From 629229b4676ae7492a84d173311ff67490e79077 Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Wed, 19 Jul 2023 13:11:22 -0400 Subject: [PATCH 01/16] add venv stuff --- examples/module/requirements.txt | 2 ++ examples/module/run.sh | 9 ++++++++- 2 files changed, 10 insertions(+), 1 deletion(-) create mode 100644 examples/module/requirements.txt diff --git a/examples/module/requirements.txt b/examples/module/requirements.txt new file mode 100644 index 000000000..cd74eca78 --- /dev/null +++ b/examples/module/requirements.txt @@ -0,0 +1,2 @@ +# add a version if viam should be pinned to a specific version +viam-sdk diff --git a/examples/module/run.sh b/examples/module/run.sh index 24212db8b..1a3922bcf 100755 --- a/examples/module/run.sh +++ b/examples/module/run.sh @@ -1,6 +1,13 @@ #!/bin/sh cd `dirname $0` +# Create a virtual environment to run our code +VENV="venv" +PYTHON="$VENV/bin/python" + +python3 -m venv $VENV +PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible + # Be sure to use `exec` so that termination signals reach the python process, # or handle forwarding termination signals manually -exec poetry run python -m src.main $@ +exec PYTHON -m src.main $@ From f9ce328082b3acfc8b25e9d2137ad6e47f017211 Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Sat, 22 Jul 2023 15:04:00 -0400 Subject: [PATCH 02/16] move stuff around --- docs/examples/example.ipynb | 385 ++++++++++-------- docs/examples/my_cool_arm.py | 20 +- examples/{module => complex_module}/README.md | 8 +- .../{module => complex_module}/buf.gen.yaml | 0 examples/{module => complex_module}/buf.lock | 0 examples/{module => complex_module}/buf.yaml | 0 examples/{module => complex_module}/client.py | 0 .../requirements.txt | 0 examples/{module => complex_module}/run.sh | 4 +- .../src/__init__.py | 0 .../src/arm/__init__.py | 0 .../src/arm/my_arm.py | 2 +- .../src/arm/my_arm_kinematics.json} | 2 +- .../src/gizmo/__init__.py | 0 .../src/gizmo/api.py | 0 .../src/gizmo/my_gizmo.py | 0 .../{module => complex_module}/src/main.py | 6 +- .../src/proto/__init__.py | 0 .../src/proto/gizmo.proto | 0 .../src/proto/gizmo_grpc.py | 0 .../src/proto/gizmo_pb2.py | 0 .../src/proto/gizmo_pb2.pyi | 0 .../src/proto/summation.proto | 0 .../src/proto/summation_grpc.py | 0 .../src/proto/summation_pb2.py | 0 .../src/proto/summation_pb2.pyi | 0 .../src/summation/__init__.py | 0 .../src/summation/api.py | 0 .../src/summation/my_summation.py | 0 examples/simple_module/README.md | 46 +++ examples/simple_module/client.py | 29 ++ examples/simple_module/requirements.txt | 2 + examples/simple_module/run.sh | 13 + examples/simple_module/src/main.py | 46 +++ 34 files changed, 373 insertions(+), 190 deletions(-) rename examples/{module => complex_module}/README.md (89%) rename examples/{module => complex_module}/buf.gen.yaml (100%) rename examples/{module => complex_module}/buf.lock (100%) rename examples/{module => complex_module}/buf.yaml (100%) rename examples/{module => complex_module}/client.py (100%) rename examples/{module => complex_module}/requirements.txt (100%) rename examples/{module => complex_module}/run.sh (65%) rename examples/{module => complex_module}/src/__init__.py (100%) rename examples/{module => complex_module}/src/arm/__init__.py (100%) rename examples/{module => complex_module}/src/arm/my_arm.py (97%) rename examples/{module/src/arm/xarm6_kinematics.json => complex_module/src/arm/my_arm_kinematics.json} (99%) rename examples/{module => complex_module}/src/gizmo/__init__.py (100%) rename examples/{module => complex_module}/src/gizmo/api.py (100%) rename examples/{module => complex_module}/src/gizmo/my_gizmo.py (100%) rename examples/{module => complex_module}/src/main.py (79%) rename examples/{module => complex_module}/src/proto/__init__.py (100%) rename examples/{module => complex_module}/src/proto/gizmo.proto (100%) rename examples/{module => complex_module}/src/proto/gizmo_grpc.py (100%) rename examples/{module => complex_module}/src/proto/gizmo_pb2.py (100%) rename examples/{module => complex_module}/src/proto/gizmo_pb2.pyi (100%) rename examples/{module => complex_module}/src/proto/summation.proto (100%) rename examples/{module => complex_module}/src/proto/summation_grpc.py (100%) rename examples/{module => complex_module}/src/proto/summation_pb2.py (100%) rename examples/{module => complex_module}/src/proto/summation_pb2.pyi (100%) rename examples/{module => complex_module}/src/summation/__init__.py (100%) rename examples/{module => complex_module}/src/summation/api.py (100%) rename examples/{module => complex_module}/src/summation/my_summation.py (100%) create mode 100644 examples/simple_module/README.md create mode 100644 examples/simple_module/client.py create mode 100644 examples/simple_module/requirements.txt create mode 100755 examples/simple_module/run.sh create mode 100644 examples/simple_module/src/main.py diff --git a/docs/examples/example.ipynb b/docs/examples/example.ipynb index cf7cca1a4..e03165c0a 100644 --- a/docs/examples/example.ipynb +++ b/docs/examples/example.ipynb @@ -1,9 +1,7 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "# Example usage\n", "\n", @@ -15,33 +13,29 @@ "## Connect as a client\n", "\n", "To connect to a robot as a client, you should instantiate an instance of a `RobotClient`" - ] + ], + "metadata": {}, + "attachments": {} }, { "cell_type": "code", "execution_count": 1, - "metadata": { - "tags": [ - "remove-input" - ] - }, - "outputs": [], "source": [ "# Please excuse the boilerplate\n", "%autoawait asyncio\n", "import warnings\n", "warnings.filterwarnings('ignore')" - ] + ], + "outputs": [], + "metadata": { + "tags": [ + "remove-input" + ] + } }, { "cell_type": "code", "execution_count": 2, - "metadata": { - "tags": [ - "hide-output" - ] - }, - "outputs": [], "source": [ "from viam import logging\n", "from viam.robot.client import RobotClient\n", @@ -53,27 +47,41 @@ " log_level=logging.FATAL\n", " )\n", " return await RobotClient.at_address('localhost:9091', options)" - ] + ], + "outputs": [], + "metadata": { + "tags": [ + "hide-output" + ] + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ "You can also create a `RobotClient` by providing an existing connection" - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 3, - "metadata": { - "tags": [ - "hide-output" - ] - }, + "source": [ + "from viam import logging\n", + "from viam.robot.client import RobotClient\n", + "from viam.rpc.dial import DialOptions, dial\n", + "\n", + "async def connect_with_channel() -> RobotClient:\n", + " async with await dial('localhost:9091', DialOptions(insecure=True, disable_webrtc=True)) as channel:\n", + " return await RobotClient.with_channel(channel, RobotClient.Options(refresh_interval=10, log_level=logging.FATAL))\n", + "\n", + "robot = await connect_with_channel()\n", + "print(robot.resource_names)\n", + "await robot.close()" + ], "outputs": [ { - "name": "stdout", "output_type": "stream", + "name": "stdout", "text": [ "[namespace: \"rdk\"\n", "type: \"component\"\n", @@ -127,36 +135,22 @@ ] } ], - "source": [ - "from viam import logging\n", - "from viam.robot.client import RobotClient\n", - "from viam.rpc.dial import DialOptions, dial\n", - "\n", - "async def connect_with_channel() -> RobotClient:\n", - " async with await dial('localhost:9091', DialOptions(insecure=True, disable_webrtc=True)) as channel:\n", - " return await RobotClient.with_channel(channel, RobotClient.Options(refresh_interval=10, log_level=logging.FATAL))\n", - "\n", - "robot = await connect_with_channel()\n", - "print(robot.resource_names)\n", - "await robot.close()" - ] + "metadata": { + "tags": [ + "hide-output" + ] + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Once you have a connected `RobotClient`, you can then obtain the robot's components by their name" - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 5, - "metadata": { - "tags": [ - "hide-output" - ] - }, - "outputs": [], "source": [ "from viam.components.camera import Camera\n", "from viam.media.video import CameraMimeType\n", @@ -168,45 +162,49 @@ "\n", "# Don't forget to close the robot when you're done!\n", "await robot.close()\n" - ] + ], + "outputs": [], + "metadata": { + "tags": [ + "hide-output" + ] + } }, { "cell_type": "code", "execution_count": 7, - "metadata": { - "tags": [ - "hide-output", - "remove-input" - ] - }, + "source": [ + "display(image)" + ], "outputs": [ { + "output_type": "display_data", "data": { "image/png": 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", "text/plain": [ "" ] }, - "metadata": {}, - "output_type": "display_data" + "metadata": {} } ], - "source": [ - "display(image)" - ] + "metadata": { + "tags": [ + "hide-output", + "remove-input" + ] + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ "You can also use the `RobotClient` to make service calls to the connected robot." