Extract Data with AI Textraction API on New Download Counts from npm API

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New Download Counts from the npm API

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Extract Data with the AI Textraction API

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Getting Started#

This integration creates a workflow with a npm trigger and AI Textraction action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Download Counts trigger
1. Connect your npm account
2. Configure timer
3. Select a Period
4. Optional- Configure Package
Configure the Extract Data action
1. Connect your AI Textraction account
2. Configure Text
3. Configure Entities
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

New Download Counts on npm

Description:Emit new event with the latest count of downloads for an npm package. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md).

Version:0.1.0

Key:npm-download-counts

View on GitHub

Trigger Code#

import app from "../../npm.app.mjs";

export default {
  key: "npm-download-counts",
  name: "New Download Counts",
  description: "Emit new event with the latest count of downloads for an npm package. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md).",
  version: "0.1.0",
  type: "source",
  props: {
    app,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      description: "One day interval time is recommended because NPM only update metrics once a day. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md#data-source).",
      default: {
        intervalSeconds: 60 * 60 * 24,
      },
    },
    period: {
      type: "string",
      label: "Period",
      description: "Select last-day, last-week or last-month.",
      optional: false,
      default: "last-day",
      options: [
        "last-day",
        "last-week",
        "last-month",
      ],
    },
    packageName: {
      type: "string",
      label: "Package",
      description: "Enter an npm package name. Leave blank for all",
      optional: true,
    },
  },
  methods: {
    getDownloadCounts({
      period, packageName, ...args
    } = {}) {
      const basePath = `/downloads/point/${encodeURIComponent(period)}`;
      return this.app.makeRequest({
        path: packageName
          ? `${basePath}/${encodeURIComponent(packageName)}`
          : basePath,
        ...args,
      });
    },
  },
  async run({ timestamp: ts }) {
    const {
      getDownloadCounts,
      period,
      packageName,
    } = this;

    const response = await getDownloadCounts({
      period,
      packageName,
    });

    this.$emit(response, {
      id: ts,
      summary: `New Download Count ${response.downloads}`,
      ts,
    });
  },
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
npm	`app`	`app`	This component uses the npm app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`	One day interval time is recommended because NPM only update metrics once a day. See the documentation.
Period	`period`	`string`	Select a value from the drop down menu:`last-daylast-weeklast-month`
Package	`packageName`	`string`	Enter an npm package name. Leave blank for all

Trigger Authentication#

The npm API does not require authentication.

About npm#

Node package manager

Action#

Extract Data on AI Textraction

Description:Extract custom data from text using AI Textraction. [See the documentation](https://rapidapi.com/textractionai/api/ai-textraction)

Version:0.0.1

Key:ai_textraction-extract-data

View on GitHub

Action Code#

import aiTextraction from "../../ai_textraction.app.mjs";

export default {
  key: "ai_textraction-extract-data",
  name: "Extract Data",
  description: "Extract custom data from text using AI Textraction. [See the documentation](https://rapidapi.com/textractionai/api/ai-textraction)",
  version: "0.0.1",
  type: "action",
  props: {
    aiTextraction,
    text: {
      type: "string",
      label: "Text",
      description: "The text to extract entities from",
    },
    entities: {
      type: "string[]",
      label: "Entities",
      description: "An array of entity names to extract from the text. Example: `first_name`",
      reloadProps: true,
    },
  },
  async additionalProps() {
    const props = {};
    if (!this.entities?.length) {
      return props;
    }
    for (const entity of this.entities) {
      props[`${entity}_type`] = {
        type: "string",
        label: `${entity} - Type`,
        description: `The type of results to return for ${entity}`,
        options: [
          "string",
          "integer",
          "array[string]",
          "array[integer]",
        ],
      };
      props[`${entity}_description`] = {
        type: "string",
        label: `${entity} - Description`,
        description: `Description of the entity ${entity}. Example: \`First name of the person\``,
      };
    }
    return props;
  },
  async run({ $ }) {
    const entities = this.entities.map((entity) => ({
      var_name: entity,
      type: this[`${entity}_type`],
      description: this[`${entity}_description`],
    }));

    const response = await this.aiTextraction.extractData({
      $,
      data: {
        text: this.text,
        entities,
      },
    });

    $.export("$summary", "Successfully extracted data from text");
    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
AI Textraction	`aiTextraction`	`app`	This component uses the AI Textraction app.
Text	`text`	`string`	The text to extract entities from
Entities	`entities`	`string[]`	An array of entity names to extract from the text. Example: `first_name`