST POST
vessel_data.py          ─────────► MQTT
wind_turbine.py         ─────────► OPC-UA (Proveit only)
proveit_data.py         ─────────► print / REST POST / MQTT / OPC-UA

Supported datasets and publish formats

Dataset	`data` argument	Publish formats	Tables
Random timestamp/value	`random`	print, put, post, mqtt	`rand_data`
Oil rig drilling	`rig`	print, put, post, mqtt	`rig_data`
Electric vessel	`vessel`	print, post, mqtt	6 tables (battery, charger, power, state)
Wind turbine	`wind-turbine`	print, post, mqtt	4 tables per turbine
Wind turbine v2	`wind-turbine2`	print, post, mqtt, opcua	farm/turbine hierarchy
ProveIT 2026	`proveit`	print, post, mqtt, opcua	Enterprise A / B / C

Usage

python data_generator_main.py [dataset] [publish_format] [options]

Global options:

Option	Default	Description
`--control-conn IP:PORT`	—	AnyLog node used to declare mapping policies and `run msg client`
`--data-conn IP:PORT`	= `control-conn`	Data destination (REST/MQTT). Defaults to `control-conn` if omitted
`--db-name NAME`	`test`	Logical database name
`--repeat N`	`10`	Iterations. `0` = run continuously
`--sleep SECONDS`	`15`	Delay between iterations
`--offset-sleep SECONDS`	`0.5`	Delay between multiple IDs per iteration
`--skip-msg-client`	false	Skip declaring `run msg client` (useful if already running)
`--skip-inserts`	false	Only declare the `run msg client`, skip data publishing

Dataset-specific options:

Option	Dataset	Description
`--ids 1 3 7`	`rig`	Rig IDs to publish (default: all 6)
`--ids DLB DLT`	`vessel`	Engine sides (default: both)
`--ids 1 3 7`	`wind-turbine`	Turbine IDs 1–11, excluding 4 (default: all)
`--topics "Enterprise A"`	`proveit`	ProveIT topic groups (default: all)

Examples

# Print random data to console — no connection needed
python data_generator_main.py random print

# Publish all rigs via MQTT to local AnyLog broker
python data_generator_main.py rig mqtt --control-conn 127.0.0.1:32149 --data-conn 127.0.0.1:32150

# Publish specific rigs only
python data_generator_main.py rig mqtt --control-conn 127.0.0.1:32149 --data-conn 127.0.0.1:32150 --ids 1 3

# Publish all wind turbines except 4 via REST POST
python data_generator_main.py wind-turbine post --control-conn 127.0.0.1:32149

# Publish specific turbines
python data_generator_main.py wind-turbine post --control-conn 127.0.0.1:32149 --ids 2 7

# Vessel DLB side only
python data_generator_main.py vessel mqtt --control-conn 127.0.0.1:32149 --data-conn 127.0.0.1:32150 --ids DLB

# Run continuously (repeat=0)
python data_generator_main.py random mqtt --control-conn 127.0.0.1:32149 --data-conn 127.0.0.1:32150 --repeat 0 --sleep 5

Validating ingestion on the operator

After running either the Python generator or a process command, verify on the operator node:

# Check the msg client is subscribed and receiving
get msg client

# Check streaming buffer status
get streaming

# Query the data (replace `test` with your --db-name if you overrode the default)
run client () sql test format=table "SELECT * FROM rand_data ORDER BY timestamp DESC LIMIT 10"