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "from viam.services.vision import VisionClient\n", "\n", @@ -214,37 +212,39 @@ " robot = await connect_with_channel()\n", " vision = VisionClient.from_robot(robot)\n", " detections = await vision.get_detections_from_camera(\"camera_1\", \"detector_1\")" - ] + ], + "outputs": [], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "At the end, don't forget to close the connection" - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 5, - "metadata": {}, - "outputs": [], "source": [ "async def cleanup():\n", " await robot.close()" - ] + ], + "outputs": [], + "metadata": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "## Create custom modules\n", - "Make a modular resource from an existing resource. In this document, we will be going over subclassing existing resource types. To learn more about creating a new resource type, see the [Viam docs](https://docs.viam.com/extend/modular-resources/#code-your-module) and [module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/module).\n", + "Make a modular resource from an existing resource API. In this document, we will be going over subclassing existing resource APIs. To learn more about creating a new resource API, see the [Viam docs](https://docs.viam.com/extend/modular-resources/#code-your-module), and [complex module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module).\n", + "\n", + "The code below resembles the [simple module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/simple_module), so look there for the final, completed modular resource.\n", "\n", "The steps required in creating a modular resource and connecting it to a robot are:\n", - "1. **Subclass a resource and implement desired functions.** This will be your custom resource.\n", + "1. **Subclass a resource and implement desired functions.** This will be your custom resource model.\n", " - For functions that you do not wish to implement, you must at least define them by putting `pass` or `raise NotImplementedError()` in the function.\n", - "2. **Register a new model.** This will register the new modular resource into the `Registry`.\n", + "2. **Register a new model.** This will register the new modular resource model into the `Registry`.\n", "3. **Create an entry point file.** Create and start the new module.\n", "4. **Make the module executable.** This allows `viam-server` to access and execute the module.\n", "5. **Configure a modular resource.** Use the new module and instantiate a new resource to a robot!\n", @@ -252,7 +252,7 @@ "Knowing this, let's implement a custom resource.\n", " \n", "### 1. Subclass a resource\n", - "The SDK provides a wide array of resources to customize. You can browse through the API Reference to see the available resources. Subclass a resource and implement the required functions. You may leave the other methods unimplemented by putting `pass` or `raise NotImplementedError()` in the function.\n", + "The SDK provides a wide array of resource APIs to customize. You can browse through the API Reference to see the available resources. Subclass a resource and implement the required functions. You may leave the other methods unimplemented by putting `pass` or `raise NotImplementedError()` in the function.\n", "\n", "This example uses a `Sensor` as an example.\n", "\n", @@ -265,7 +265,6 @@ "from typing import Any, Dict, Mapping, Optional\n", "\n", "from viam.components.sensor import Sensor\n", - "from viam.operations import run_with_operation\n", "\n", "\n", "class MySensor(Sensor):\n", @@ -276,7 +275,7 @@ " wifi_signal = [x for x in content[2].split(\" \") if x != \"\"]\n", " return {\"link\": wifi_signal[2], \"level\": wifi_signal[3], \"noise\": wifi_signal[4]}\n", "\n", - "# Anything below this line is optional, but may come in handy for debugging and testing.\n", + "# Anything below this line is optional and will be replaced later, but may come in handy for debugging and testing.\n", "# To use, call `python wifi_sensor.py` in the command line while in the `src` directory.\n", "async def main():\n", " wifi=MySensor(name=\"wifi\")\n", @@ -288,15 +287,15 @@ "```\n", "\n", "You can view more component implementations in the [examples](https://github.com/viamrobotics/python-sdk/blob/main/examples/server/v1/components.py)." - ] + ], + "metadata": {}, + "attachments": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "### 2. Register the new modular resource\n", - "Now that we've created the modular resource, we must register the resource to the registry.\n", + "Now that we've created the modular resource model, we must register it to the registry.\n", "\n", "Define a [`Model`](https://docs.viam.com/extend/modular-resources/#models) name and a creator function in the resource. A creator function is a function that can create a resource given a config and map of dependencies.\n", "\n", @@ -327,37 +326,42 @@ " return sensor\n", "```\n", "\n", - "After the resource has a defined model and creator function, the resource must be registered to the `Registry`. This can be done using [`register_resource_creator()`](https://python.viam.dev/autoapi/viam/resource/registry/index.html#viam.resource.registry.Registry.register_resource_creator) and passing a [`ResourceCreatorRegistration`](https://python.viam.dev/autoapi/viam/resource/registry/index.html#viam.resource.registry.ResourceCreatorRegistration) object with the creator function as a parameter.\n", + "After the resource model has a defined model and creator function, the resource model must be registered to the `Registry`. This can be done using [`register_resource_creator()`](https://python.viam.dev/autoapi/viam/resource/registry/index.html#viam.resource.registry.Registry.register_resource_creator) and passing a [`ResourceCreatorRegistration`](https://python.viam.dev/autoapi/viam/resource/registry/index.html#viam.resource.registry.ResourceCreatorRegistration) object with the creator function as a parameter.\n", "\n", - "In the same `src` directory, create a new file named `__init__.py`. In it, call `Registry.register_resource_creator()` with the subtype of the resource that was subclassed, the model name, and a `ResourceCreatorRegistration` object with the creator function defined in the modular resource.\n", + "In the main function of `wifi_sensor.py`, call `Registry.register_resource_creator()` with the subtype of the resource that was subclassed, the model name, and a `ResourceCreatorRegistration` object with the creator function defined in the modular resource. In a more complex module, it makes sense to call the function in an `__init__.py` file in the same folder as the new resource model. See [here](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module/src/arm/__init__.py) for an example.\n", "\n", "```python\n", - "# wifi-sensor/src/__init__.py\n", - "from viam.components.sensor import Sensor\n", + "# wifi-sensor/src/wifi_sensor.py\n", "from viam.resource.registry import Registry, ResourceCreatorRegistration\n", - "from .wifi_sensor import MySensor\n", - "\n", + "from viam.components.sensor import Sensor\n", "\n", - "Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new))\n", - "```\n", + "async def main():\n", + " Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new))\n", + "```\n" + ], + "metadata": {}, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ "\n", "### 3. Create an entry point file\n", - "The module now has to be created and started. In the `src` directory, create a new file called `main.py`.\n", + "The module now has to be created and started. In the `wifi_sensor.py` file, update the main function to the following. In a more complex module, it makes sense to create an entirely new entrypoint file. See [here](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module/src/main.py) for an example.\n", "\n", "```python\n", - "# wifi-sensor/src/main.py\n", + "# wifi-sensor/src/wifi_sensor.py\n", "import asyncio\n", "\n", "from viam.module.module import Module\n", "from viam.components.sensor import Sensor\n", - "\n", - "from .wifi_sensor import MySensor \n", + "from viam.resource.registry import Registry, ResourceCreatorRegistration\n", "\n", "\n", "async def main():\n", - " \"\"\"This function creates and starts a new module, after adding all desired resources.\n", - " Resources must be pre-registered. For an example, see the `__init__.py` file.\n", - " \"\"\"\n", + " \"\"\"This function creates and starts a new module, after adding all desired resource models.\"\"\"\n", + " # first register your new resource creator!\n", + " Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new))\n", "\n", " module = Module.from_args()\n", " module.add_model_from_registry(Sensor.SUBTYPE, MySensor.MODEL)\n", @@ -366,42 +370,60 @@ "\n", "if __name__ == \"__main__\":\n", " asyncio.run(main())\n", - "```\n", - "\n", + "```" + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ "### 4. Make the module executable\n", "To add the module to your robot, you must provide it as an [executable file](https://docs.viam.com/extend/modular-resources/#make-your-module-executable) that [`viam-server` can access](https://docs.viam.com/extend/modular-resources/#make-sure-viam-server-can-access-your-executable).\n", "\n", "Dependencies for the module (including Viam SDK) have to be installed. In the `wifi-sensor` directory, create a new file called `requirements.txt` that has all your dependencies. For this example, add `viam-sdk` in `requirements.txt`.\n", "\n", "```\n", + "# add a version if viam should be pinned to a specific version\n", "viam-sdk\n", "```\n", "\n", - "One option with the Python SDK is to create a new shell script (`.sh`) that runs your module, which can also be used to install the dependencies. For example, in the `wifi-sensor` directory, add an `exec.sh` file:\n", + "One option with the Python SDK is to create a new shell script (`.sh`) that runs your module, which can also be used to install the dependencies. For example, in the `wifi-sensor` directory, add an `run.sh` file:\n", "\n", "```sh\n", "#!