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databots can extend to provide several utility functions, error handling, and logging.\n\n## installation and usage\n\n```\nnpm i @nqminds/crop-doc-proc-databot\n```\n\nIn the entry point of your databot:\n\n```javascript\nconst input = require(\"@nqminds/nqm-databot-utils\").input;\nconst MyDatabot = require(\"./path/to/databot\");\n\nconst databot = function (input, output, context) {\n  const myDatabotInstance = new MyDatabot(input, output, context);\n  myDatabotInstance.start();\n};\n\ninput.pipe(databot);\n```\n\nIn your databot code:\n\n```javascript\nconst ProcessDatabot = require(\"@nqminds/crop-doc-proc-databot\");\n\nclass MyDatabot extends ProcessDatabot {\n  async main() {\n    // Code of databot\n  }\n}\n```\n\n## Package parameters\n\nDatabots that extend process databot must provide the following data in their packageParams included on context.\n\n```json\n{\n  \"name\": \"string\", // The unique name of this databot definition\n  \"manifest\": [\n    // See manifest below for more details\n    {\n      \"inputName\": \"string\",\n      \"inputType\": \"string\",\n      \"ttl\": \"number\",\n      \"timeKey\": \"string\",\n      \"owner\": \"string\"\n    }\n  ],\n  // python installation options (pick one only)\n  pythonPackages: [\"string\"], // names of python3 packages to install\n  condaEnv: \"string\" // path of a conda environment.yml\n  usePoetry: \"bool\" // install using poetry (pyproject.toml must be defined, poetry.lock optional)\n  javaSubProcess: { // optional\n    port: \"number\", // The port on which to launch the websocket server for communication\n    executablePath: \"string\" // The location of the java executable to run\n  }\n}\n```\n\n## Manifest\n\nThe manifest for a process databot details information on the inputs required for the databot to run. Before a process databot begins it will verify that all of these inputs are available.\n\n```json\n{\n  inputName: \"input1\", // A unique name for this input\n  inputType: \"geotiff\", // The type of input, this will determine how the input is loaded by the databot\n                        // Usually one of \"geotiff\", \"dataset\"\n  ttl: 60, // The maximum age of the most recent input for it to be considered valid in minutes\n  timeKey: \"timestamp\", // If loading a dataset, the field name containing the creation time for the record\n  owner: \"info@nqminds.com\", // Email address of the party responsible for this input\n}\n// Dataset exmaple with time sensitivity\n{inputName: \"dataInputA\", inputType: \"dataset\", ttl: 60, timeKey: \"timestamp\", owner: \"info@nqminds.com\"}\n// Geotiff Example\n{inputName: \"dataInput\", inputType: \"geotiff\", ttl: 60, owner: \"info@nqminds.com\"}\n```\n\nAn input takes the form of a resource on the TDX, inputs should be tagged with both their input name and their input type. Resource creation time will be used for verifying TTL.\n\n### Conda environment\n\nTo specifiy your desired python environment, create an `environment.yml` with your dependencies. Below is what a YAML environment file might look like:\n\n```yaml\nchannels:\n  - conda-forge\n  - defaults\n  - mro\ndependencies:\n  - python=3.7.*\n  - scikit-learn=0.20.*\n  - scipy=1.2.*\n  - matplotlib=3.0.*\n  - pandas=0.24.*\n  - pymongo=3.7.*\n  - pytest=4.4.*\n  - pip=19.0.*\n  - pip:\n      - pytest-mpl==0.10.*\n```\n\n## Communication with Java\n\nIf the javaSubProcess option was set in packageParams then the process databot will instatiate an instance of the java communicator class. This can be used to communicate with a java process (see java stub package for an example of java code). Usage is as follows:\n\n```javascript\nthis.javaCom.on(\"ready\", () => { // The java process is ready to receive inputs\n  this.javaCom.sendData([{inputType: \"file\", path: \"home\"}]); // Send a json array of input values\n});\nthis.javaCom.on(\"data\", (data) => {\n  // Do something with the data received from java\n});\nthis.javaCom.on(\"end\", (code) => {\n  // The java code has disconneted from the web socket\n});\n```\n\n## functionality\n\n# API Reference\n\n<a name=\"module_process-databot\"></a>\n\n## process-databot\n\n- [process-databot](#module_process-databot)\n  - [ProcessDatabot](#exp_module_process-databot--ProcessDatabot) ⏏\n    - [.getDatasetId(dataset)](#module_process-databot--ProcessDatabot+getDatasetId) ⇒ <code>string</code>\n    - [.main()](#module_process-databot--ProcessDatabot+main)\n    - [.start()](#module_process-databot--ProcessDatabot+start)\n    - [.log(message)](#module_process-databot--ProcessDatabot+log)\n    - [.installPythonPackages()](#module_process-databot--ProcessDatabot+installPythonPackages)\n    - [.python(scriptName, ...args)](#module_process-databot--ProcessDatabot+python)\n    - [.finish()](#module_process-databot--ProcessDatabot+finish)\n\n<a