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remove processing engine docker dependency (#5841)
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content/shared/v3-core-get-started/_index.md

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### Python plugins and the Processing engine
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> [!Important]
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> #### Processing engine only works with Docker
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>
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> The Processing engine is currently supported only in Docker x86 environments. Non-Docker support is coming soon. The engine, API, and developer experience are actively evolving and may change. Join our [Discord](https://discord.gg/9zaNCW2PRT) for updates and feedback.
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The InfluxDB 3 Processing engine is an embedded Python VM for running code inside the database to process and transform data.
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To use the Processing engine, you create [plugins](#plugin) and [triggers](#trigger).
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### Test, create, and trigger plugin code
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> [!Important]
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> #### Processing engine only works with Docker
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>
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> The Processing engine is currently supported only in Docker x86 environments. Non-Docker support is coming soon. The engine, API, and developer experience are actively evolving and may change. Join our [Discord](https://discord.gg/9zaNCW2PRT) for updates and feedback.
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##### Example: Python plugin for WAL flush
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```python
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To test a plugin, do the following:
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1. Create a _plugin directory_--for example, `/path/to/.influxdb/plugins`
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2. Make the plugin directory available to the Docker container (for example, using a bind mount)
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3. Run the Docker command to [start the server](#start-influxdb) and include the `--plugin-dir` option with your plugin directory path.
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4. Save the [preceding example code](#example-python-plugin) to a plugin file inside of the plugin directory. If you haven't yet written data to the table in the example, comment out the lines where it queries.
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5. To run the test, enter the following command with the following options:
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2. [Start the InfluxDB server](#start-influxdb) and include the `--plugin-dir` option with your plugin directory path.
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3. Save the [preceding example code](#example-python-plugin) to a plugin file inside of the plugin directory. If you haven't yet written data to the table in the example, comment out the lines where it queries.
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4. To run the test, enter the following command with the following options:
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- `--lp` or `--file`: The line protocol to test
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- Optional: `--input-arguments`: A comma-delimited list of `<KEY>=<VALUE>` arguments for your plugin code

content/shared/v3-core-plugins/_index.md

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> [!Important]
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> #### Processing engine only works with Docker
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>
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> The Processing engine is currently supported only in Docker x86 environments. Non-Docker support is coming soon. The engine, API, and developer experience are actively evolving and may change. Join our [Discord](https://discord.gg/9zaNCW2PRT) for updates and feedback.
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Use the {{% product-name %}} Processing engine to run code and perform tasks
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for different database events.
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- **On Request**: Bound to the HTTP API `/api/v3/engine/<CUSTOM_PATH>` endpoint and triggered by a GET or POST request to the endpoint.
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## Activate the Processing engine
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To enable the Processing engine, start the {{% product-name %}} server with the `--plugin-dir` option and a path to your plugins directory (it doesn't need to exist yet)--for example:
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```bash
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```
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### Schedule Trigger Configuration
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Schedule plugins are set with a `trigger-spec` of `schedule:<cron_expression>` or `every:<duration>`. The `args` parameter can be used to pass configuration to the plugin. For example, if we wanted to use the system-metrics example from the Github repo and have it collect every 10 seconds we could use the following trigger definition:
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```shell
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```
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## On Request Plugin
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On Request plugins are triggered by a request to a specific endpoint under `/api/v3/engine`. The plugin will receive the local API, query parameters `Dict[str, str]`, request headers `Dict[str, str]`, request body (as bytes), and any arguments passed in the trigger definition. Here's an example of a simple On Request plugin:
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```python
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```
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### On Request Trigger Configuration
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On Request plugins are set with a `trigger-spec` of `request:<endpoint>`. The `args` parameter can be used to pass configuration to the plugin. For example, if we wanted the above plugin to run on the endpoint `/api/v3/engine/my_plugin`, we would use `request:my_plugin` as the `trigger-spec`.
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Trigger specs must be unique across all configured plugins, regardless of which database they are tied to, given the path is the same. Here's an example to create a request trigger tied to the "hello-world' path using a plugin in the plugin-dir:

content/shared/v3-enterprise-get-started/_index.md

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### Python plugins and the Processing engine
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> [!Important]
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> #### Processing engine only works with Docker
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>
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> The Processing engine is currently supported only in Docker x86 environments. Non-Docker support is coming soon. The engine, API, and developer experience are actively evolving and may change. Join our [Discord](https://discord.gg/9zaNCW2PRT) for updates and feedback.
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The InfluxDB 3 Processing engine is an embedded Python VM for running code inside the database to process and transform data.
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To use the Processing engine, you create [plugins](#plugin) and [triggers](#trigger).
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### Test, create, and trigger plugin code
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> [!Important]
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> #### Processing engine only works with Docker
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>
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> The Processing engine is currently supported only in Docker x86 environments. Non-Docker support is coming soon. The engine, API, and developer experience are actively evolving and may change. Join our [Discord](https://discord.gg/9zaNCW2PRT) for updates and feedback.
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##### Example: Python plugin for WAL flush
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```python
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To test a plugin, do the following:
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1. Create a _plugin directory_--for example, `/path/to/.influxdb/plugins`
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2. Make the plugin directory available to the Docker container (for example, using a bind mount)
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3. Run the Docker command to [start the server](#start-influxdb) and include the `--plugin-dir` option with your plugin directory path.
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4. Save the [preceding example code](#example-python-plugin) to a plugin file inside of the plugin directory. If you haven't yet written data to the table in the example, comment out the lines where it queries.
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5. To run the test, enter the following command with the following options:
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2. [Start the InfluxDB server](#start-influxdb) and include the `--plugin-dir` option with your plugin directory path.
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3. Save the [preceding example code](#example-python-plugin) to a plugin file inside of the plugin directory. If you haven't yet written data to the table in the example, comment out the lines where it queries.
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4. To run the test, enter the following command with the following options:
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- `--lp` or `--file`: The line protocol to test
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- Optional: `--input-arguments`: A comma-delimited list of `<KEY>=<VALUE>` arguments for your plugin code

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