/bin/sh\n", "cd `dirname $0`\n", "\n", - "pip3 install -r requirements.txt\n", + "# Create a virtual environment to run our code\n", + "VENV=\"venv\"\n", + "PYTHON=\"$VENV/bin/python\"\n", + "\n", + "python3 -m venv $VENV\n", + "$PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible\n", + "\n", "\n", "# Be sure to use `exec` so that termination signals reach the python process,\n", "# or handle forwarding termination signals manually\n", - "exec python3 -m . $@\n", + "exec $PYTHON src/wifi-sensor.py $@\n", "```\n", "\n", - "**Please note that the filename has to be without the extension.** In this case, `.` would be replaced with `src.main`.\n", + "**Please note that a more complex module should be run as a Python module, meaning that the file extension `.py` has to be omitted. See [here](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module/run.sh) for an example.** \n", "\n", "To make this shell script executable, run this in the Terminal:\n", "\n", "```sudo chmod +x /```\n", "\n", - "`` would be `exec.sh`.\n", - "\n", + "`` would be `run.sh`.\n", + "\n" + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ "### 5. Configure a modular resource\n", "**NOTE:** *These instructions are for local development. Soon we will launch a `Registry` which will allow users to upload modules to app.viam.com directly. We will update the documentation with instructions on how to do that shortly.*\n", "\n", - "[Configure your new module](https://docs.viam.com/extend/modular-resources/#configure-your-module) on your robot by navigating to the **Config** tab of the robot's page on the Viam app, then click on the **Modules** subtab. Add the name of your module and the executable path. For our example, the path would be `/wifi-sensor/exec.sh`.\n", + "[Configure your new module](https://docs.viam.com/extend/modular-resources/#configure-your-module) on your robot by navigating to the **Config** tab of the robot's page on the Viam app, then click on the **Modules** subtab. Add the name of your module and the executable path. For our example, the path would be `/wifi-sensor/run.sh`.\n", "\n", "Once you have configured a module as part of your robot configuration, [configure your modular resource](https://docs.viam.com/extend/modular-resources/#configure-your-modular-resource) made available by that module by adding new components or services configured with your modular resources' new type or model. To instantiate a new resource from your module, specify the `type`, `model`, and `name` of your modular resource. This is a JSON example:\n", "\n", @@ -418,23 +440,22 @@ " ],\n", " \"modules\": [\n", " {\n", - " \"executable_path\": \"/wifi-sensor/exec.sh\",\n", + " \"executable_path\": \"/wifi-sensor/run.sh\",\n", " \"name\": \"wifi_sensor\"\n", " }\n", " ]\n", "}\n", "```\n" - ] + ], + "metadata": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "### Custom Modular Arm Example\n", "The following is an example of how to implement a custom modular arm. For further instructions, read the detailed `Sensor` example above. Our custom Arm will be extremely simple. Please note that the minimum set of endpoints you need to implement for an arm are `GetKinematics`, `GetJointPositions`, and `MoveToJointPositions`.\n", "\n", - "This arm example has a kinematics JSON file that contains its kinematics data, which can be found [here](https://github.com/viamrobotics/viam-python-sdk/blob/main/examples/module/src/arm/xarm6_kinematics.json). Save this file in the `src` directory under the name `xarm6_kinematics.json`.\n", + "This arm example contains a minimal kinematics model. For a full model, take a look [here](https://github.com/viamrobotics/viam-python-sdk/blob/main/complex_module/src/arm/my_arm_kinematics.json).\n", "\n", "Subclassing the `Arm` component and implementing the required functions:\n", "```python\n", @@ -459,6 +480,18 @@ " def __init__(self, name: str):\n", " # Starting joint positions\n", " self.joint_positions = JointPositions(values=[0, 0, 0, 0, 0, 0])\n", + "\n", + "\n", + " # Minimal working kinematics\n", + " self.kinematics = json.dumps(\n", + " {\n", + " \"name\": \"MyArm\",\n", + " \"links\": [{\"id\": \"base\", \"parent\": \"world\", \"translation\": {\"x\": 0, \"y\": 0, \"z\": 0}}],\n", + " \"joints\": [\n", + " {\"id\": \"waist\", \"type\": \"revolute\", \"parent\": \"base\", \"axis\": {\"x\": 0, \"y\": 0, \"z\": 1}, \"max\": 359, \"min\": -359}\n", + " ],\n", + " }\n", + " ).encode(\"utf-8\")\n", " super().__init__(name)\n", "\n", " @classmethod\n", @@ -500,11 +533,7 @@ " return not self.is_stopped\n", "\n", " async def get_kinematics(self, **kwargs) -> Tuple[KinematicsFileFormat.ValueType, bytes]:\n", - " dirname = os.path.dirname(__file__)\n", - " filepath = os.path.join(dirname, \"./xarm6_kinematics.json\")\n", - " with open(filepath, mode=\"rb\") as f:\n", - " file_data = f.read()\n", - " return (KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, file_data)\n", + " return KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, self.kinematics\n", "```\n", "\n", "Registering the modular resource:\n", @@ -544,12 +573,12 @@ "```\n", "\n", "Lastly, make the module executable and configure the module on your robot." - ] + ], + "metadata": {}, + "attachments": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "## Create custom remotes\n", "\n", @@ -569,18 +598,29 @@ "The SDK provides a wide array of components to customize. You can browse through the API Reference to see all of them, but for now we'll use an `Arm` as an example. Our custom Arm will be extremely simple -- it will only save and return the positions provided to it.\n", "\n", "Let's start by creating a directory called `my-python-robot`. Inside of that directory, create a file called `my_cool_arm.py`. The contents of `my_cool_arm.py` should be as follows:" - ] + ], + "metadata": {}, + "attachments": {} }, { "cell_type": "code", "execution_count": 2, - "metadata": { - "tags": [ - "remove-input" - ] - }, + "source": [ + "from pygments import highlight\n", + "from pygments.lexers import PythonLexer\n", + "from pygments.formatters import HtmlFormatter\n", + "import IPython\n", + "with open('my_cool_arm.py') as f:\n", + " code = f.read()\n", + "\n", + "formatter = HtmlFormatter()\n", + "IPython.display.HTML('{}'.format(\n", + " formatter.get_style_defs('.highlight'),\n", + " highlight(code, PythonLexer(), formatter)))" + ], "outputs": [ { + "output_type": "execute_result", "data": { "text/html": [ "
# my-python-robot/my_cool_arm.py\n",
        "\n",
        "import asyncio\n",
-       "import os\n",
+       "import json\n",
        "from typing import Any, Dict, Optional, Tuple\n",
+       "\n",
        "from viam.components.arm import Arm, JointPositions, KinematicsFileFormat, Pose\n",
        "from viam.operations import run_with_operation\n",
        "\n",
@@ -683,6 +724,17 @@
        "        # Starting joint positions\n",
        "        self.joint_positions = JointPositions(values=[0, 0, 0, 0, 0, 0])\n",
        "        self.is_stopped = True\n",
+       "\n",
+       "        # Minimal working kinematics model\n",
+       "        self.kinematics = json.dumps(\n",
+       "            {\n",
+       "                "name": "MyArm",\n",
+       "                "links": [{"id": "base", "parent": "world", "translation": {"x": 0, "y": 0, "z": 0}}],\n",
+       "                "joints": [\n",
+       "                    {"id": "waist", "type": "revolute", "parent": "base", "axis": {"x": 0, "y": 0, "z": 1}, "max": 359, "min": -359}\n",
+       "                ],\n",
+       "            }\n",
+       "        ).encode("utf-8")\n",
        "        super().__init__(name)\n",
        "\n",
        "    async def get_end_position(self, extra: Optional[Dict[str, Any]] = None, **kwargs) -> Pose:\n",
@@ -739,73 +791,48 @@
        "        return not self.is_stopped\n",
        "\n",
        "    async def get_kinematics(self, **kwargs) -> Tuple[KinematicsFileFormat.ValueType, bytes]:\n",
-       "        dirname = os.path.dirname(__file__)\n",
-       "        filepath = os.path.join(dirname, "./xarm6_kinematics.json")\n",
-       "        with open(filepath, mode="rb") as f:\n",
-       "            file_data = f.read()\n",
-       "        return (KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, file_data)\n",
+       "        return KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, self.kinematics\n",
        "