name=\"exp_module_process-databot--ProcessDatabot\"></a>\n\n### ProcessDatabot ⏏\n\nProcess databot base class\n\n**Kind**: Exported class  \n<a name=\"module_process-databot--ProcessDatabot+getDatasetId\"></a>\n\n#### processDatabot.getDatasetId(dataset) ⇒ <code>string</code>\n\nReturns the dataset id of a resource created by the app\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n**Returns**: <code>string</code> - datasetId\n\n| Param   | Type                | Description                                          |\n| ------- | ------------------- | ---------------------------------------------------- |\n| dataset | <code>string</code> | Id of the schema for the dataset (e.g. serviceUsers) |\n\n<a name=\"module_process-databot--ProcessDatabot+main\"></a>\n\n#### processDatabot.main()\n\nThe main function of this databot.\nYou must override this function in your own databot class,\nas it will be called by `start()`.\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n<a name=\"module_process-databot--ProcessDatabot+start\"></a>\n\n#### processDatabot.start()\n\nStarts the databot\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n<a name=\"module_process-databot--ProcessDatabot+log\"></a>\n\n#### processDatabot.log(message)\n\nAdds a timestamped message to the process log\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)\n\n| Param   | Type                | Description                 |\n| ------- | ------------------- | --------------------------- |\n| message | <code>string</code> | 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databot class for the crop doc data processing chain","contributors":[{"name":"Ivan Glautier","email":"ivan@nqminds.com"}],"maintainers":[{"email":"ionut@nquiringminds.com","name":"ionut_nqm"},{"email":"npm-bot@nquiringminds.com","name":"nqminds-bot"},{"email":"nqminds@gmail.com","name":"nqminds-org"},{"email":"mereacre@gmail.com","name":"mereacre"},{"email":"antmcc49@gmail.com","name":"antmcc"},{"email":"toby.ealden@gmail.com","name":"toby.ealden"},{"email":"ash@nquiringminds.com","name":"ashleysetter"}],"readme":"# @nqminds/crop-doc-proc-databot\n\nThis package provides a base class that crop doc process databots can extend to provide several utility functions, error handling, and logging.\n\n## installation and usage\n\n```\nnpm i @nqminds/crop-doc-proc-databot\n```\n\nIn the entry point of your databot:\n\n```javascript\nconst input = require(\"@nqminds/nqm-databot-utils\").input;\nconst MyDatabot = require(\"./path/to/databot\");\n\nconst databot = function (input, output, context) {\n  const myDatabotInstance = new MyDatabot(input, output, context);\n  myDatabotInstance.start();\n};\n\ninput.pipe(databot);\n```\n\nIn your databot code:\n\n```javascript\nconst ProcessDatabot = require(\"@nqminds/crop-doc-proc-databot\");\n\nclass MyDatabot extends ProcessDatabot {\n  async main() {\n    // Code of databot\n  }\n}\n```\n\n## Package parameters\n\nDatabots that extend process databot must provide the following data in their packageParams included on context.\n\n```json\n{\n  \"name\": \"string\", // The unique name of this databot definition\n  \"manifest\": [\n    // See manifest below for more details\n    {\n      \"inputName\": \"string\",\n      \"inputType\": \"string\",\n      \"ttl\": \"number\",\n      \"timeKey\": \"string\",\n      \"owner\": \"string\"\n    }\n  ],\n  // python installation options (pick one only)\n  pythonPackages: [\"string\"], // names of python3 packages to install\n  condaEnv: \"string\" // path of a conda environment.yml\n  usePoetry: \"bool\" // install using poetry (pyproject.toml must be defined, poetry.lock optional)\n  javaSubProcess: { // optional\n    port: \"number\", // The port on which to launch the websocket server for communication\n    executablePath: \"string\" // The location of the java executable to run\n  }\n}\n```\n\n## Manifest\n\nThe manifest for a process databot details information on the inputs required for the databot to run. Before a process databot begins it will verify that all of these inputs are available.\n\n```json\n{\n  inputName: \"input1\", // A unique name for this input\n  inputType: \"geotiff\", // The type of input, this will determine how the input is loaded by the databot\n                        // Usually one of \"geotiff\", \"dataset\"\n  ttl: 60, // The maximum age of the most recent input for it to be considered valid in minutes\n  timeKey: \"timestamp\", // If loading a dataset, the field name containing the creation time for the record\n  owner: \"info@nqminds.com\", // Email address of the party responsible for this input\n}\n// Dataset exmaple with time sensitivity\n{inputName: \"dataInputA\", inputType: \"dataset\", ttl: 60, timeKey: \"timestamp\", owner: \"info@nqminds.com\"}\n// Geotiff Example\n{inputName: \"dataInput\", inputType: \"geotiff\", ttl: 60, owner: \"info@nqminds.com\"}\n```\n\nAn input takes the form of a resource on the TDX, inputs should be tagged with both their input name and their input type. Resource creation time will be used for verifying TTL.