\n" ], "text/plain": [ "" ] }, - "execution_count": 2, "metadata": {}, - "output_type": "execute_result" + "execution_count": 2 } ], - "source": [ - "from pygments import highlight\n", - "from pygments.lexers import PythonLexer\n", - "from pygments.formatters import HtmlFormatter\n", - "import IPython\n", - "with open('my_cool_arm.py') as f:\n", - " code = f.read()\n", - "\n", - "formatter = HtmlFormatter()\n", - "IPython.display.HTML('{}'.format(\n", - " formatter.get_style_defs('.highlight'),\n", - " highlight(code, PythonLexer(), formatter)))" - ] + "metadata": { + "tags": [ + "remove-input" + ] + } }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "You can view more component implementations in the [examples](https://github.com/viamrobotics/python-sdk/blob/main/examples/server/v1/components.py).\n", "\n", - "This arm example has a kinematics JSON file that contains its kinematics data, which can be found [here](https://github.com/viamrobotics/viam-python-sdk/blob/main/examples/module/src/arm/xarm6_kinematics.json). Save this file in the `my-python-robot` directory under the name `xarm6_kinematics.json`" - ] + "This arm example contains a minimal kinematics model. For a full model, take a look [here](https://github.com/viamrobotics/viam-python-sdk/blob/main/complex_module/src/arm/my_arm_kinematics.json)." + ], + "metadata": {}, + "attachments": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "### 2. Register the custom component\n", "\n", "Now that we've created the custom component, we must register it so that it will be visible to any robots connecting to it. This is done by creating an `RPC` server and adding `MyCoolArm` as a connected component. This `RPC` server will receive gRPC requests from the Viam Server or any other connections and forward those requests to your custom component.\n", "\n", "In the same `my-python-robot` directory, create a new file called `main.py`." - ] + ], + "metadata": {}, + "attachments": {} }, { "cell_type": "code", "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/vh/04mycgp163125hlq8k9bkl8w0000gn/T/ipykernel_50114/2037726754.py:15: RuntimeWarning: coroutine 'main' was never awaited\n", - " pass\n", - "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n" - ] - } - ], "source": [ "# my-python-robot/main.py\n", "\n", @@ -823,12 +850,22 @@ " asyncio.run(main())\n", " except:\n", " pass" - ] + ], + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/var/folders/vh/04mycgp163125hlq8k9bkl8w0000gn/T/ipykernel_50114/2037726754.py:15: RuntimeWarning: coroutine 'main' was never awaited\n", + " pass\n", + "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n" + ] + } + ], + "metadata": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "### 3. Start the Server and add it as a Remote\n", "\n", @@ -884,12 +921,12 @@ " }\n", "]\n", "```" - ] + ], + "metadata": {}, + "attachments": {} }, { - "attachments": {}, "cell_type": "markdown", - "metadata": {}, "source": [ "## Operations\n", "\n", @@ -1073,9 +1110,8 @@ "metadata": { "celltoolbar": "Tags", "kernelspec": { - "display_name": "viam-sdk-1ZkIuRmo-py3.11", - "language": "python", - "name": "python3" + "name": "python3", + "display_name": "Python 3.10.7 64-bit ('viam-sdk-vMF2PqL3-py3.10': poetry)" }, "language_info": { "codemirror_mode": { @@ -1087,12 +1123,15 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.11" }, "vscode": { "interpreter": { "hash": "3dcf3a0dc186f3f37ed02c43aacb5aba79c21834e2f1b6d3d1f9d9c84c46ec17" } + }, + "interpreter": { + "hash": "f23d0e37baf6e16775d141979f903b614c23312866692f80dbad6fe3f7e24d7b" } }, "nbformat": 4, diff --git a/docs/examples/my_cool_arm.py b/docs/examples/my_cool_arm.py index 1c4a182c6..be63c814a 100644 --- a/docs/examples/my_cool_arm.py +++ b/docs/examples/my_cool_arm.py @@ -1,8 +1,9 @@ # my-python-robot/my_cool_arm.py import asyncio -import os +import json from typing import Any, Dict, Optional, Tuple + from viam.components.arm import Arm, JointPositions, KinematicsFileFormat, Pose from viam.operations import run_with_operation @@ -25,6 +26,17 @@ def __init__(self, name: str): # Starting joint positions self.joint_positions = JointPositions(values=[0, 0, 0, 0, 0, 0]) self.is_stopped = True + + # Minimal working kinematics model + self.kinematics = json.dumps( + { + "name": "MyArm", + "links": [{"id": "base", "parent": "world", "translation": {"x": 0, "y": 0, "z": 0}}], + "joints": [ + {"id": "waist", "type": "revolute", "parent": "base", "axis": {"x": 0, "y": 0, "z": 1}, "max": 359, "min": -359} + ], + } + ).encode("utf-8") super().__init__(name) async def get_end_position(self, extra: Optional[Dict[str, Any]] = None, **kwargs) -> Pose: @@ -81,8 +93,4 @@ async def is_moving(self) -> bool: return not self.is_stopped async def get_kinematics(self, **kwargs) -> Tuple[KinematicsFileFormat.ValueType, bytes]: - dirname = os.path.dirname(__file__) - filepath = os.path.join(dirname, "./xarm6_kinematics.json") - with open(filepath, mode="rb") as f: - file_data = f.read() - return (KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, file_data) + return KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, self.kinematics diff --git a/examples/module/README.md b/examples/complex_module/README.md similarity index 89% rename from examples/module/README.md rename to examples/complex_module/README.md index 0d539d96a..bba0ab9a5 100644 --- a/examples/module/README.md +++ b/examples/complex_module/README.md @@ -1,4 +1,4 @@ -# VIAM Module Example +# VIAM Complex Module Example This example goes through how to create custom modular resources using Viam's python SDK, and how to connect it to a Robot. This is a limited document. For a more in-depth understanding of modules, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). @@ -6,7 +6,7 @@ This is a limited document. For a more in-depth understanding of modules, see th ## Purpose Modular resources allows you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. -For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). +For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). For a simpler example, take a look at the [simple module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/simple_module), which only contains one custom resource model in one file. ## Project structure The definition of the new resources are in the `src` directory. Within this directory are the `proto`, `gizmo`, `arm`, and `summation` subdirectories. @@ -26,7 +26,7 @@ Outside the `src` directory, there is the `client.py` file. This can be used to ## How to use These steps assume that you have a robot available at [app.viam.com](app.viam.com). -The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, this could be `/home/viam-python-sdk/examples/module/run.sh`. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. +The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, this could be `/home/viam-python-sdk/examples/complex_module/run.sh`. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. Once the module has been added to your robot, you can then add a component that uses the `MyGizmo` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. You can add a service that uses the `MySum` model in a similar manner. @@ -80,7 +80,7 @@ An example configuration for an Arm component, a Gizmo component, and a Summatio "modules": [ { "name": "my-module", - "executable_path": "/home/viam-python-sdk/examples/module/run.sh" + "executable_path": "/home/viam-python-sdk/examples/complex_module/run.sh" } ] } diff --git a/examples/module/buf.gen.yaml b/examples/complex_module/buf.gen.yaml similarity index 100% rename from examples/module/buf.gen.yaml rename to examples/complex_module/buf.gen.yaml diff --git a/examples/module/buf.lock b/examples/complex_module/buf.lock similarity index 100% rename from examples/module/buf.lock rename to examples/complex_module/buf.lock diff --git a/examples/module/buf.yaml b/examples/complex_module/buf.yaml similarity index 100% rename from examples/module/buf.yaml rename to examples/complex_module/buf.yaml diff --git a/examples/module/client.py b/examples/complex_module/client.py similarity index 100% rename from examples/module/client.py rename to examples/complex_module/client.py diff --git a/examples/module/requirements.txt b/examples/complex_module/requirements.txt similarity index 100% rename from examples/module/requirements.txt rename to examples/complex_module/requirements.txt diff --git a/examples/module/run.sh b/examples/complex_module/run.sh similarity index 65% rename from examples/module/run.sh rename to examples/complex_module/run.sh index 1a3922bcf..5788d422a 100755 --- a/examples/module/run.sh +++ b/examples/complex_module/run.sh @@ -6,8 +6,8 @@ VENV="venv" PYTHON="$VENV/bin/python" python3 -m venv $VENV -PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible +$PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible # Be sure to use `exec` so that termination signals reach the python process, # or handle forwarding termination signals manually -exec PYTHON -m src.main $@ +exec $PYTHON -m src.main $@ diff --git a/examples/module/src/__init__.py b/examples/complex_module/src/__init__.py similarity index 100% rename from examples/module/src/__init__.py rename to examples/complex_module/src/__init__.py diff --git a/examples/module/src/arm/__init__.py b/examples/complex_module/src/arm/__init__.py similarity index 100% rename from examples/module/src/arm/__init__.py rename to examples/complex_module/src/arm/__init__.py diff --git a/examples/module/src/arm/my_arm.py b/examples/complex_module/src/arm/my_arm.py similarity index 97% rename from examples/module/src/arm/my_arm.py rename to examples/complex_module/src/arm/my_arm.py index bf15ecde0..d1c8caa25 100644 --- a/examples/module/src/arm/my_arm.py +++ b/examples/complex_module/src/arm/my_arm.py @@ -92,7 +92,7 @@ async def is_moving(self) -> bool: async def get_kinematics(self, **kwargs) -> Tuple[KinematicsFileFormat.ValueType, bytes]: dirname = os.path.dirname(__file__) - filepath = os.path.join(dirname, "./xarm6_kinematics.json") + filepath = os.path.join(dirname, "./my_arm_kinematics.json") with open(filepath, mode="rb") as f: file_data = f.read() return (KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, file_data) diff --git a/examples/module/src/arm/xarm6_kinematics.json b/examples/complex_module/src/arm/my_arm_kinematics.json similarity index 99% rename from examples/module/src/arm/xarm6_kinematics.json rename to examples/complex_module/src/arm/my_arm_kinematics.json index cb4c8af96..2d38086a9 100644 --- a/examples/module/src/arm/xarm6_kinematics.json +++ b/examples/complex_module/src/arm/my_arm_kinematics.json @@ -1,5 +1,5 @@ { - "name": "xArm6", + "name": "MyArm", "links": [ { "id": "base", diff --git a/examples/module/src/gizmo/__init__.py b/examples/complex_module/src/gizmo/__init__.py similarity index 100% rename from examples/module/src/gizmo/__init__.py rename to examples/complex_module/src/gizmo/__init__.py diff --git a/examples/module/src/gizmo/api.py b/examples/complex_module/src/gizmo/api.py similarity index 100% rename from examples/module/src/gizmo/api.py rename to examples/complex_module/src/gizmo/api.py diff --git a/examples/module/src/gizmo/my_gizmo.py b/examples/complex_module/src/gizmo/my_gizmo.py similarity index 100% rename from examples/module/src/gizmo/my_gizmo.py rename to examples/complex_module/src/gizmo/my_gizmo.py diff --git a/examples/module/src/main.py b/examples/complex_module/src/main.py similarity index 79% rename from examples/module/src/main.py rename to examples/complex_module/src/main.py index 7532c3592..cb1af4e47 100644 --- a/examples/module/src/main.py +++ b/examples/complex_module/src/main.py @@ -3,14 +3,14 @@ from viam.module.module import Module from viam.components.arm import Arm -from .arm import MyArm +from .arm.my_arm import MyArm from .gizmo import Gizmo, MyGizmo from .summation import MySummationService, SummationService async def main(): - """This function creates and starts a new module, after adding all desired resources. - Resources must be pre-registered. For an example, see the `gizmo.__init__.py` file. + """This function creates and starts a new module, after adding all desired resource models. + Resource models must be pre-registered. For an example, see the `gizmo.__init__.py` file. """ module = Module.from_args() diff --git a/examples/module/src/proto/__init__.py b/examples/complex_module/src/proto/__init__.py similarity index 100% rename from examples/module/src/proto/__init__.py rename to examples/complex_module/src/proto/__init__.py diff --git a/examples/module/src/proto/gizmo.proto b/examples/complex_module/src/proto/gizmo.proto similarity index 100% rename from examples/module/src/proto/gizmo.proto rename to examples/complex_module/src/proto/gizmo.proto diff --git a/examples/module/src/proto/gizmo_grpc.py b/examples/complex_module/src/proto/gizmo_grpc.py similarity index 100% rename from examples/module/src/proto/gizmo_grpc.py rename to examples/complex_module/src/proto/gizmo_grpc.py diff --git a/examples/module/src/proto/gizmo_pb2.py b/examples/complex_module/src/proto/gizmo_pb2.py similarity index 100% rename from examples/module/src/proto/gizmo_pb2.py rename to examples/complex_module/src/proto/gizmo_pb2.py diff --git a/examples/module/src/proto/gizmo_pb2.pyi b/examples/complex_module/src/proto/gizmo_pb2.pyi similarity index 100% rename from examples/module/src/proto/gizmo_pb2.pyi rename to examples/complex_module/src/proto/gizmo_pb2.pyi diff --git a/examples/module/src/proto/summation.proto b/examples/complex_module/src/proto/summation.proto similarity index 100% rename from examples/module/src/proto/summation.proto rename to examples/complex_module/src/proto/summation.proto diff --git a/examples/module/src/proto/summation_grpc.py b/examples/complex_module/src/proto/summation_grpc.py similarity index 100% rename from examples/module/src/proto/summation_grpc.py rename to examples/complex_module/src/proto/summation_grpc.py diff --git a/examples/module/src/proto/summation_pb2.py b/examples/complex_module/src/proto/summation_pb2.py similarity index 100% rename from examples/module/src/proto/summation_pb2.py rename to examples/complex_module/src/proto/summation_pb2.py diff --git a/examples/module/src/proto/summation_pb2.pyi b/examples/complex_module/src/proto/summation_pb2.pyi similarity index 100% rename from examples/module/src/proto/summation_pb2.pyi rename to examples/complex_module/src/proto/summation_pb2.pyi diff --git a/examples/module/src/summation/__init__.py b/examples/complex_module/src/summation/__init__.py similarity index 100% rename from examples/module/src/summation/__init__.py rename to examples/complex_module/src/summation/__init__.py diff --git a/examples/module/src/summation/api.py b/examples/complex_module/src/summation/api.py similarity index 100% rename from examples/module/src/summation/api.py rename to examples/complex_module/src/summation/api.py diff --git a/examples/module/src/summation/my_summation.py b/examples/complex_module/src/summation/my_summation.py similarity index 100% rename from examples/module/src/summation/my_summation.py rename to examples/complex_module/src/summation/my_summation.py diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md new file mode 100644 index 000000000..741312f8b --- /dev/null +++ b/examples/simple_module/README.md @@ -0,0 +1,46 @@ +# VIAM Simple Module Example +This example goes through how to create custom modular resources using Viam's python SDK, and how to connect it to a Robot. + +This is a limited document. For a more in-depth understanding of modules, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). + +## Purpose +Modular resources allows you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. + +For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). For a more complex example, take a look at the [complex module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module), which only contains multiple new APIs and custom resource models. + +## Project structure +The definition of the new resources are in the `main` file of the `src` directory. + +The `main.py` file contains the definition of a new sensor model and then registers it. It then creates and starts a module. This file is called by the `run.sh` script, which is the entrypoint for this module. Read further to learn how to connect this module to your robot. + +Outside the `src` directory, there is the `client.py` file. This can be used to test the module once it's connected to the robot. You will have to update the credentials and robot address in that file. + +## How to use +These steps assume that you have a robot available at [app.viam.com](app.viam.com). + +The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, this could be `/home/viam-python-sdk/examples/simple_module/run.sh`. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. + +Once the module has been added to your robot, you can then add a component that uses the `MySensor` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. + +An example configuration for a Sensor component could look like this: +```json +{ + "components": [ + { + "name": "sensor1", + "type": "sensor", + "model": "acme:demo:mysensor", + "attributes": {}, + "depends_on": [] + } + ], + "modules": [ + { + "name": "my-module", + "executable_path": "/home/viam-python-sdk/examples/simple_module/run.sh" + } + ] +} +``` + +After the robot has started and connected to the module, you can use the provided `client.py` to connect to your robot and make calls to your custom, modular resources. diff --git a/examples/simple_module/client.py b/examples/simple_module/client.py new file mode 100644 index 000000000..d9bceba27 --- /dev/null +++ b/examples/simple_module/client.py @@ -0,0 +1,29 @@ +import asyncio + +from viam import logging +from viam.robot.client import RobotClient +from viam.rpc.dial import Credentials, DialOptions +from viam.components.sensor import Sensor + + +async def connect(): + creds = Credentials(type="", payload="") + opts = RobotClient.Options(refresh_interval=0, dial_options=DialOptions(credentials=creds), log_level=logging.DEBUG) + return await RobotClient.at_address("", opts) + + +async def main(): + robot = await connect() + + print("Resources:") + print(robot.resource_names) + + sensor = Sensor.from_robot(robot, name="sensor1") + reading = await sensor.get_readings() + print(f"The reading is {reading}") + + await robot.close() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/simple_module/requirements.txt b/examples/simple_module/requirements.txt new file mode 100644 index 000000000..cd74eca78 --- /dev/null +++ b/examples/simple_module/requirements.txt @@ -0,0 +1,2 @@ +# add a version if viam should be pinned to a specific version +viam-sdk diff --git a/examples/simple_module/run.sh b/examples/simple_module/run.sh new file mode 100755 index 000000000..6651644c4 --- /dev/null +++ b/examples/simple_module/run.sh @@ -0,0 +1,13 @@ +#!