\n\n### Conda environment\n\nTo specifiy your desired python environment, create an `environment.yml` with your dependencies. Below is what a YAML environment file might look like:\n\n```yaml\nchannels:\n  - conda-forge\n  - defaults\n  - mro\ndependencies:\n  - python=3.7.*\n  - scikit-learn=0.20.*\n  - scipy=1.2.*\n  - matplotlib=3.0.*\n  - pandas=0.24.*\n  - pymongo=3.7.*\n  - pytest=4.4.*\n  - pip=19.0.*\n  - pip:\n      - pytest-mpl==0.10.*\n```\n\n## Communication with Java\n\nIf the javaSubProcess option was set in packageParams then the process databot will instatiate an instance of the java communicator class. This can be used to communicate with a java process (see java stub package for an example of java code). Usage is as follows:\n\n```javascript\nthis.javaCom.on(\"ready\", () => { // The java process is ready to receive inputs\n  this.javaCom.sendData([{inputType: \"file\", path: \"home\"}]); // Send a json array of input values\n});\nthis.javaCom.on(\"data\", (data) => {\n  // Do something with the data received from java\n});\nthis.javaCom.on(\"end\", (code) => {\n  // The java code has disconneted from the web socket\n});\n```\n\n## functionality\n\n# API Reference\n\n<a name=\"module_process-databot\"></a>\n\n## process-databot\n\n- [process-databot](#module_process-databot)\n  - [ProcessDatabot](#exp_module_process-databot--ProcessDatabot) ⏏\n    - [.getDatasetId(dataset)](#module_process-databot--ProcessDatabot+getDatasetId) ⇒ <code>string</code>\n    - [.main()](#module_process-databot--ProcessDatabot+main)\n    - [.start()](#module_process-databot--ProcessDatabot+start)\n    - [.log(message)](#module_process-databot--ProcessDatabot+log)\n    - [.installPythonPackages()](#module_process-databot--ProcessDatabot+installPythonPackages)\n    - [.python(scriptName, ...args)](#module_process-databot--ProcessDatabot+python)\n    - [.finish()](#module_process-databot--ProcessDatabot+finish)\n\n<a name=\"exp_module_process-databot--ProcessDatabot\"></a>\n\n### ProcessDatabot ⏏\n\nProcess databot base class\n\n**Kind**: Exported class  \n<a name=\"module_process-databot--ProcessDatabot+getDatasetId\"></a>\n\n#### processDatabot.getDatasetId(dataset) ⇒ <code>string</code>\n\nReturns the dataset id of a resource created by the app\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n**Returns**: <code>string</code> - datasetId\n\n| Param   | Type                | Description                                          |\n| ------- | ------------------- | ---------------------------------------------------- |\n| dataset | <code>string</code> | Id of the schema for the dataset (e.g. serviceUsers) |\n\n<a name=\"module_process-databot--ProcessDatabot+main\"></a>\n\n#### processDatabot.main()\n\nThe main function of this databot.\nYou must override this function in your own databot class,\nas it will be called by `start()`.\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n<a name=\"module_process-databot--ProcessDatabot+start\"></a>\n\n#### processDatabot.start()\n\nStarts the databot\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n<a name=\"module_process-databot--ProcessDatabot+log\"></a>\n\n#### processDatabot.log(message)\n\nAdds a timestamped message to the process log\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)\n\n| Param   | Type                | Description                 |\n| ------- | ------------------- | --------------------------- |\n| message | <code>string</code> | Text content of the message |\n\n<a name=\"module_process-databot--ProcessDatabot+installPythonPackages\"></a>\n\n#### processDatabot.installPythonPackages()\n\nInstalls required python3 packages\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)  \n<a name=\"module_process-databot--ProcessDatabot+python\"></a>\n\n#### processDatabot.python(scriptName, ...args)\n\nRuns a python script using python3 and given arguments\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)\n\n| Param      | Type                | Description                                                                                      |\n| ---------- | ------------------- | ------------------------------------------------------------------------------------------------ |\n| scriptName | <code>string</code> | The name of the python script, the code will look for this file in the current working directory |\n| ...args    | <code>any</code>    | Arguments to pass to the python script                                                           |\n\n<a name=\"module_process-databot--ProcessDatabot+finish\"></a>\n\n#### processDatabot.finish()\n\nCalled when the databot exits\n\n**Kind**: instance method of [<code>ProcessDatabot</code>](#exp_module_process-databot--ProcessDatabot)\n","readmeFilename":"README.md"}