/bin/sh +cd `dirname $0` + +# Create a virtual environment to run our code +VENV="venv" +PYTHON="$VENV/bin/python" + +python3 -m venv $VENV +$PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible + +# Be sure to use `exec` so that termination signals reach the python process, +# or handle forwarding termination signals manually +exec $PYTHON src/main.py $@ diff --git a/examples/simple_module/src/main.py b/examples/simple_module/src/main.py new file mode 100644 index 000000000..8a5ec01d4 --- /dev/null +++ b/examples/simple_module/src/main.py @@ -0,0 +1,46 @@ +import asyncio +from typing import Any, ClassVar, Dict, Mapping, Optional + +from typing_extensions import Self + +from viam.components.sensor import Sensor +from viam.module.module import Module +from viam.proto.app.robot import ComponentConfig +from viam.proto.common import ResourceName +from viam.resource.base import ResourceBase +from viam.resource.registry import Registry, ResourceCreatorRegistration +from viam.resource.types import Model, ModelFamily +from viam.utils import ValueTypes + + +class MySensor(Sensor): + # Subclass the Viam Sensor component and implement the required functions + MODEL: ClassVar[Model] = Model(ModelFamily("acme", "demo"), "mysensor") + + def __init__(self, name: str): + super().__init__(name) + + @classmethod + def new(cls, config: ComponentConfig, dependencies: Mapping[ResourceName, ResourceBase]) -> Self: + sensor = cls(config.name) + return sensor + + async def get_readings(self, extra: Optional[Dict[str, Any]] = None, **kwargs) -> Mapping[str, Any]: + return {"signal": 1} + + async def do_command(self, command: Mapping[str, ValueTypes], *, timeout: Optional[float] = None, **kwargs) -> Mapping[str, ValueTypes]: + return command + + +async def main(): + """This function creates and starts a new module, after adding all desired resource models.""" + # first register your new resource creator! + Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new)) + + module = Module.from_args() + module.add_model_from_registry(Sensor.SUBTYPE, MySensor.MODEL) + await module.start() + + +if __name__ == "__main__": + asyncio.run(main()) From c435077720e459ad7125c7e959ee66e19920792a Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Sat, 22 Jul 2023 15:16:57 -0400 Subject: [PATCH 03/16] update arm example --- docs/examples/example.ipynb | 135 ++++++++++++++++-------------------- 1 file changed, 58 insertions(+), 77 deletions(-) diff --git a/docs/examples/example.ipynb b/docs/examples/example.ipynb index e03165c0a..6fc2c5d9e 100644 --- a/docs/examples/example.ipynb +++ b/docs/examples/example.ipynb @@ -359,8 +359,9 @@ "\n", "\n", "async def main():\n", - " \"\"\"This function creates and starts a new module, after adding all desired resource models.\"\"\"\n", - " # first register your new resource creator!\n", + " \"\"\"This function creates and starts a new module, after adding all desired resources.\n", + " Resource models must be registered to the resource registry before the module adds it.\n", + " \"\"\"\n", " Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new))\n", "\n", " module = Module.from_args()\n", @@ -466,10 +467,12 @@ "from typing_extensions import Self\n", "\n", "from viam.components.arm import Arm, JointPositions, KinematicsFileFormat, Pose\n", + "from viam.module.module import Module\n", "from viam.operations import run_with_operation\n", "from viam.proto.app.robot import ComponentConfig\n", "from viam.proto.common import ResourceName\n", "from viam.resource.base import ResourceBase\n", + "from viam.resource.registry import Registry, ResourceCreatorRegistration\n", "from viam.resource.types import Model, ModelFamily\n", "\n", "\n", @@ -534,35 +537,12 @@ "\n", " async def get_kinematics(self, **kwargs) -> Tuple[KinematicsFileFormat.ValueType, bytes]:\n", " return KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, self.kinematics\n", - "```\n", - "\n", - "Registering the modular resource:\n", - "```python\n", - "# modular-arm/src/__init__.py\n", - "from viam.components.arm import Arm\n", - "from viam.resource.registry import Registry, ResourceCreatorRegistration\n", - "from .my_modular_arm import MyModularArm\n", - "\n", - "\n", - "Registry.register_resource_creator(Arm.SUBTYPE, MyModularArm.MODEL, ResourceCreatorRegistration(MyModularArm.new))\n", - "```\n", - "\n", - "Creating an entry point file to create and start the module:\n", - "```python\n", - "# modular-arm/src/main.py\n", - "import asyncio\n", - "\n", - "from viam.module.module import Module\n", - "from viam.components.arm import Arm\n", - "\n", - "from .my_modular_arm import MyModularArm \n", - "\n", "\n", "async def main():\n", " \"\"\"This function creates and starts a new module, after adding all desired resources.\n", - " Resources must be pre-registered. For an example, see the `__init__.py` file.\n", + " Resource models must be registered to the resource registry before the module adds it.\n", " \"\"\"\n", - "\n", + " Registry.register_resource_creator(Arm.SUBTYPE, MyModularArm.MODEL, ResourceCreatorRegistration(MyModularArm.new))\n", " module = Module.from_args()\n", " module.add_model_from_registry(Arm.SUBTYPE, MyModularArm.MODEL)\n", " await module.start()\n", @@ -935,24 +915,21 @@ "In order to take advantage of operations, you should wrap the component method with the `run_with_operation` decorator from the `viam.operations` package. Each component has a function, `get_operation(kwargs: Mapping[str, Any]) -> Operation`, that will return an Operation that will tell us if the operation is ever cancelled, allowing us to clean up any long running tasks, close connections, etc.\n", "\n", "It is extremely important that we check the `Operation` status, as this not only prevents any unnecessary resource usage, but also allows us to respond to urgent cancellation requests and stop components' motion." - ] + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "## Connect as a client to app\n", "\n", "To connect to app as a client and make calls to the data API, you should instantiate an instance of an `AppClient` and retrieve its `DataClient` member." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 1, - "metadata": { - "tags": [] - }, - "outputs": [], "source": [ "from viam.rpc.dial import DialOptions, Credentials\n", "from viam.app.client import AppClient\n", @@ -966,24 +943,22 @@ " )\n", " )\n", " return await AppClient.create(dial_options)" - ] + ], + "outputs": [], + "metadata": { + "tags": [] + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ "Once you have a connected `AppClient`, you can then obtain a `DataClient` as a property." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 2, - "metadata": { - "tags": [ - "remove-input" - ] - }, - "outputs": [], "source": [ "# Hidden.\n", "from typing_extensions import Self\n", @@ -1004,41 +979,37 @@ " self._channel.close()\n", "\n", "app_client = await MockAppClient.create_app_client()" - ] + ], + "outputs": [], + "metadata": { + "tags": [ + "remove-input" + ] + } }, { "cell_type": "code", "execution_count": 3, + "source": [ + "data_client = app_client.data_client" + ], + "outputs": [], "metadata": { "tags": [ "hide-output" ] - }, - "outputs": [], - "source": [ - "data_client = app_client.data_client" - ] + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ "This `DataClient` can be used to make method calls that retrieve data from app." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[{'IsPowered': False, 'PowerPct': 0.0}, {'IsPowered': False, 'PowerPct': 0.0}, {'Position': 0.0}]\n" - ] - } - ], "source": [ "from datetime import datetime\n", "\n", @@ -1058,24 +1029,28 @@ "\n", "data = await data_client.tabular_data_by_filter(filter=left_motor_filter)\n", "print(data)" - ] + ], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "[{'IsPowered': False, 'PowerPct': 0.0}, {'IsPowered': False, 'PowerPct': 0.0}, {'Position': 0.0}]\n" + ] + } + ], + "metadata": {} }, { "cell_type": "markdown", - "metadata": {}, "source": [ "You can also use your `DataClient` to upload data to app." - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 6, - "metadata": { - "tags": [ - "hide-output" - ] - }, - "outputs": [], "source": [ "await data_client.tabular_data_capture_upload(\n", " part_id='',\n", @@ -1087,31 +1062,37 @@ " data_request_times=None,\n", " tabular_data=[{'PowerPCT': 0, 'IsPowered': False}, {'PowerPCT': 10, 'IsPowered': True}]\n", ")" - ] + ], + "outputs": [], + "metadata": { + "tags": [ + "hide-output" + ] + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ "At the end, you may close the connection" - ] + ], + "metadata": {} }, { "cell_type": "code", "execution_count": 7, - "metadata": {}, - "outputs": [], "source": [ "async def cleanup():\n", " await app_client.close()" - ] + ], + "outputs": [], + "metadata": {} } ], "metadata": { "celltoolbar": "Tags", "kernelspec": { "name": "python3", - "display_name": "Python 3.10.7 64-bit ('viam-sdk-vMF2PqL3-py3.10': poetry)" + "display_name": "Python 3.10.7 64-bit" }, "language_info": { "codemirror_mode": { From 875f3a9325c6bb6b3d7ae4d08f0e4631d84f4955 Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Sat, 22 Jul 2023 15:24:18 -0400 Subject: [PATCH 04/16] more updates --- docs/examples/example.ipynb | 10 +++++----- examples/simple_module/src/main.py | 5 +++-- 2 files changed, 8 insertions(+), 7 deletions(-) diff --git a/docs/examples/example.ipynb b/docs/examples/example.ipynb index 6fc2c5d9e..8bdb0733a 100644 --- a/docs/examples/example.ipynb +++ b/docs/examples/example.ipynb @@ -359,8 +359,8 @@ "\n", "\n", "async def main():\n", - " \"\"\"This function creates and starts a new module, after adding all desired resources.\n", - " Resource models must be registered to the resource registry before the module adds it.\n", + " \"\"\"This function creates and starts a new module, after adding all desired resource model.\n", + " Resource creators must be registered to the resource registry before the module adds the resource model.\n", " \"\"\"\n", " Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new))\n", "\n", @@ -539,8 +539,8 @@ " return KinematicsFileFormat.KINEMATICS_FILE_FORMAT_SVA, self.kinematics\n", "\n", "async def main():\n", - " \"\"\"This function creates and starts a new module, after adding all desired resources.\n", - " Resource models must be registered to the resource registry before the module adds it.\n", + " \"\"\"This function creates and starts a new module, after adding all desired resource model.\n", + " Resource creators must be registered to the resource registry before the module adds the resource model.\n", " \"\"\"\n", " Registry.register_resource_creator(Arm.SUBTYPE, MyModularArm.MODEL, ResourceCreatorRegistration(MyModularArm.new))\n", " module = Module.from_args()\n", @@ -1117,4 +1117,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/examples/simple_module/src/main.py b/examples/simple_module/src/main.py index 8a5ec01d4..3e9bf1f72 100644 --- a/examples/simple_module/src/main.py +++ b/examples/simple_module/src/main.py @@ -33,8 +33,9 @@ async def do_command(self, command: Mapping[str, ValueTypes], *, timeout: Option async def main(): - """This function creates and starts a new module, after adding all desired resource models.""" - # first register your new resource creator! + """This function creates and starts a new module, after adding all desired resource model. + Resource creators must be registered to the resource registry before the module adds the resource model. + """ Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new)) module = Module.from_args() From 9c006d4afa41d8d9c9fdb199fe601993e77ab4bd Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Sat, 22 Jul 2023 15:34:29 -0400 Subject: [PATCH 05/16] notebook shenanigans --- docs/examples/example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/examples/example.ipynb b/docs/examples/example.ipynb index 8bdb0733a..727dc21bb 100644 --- a/docs/examples/example.ipynb +++ b/docs/examples/example.ipynb @@ -1057,7 +1057,7 @@ " component_type='rdk:component:motor',\n", " component_name='left_motor',\n", " method_name='IsPowered',\n", - " method_parameters=None,\n", + " method_parameters=None\n", " tags=[\"tag_1\", \"tag_2\"],\n", " data_request_times=None,\n", " tabular_data=[{'PowerPCT': 0, 'IsPowered': False}, {'PowerPCT': 10, 'IsPowered': True}]\n", From cf958f8acb2ea914f2fc582a908abcce6d4e1b07 Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Sat, 22 Jul 2023 15:38:39 -0400 Subject: [PATCH 06/16] undo --- docs/examples/example.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/examples/example.ipynb b/docs/examples/example.ipynb index 727dc21bb..8bdb0733a 100644 --- a/docs/examples/example.ipynb +++ b/docs/examples/example.ipynb @@ -1057,7 +1057,7 @@ " component_type='rdk:component:motor',\n", " component_name='left_motor',\n", " method_name='IsPowered',\n", - " method_parameters=None\n", + " method_parameters=None,\n", " tags=[\"tag_1\", \"tag_2\"],\n", " data_request_times=None,\n", " tabular_data=[{'PowerPCT': 0, 'IsPowered': False}, {'PowerPCT': 10, 'IsPowered': True}]\n", From 03836a0f09854af4b78287051d206483ccb82b9f Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Mon, 24 Jul 2023 15:30:50 -0400 Subject: [PATCH 07/16] spelling --- examples/simple_module/src/main.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/src/main.py b/examples/simple_module/src/main.py index 3e9bf1f72..2896143ce 100644 --- a/examples/simple_module/src/main.py +++ b/examples/simple_module/src/main.py @@ -33,7 +33,7 @@ async def do_command(self, command: Mapping[str, ValueTypes], *, timeout: Option async def main(): - """This function creates and starts a new module, after adding all desired resource model. + """This function creates and starts a new module, after adding all desired resource models. Resource creators must be registered to the resource registry before the module adds the resource model. """ Registry.register_resource_creator(Sensor.SUBTYPE, MySensor.MODEL, ResourceCreatorRegistration(MySensor.new)) From 23cdb4945f335c56dadedb202f6e8aa649ce0392 Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Mon, 24 Jul 2023 17:22:19 -0400 Subject: [PATCH 08/16] change name --- docs/examples/example.ipynb | 6 +++--- examples/complex_module/run.sh | 6 +++--- examples/simple_module/run.sh | 6 +++--- 3 files changed, 9 insertions(+), 9 deletions(-) diff --git a/docs/examples/example.ipynb b/docs/examples/example.ipynb index 8bdb0733a..0a2b05c9c 100644 --- a/docs/examples/example.ipynb +++ b/docs/examples/example.ipynb @@ -395,10 +395,10 @@ "cd `dirname $0`\n", "\n", "# Create a virtual environment to run our code\n", - "VENV=\"venv\"\n", - "PYTHON=\"$VENV/bin/python\"\n", + "VENV_NAME=\"venv\"\n", + "PYTHON=\"$VENV_NAME/bin/python\"\n", "\n", - "python3 -m venv $VENV\n", + "python3 -m venv $VENV_NAME\n", "$PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible\n", "\n", "\n", diff --git a/examples/complex_module/run.sh b/examples/complex_module/run.sh index 5788d422a..dd70be07e 100755 --- a/examples/complex_module/run.sh +++ b/examples/complex_module/run.sh @@ -2,10 +2,10 @@ cd `dirname $0` # Create a virtual environment to run our code -VENV="venv" -PYTHON="$VENV/bin/python" +VENV_NAME="venv" +PYTHON="$VENV_NAME/bin/python" -python3 -m venv $VENV +python3 -m venv $VENV_NAME $PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible # Be sure to use `exec` so that termination signals reach the python process, diff --git a/examples/simple_module/run.sh b/examples/simple_module/run.sh index 6651644c4..a3f12d977 100755 --- a/examples/simple_module/run.sh +++ b/examples/simple_module/run.sh @@ -2,10 +2,10 @@ cd `dirname $0` # Create a virtual environment to run our code -VENV="venv" -PYTHON="$VENV/bin/python" +VENV_NAME="venv" +PYTHON="$VENV_NAME/bin/python" -python3 -m venv $VENV +python3 -m venv $VENV_NAME $PYTHON -m pip install -r requirements.txt -U # remove -U if viam-sdk should not be upgraded whenever possible # Be sure to use `exec` so that termination signals reach the python process, From 26ffe3638f6171bf399e91e26ac5f89cc06465ae Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:29:40 -0400 Subject: [PATCH 09/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index 741312f8b..b9b7e2bfe 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -4,7 +4,7 @@ This example goes through how to create custom modular resources using Viam's py This is a limited document. For a more in-depth understanding of modules, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). ## Purpose -Modular resources allows you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. +Modular resources allow you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). For a more complex example, take a look at the [complex module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module), which only contains multiple new APIs and custom resource models. From 77efe966b55aa604713062491c288da21e894704 Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:29:54 -0400 Subject: [PATCH 10/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index b9b7e2bfe..ed383d619 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -6,7 +6,7 @@ This is a limited document. For a more in-depth understanding of modules, see th ## Purpose Modular resources allow you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. -For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). For a more complex example, take a look at the [complex module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module), which only contains multiple new APIs and custom resource models. +For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). For a more complex example, take a look at the [complex module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/complex_module), which contains multiple new APIs and custom resource models. ## Project structure The definition of the new resources are in the `main` file of the `src` directory. From a8269281494d1a8643757a30278d434df66aa98e Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:30:13 -0400 Subject: [PATCH 11/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index ed383d619..5b86eea9b 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -11,7 +11,7 @@ For more information, see the [documentation](https://docs.viam.com/program/exte ## Project structure The definition of the new resources are in the `main` file of the `src` directory. -The `main.py` file contains the definition of a new sensor model and then registers it. It then creates and starts a module. This file is called by the `run.sh` script, which is the entrypoint for this module. Read further to learn how to connect this module to your robot. +The `run.sh` script is the entrypoint for a module and calls the `main.py` file. The `main.py` file contains the definition of a new sensor model and code to register it. When called, the program creates and starts the module. Read further to learn how to connect this module to your robot. Outside the `src` directory, there is the `client.py` file. This can be used to test the module once it's connected to the robot. You will have to update the credentials and robot address in that file. From c3ba6c5b029bd8544afcb11af97a7a60fc31c657 Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:33:07 -0400 Subject: [PATCH 12/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index 5b86eea9b..3885d3eb0 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -13,7 +13,7 @@ The definition of the new resources are in the `main` file of the `src` director The `run.sh` script is the entrypoint for a module and calls the `main.py` file. The `main.py` file contains the definition of a new sensor model and code to register it. When called, the program creates and starts the module. Read further to learn how to connect this module to your robot. -Outside the `src` directory, there is the `client.py` file. This can be used to test the module once it's connected to the robot. You will have to update the credentials and robot address in that file. +Outside the `src` directory, there is a `client.py` file. You can use this file to test the module once you have connected to your robot and configured the module. You will have to update the credentials and robot address in that file. ## How to use These steps assume that you have a robot available at [app.viam.com](app.viam.com). From 8671b0cb0ada0a7c95af1224414e74229037cb00 Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:33:24 -0400 Subject: [PATCH 13/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index 3885d3eb0..48cbc016c 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -15,7 +15,7 @@ The `run.sh` script is the entrypoint for a module and calls the `main.py` file. Outside the `src` directory, there is a `client.py` file. You can use this file to test the module once you have connected to your robot and configured the module. You will have to update the credentials and robot address in that file. -## How to use +## Configuring and using the module These steps assume that you have a robot available at [app.viam.com](app.viam.com). The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, this could be `/home/viam-python-sdk/examples/simple_module/run.sh`. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. From 69e768dd083bd72da614e1a7517c6d34ab439f0a Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:34:49 -0400 Subject: [PATCH 14/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index 48cbc016c..f4b85a94b 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -18,7 +18,7 @@ Outside the `src` directory, there is a `client.py` file. You can use this file ## Configuring and using the module These steps assume that you have a robot available at [app.viam.com](app.viam.com). -The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, this could be `/home/viam-python-sdk/examples/simple_module/run.sh`. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. +The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, your file may be at `/home/viam-python-sdk/examples/simple_module/run.sh` and you must add this file path to your configuration. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. Once the module has been added to your robot, you can then add a component that uses the `MySensor` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. From 1d665f2a01ff8ac75b005d08e142cadbf45afa7c Mon Sep 17 00:00:00 2001 From: Cheuk <90270663+cheukt@users.noreply.github.com> Date: Wed, 26 Jul 2023 12:35:54 -0400 Subject: [PATCH 15/16] Update examples/simple_module/README.md Co-authored-by: Naomi Pentrel <5212232+npentrel@users.noreply.github.com> --- examples/simple_module/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index f4b85a94b..61bc0b747 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -20,7 +20,7 @@ These steps assume that you have a robot available at [app.viam.com](app.viam.co The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, your file may be at `/home/viam-python-sdk/examples/simple_module/run.sh` and you must add this file path to your configuration. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. -Once the module has been added to your robot, you can then add a component that uses the `MySensor` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. +Once the module has been added to your robot, add a new component that uses the `MySensor` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. An example configuration for a Sensor component could look like this: ```json From 2ce1d3c2c9d0928a3359ee3bebd209a40a5efcbd Mon Sep 17 00:00:00 2001 From: Cheuk Tse Date: Wed, 26 Jul 2023 12:39:26 -0400 Subject: [PATCH 16/16] final changes --- examples/complex_module/README.md | 10 +++++----- examples/simple_module/README.md | 2 +- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/examples/complex_module/README.md b/examples/complex_module/README.md index bba0ab9a5..61bf4a87f 100644 --- a/examples/complex_module/README.md +++ b/examples/complex_module/README.md @@ -4,7 +4,7 @@ This example goes through how to create custom modular resources using Viam's py This is a limited document. For a more in-depth understanding of modules, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). ## Purpose -Modular resources allows you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. +Modular resources allow you to define custom components and services, and add them to your robot. Viam ships with many component types, but you're not limited to only using those types -- you can create your own using modules. For more information, see the [documentation](https://docs.viam.com/program/extend/modular-resources/). For a simpler example, take a look at the [simple module example](https://github.com/viamrobotics/viam-python-sdk/tree/main/examples/simple_module), which only contains one custom resource model in one file. @@ -21,14 +21,14 @@ The `arm` directory contains all the necessary definitions for creating a custom There is also a `main.py` file, which creates a module, adds the desired resources, and starts the module. This file is called by the `run.sh` script, which is the entrypoint for this module. Read further to learn how to connect this module to your robot. -Outside the `src` directory, there is the `client.py` file. This can be used to test the module once it's connected to the robot. You will have to update the credentials and robot address in that file. +Outside the `src` directory, there is a `client.py` file. You can use this file to test the module once you have connected to your robot and configured the module. You will have to update the credentials and robot address in that file. -## How to use +## Configuring and using the module These steps assume that you have a robot available at [app.viam.com](app.viam.com). -The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, this could be `/home/viam-python-sdk/examples/complex_module/run.sh`. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. +The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, the entrypoint file may be at `/home/viam-python-sdk/examples/complex_module/run.sh` and you must add this file path to your configuration. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. -Once the module has been added to your robot, you can then add a component that uses the `MyGizmo` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. You can add a service that uses the `MySum` model in a similar manner. +Once the module has been added to your robot, add a `Gizmo` component that uses the `MyGizmo` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details. You can also add an `Arm` component that uses the `MyArm` model and a `Summation` service that uses the `MySum` model in a similar manner. An example configuration for an Arm component, a Gizmo component, and a Summation service could look like this: ```json diff --git a/examples/simple_module/README.md b/examples/simple_module/README.md index 61bc0b747..a830aba7e 100644 --- a/examples/simple_module/README.md +++ b/examples/simple_module/README.md @@ -18,7 +18,7 @@ Outside the `src` directory, there is a `client.py` file. You can use this file ## Configuring and using the module These steps assume that you have a robot available at [app.viam.com](app.viam.com). -The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, your file may be at `/home/viam-python-sdk/examples/simple_module/run.sh` and you must add this file path to your configuration. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. +The `run.sh` script is the entrypoint for this module. To connect this module with your robot, you must add this module's entrypoint to the robot's config. For example, the entrypoint file may be at `/home/viam-python-sdk/examples/simple_module/run.sh` and you must add this file path to your configuration. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#use-a-modular-resource-with-your-robot) for more details. Once the module has been added to your robot, add a new component that uses the `MySensor` model. See the [documentation](https://docs.viam.com/program/extend/modular-resources/#configure-a-component-instance-for-a-modular-resource) for more details.