Update Row with PostgreSQL API on New Article Published from New York Times API

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New Article Published from the New York Times API

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Update Row with the PostgreSQL API

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Getting Started#

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

Select this integration
Configure the New Article Published trigger
1. Connect your New York Times account
2. Configure timer
3. Optional- Configure Facet
4. Optional- Select one or more Facet Fields
5. Optional- Configure Facet Filter
6. Optional- Configure Field List
7. Optional- Configure Filtered Query
8. Optional- Configure Query
9. Configure alert
Configure the Update Row action
1. Connect your PostgreSQL account
2. Select a Schema
3. Select a Table
4. Select a Lookup Column
5. Select a Lookup Value
6. Configure Row Values
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 Article Published on New York Times

Description:Emit new event when an article is published.

Version:0.0.1

Key:new_york_times-new-article

View on GitHub

New York Times Overview#

The New York Times API offers a variety of endpoints to access different types of news and information. With Pipedream, you can tap into this wealth of data to automate tasks, enrich applications with the latest news, or even analyze trends. Workflows on Pipedream triggered by NYT's API can range from sending daily news briefings to your communication platform, to analyzing article metadata for SEO research, or even keeping track of the most popular stories for content curation.

Trigger Code#

import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";
import moment from "moment";
import app from "../../new_york_times.app.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  key: "new_york_times-new-article",
  name: "New Article Published",
  description: "Emit new event when an article is published.",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  props: {
    app,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    facet: {
      type: "boolean",
      label: "Facet",
      description: "Whether to show facet counts.",
      optional: true,
    },
    facetFields: {
      type: "string[]",
      label: "Facet Fields",
      description: "Use facets to view the relative importance of certain fields to a search term, and gain insight about how to best refine your queries and filter your search results.",
      options: [
        "day_of_week",
        "document_type",
        "ingredients",
        "news_desk",
        "pub_month",
        "pub_year",
        "section_name",
        "source",
        "subsection_name",
        "type_of_material",
      ],
      optional: true,
    },
    facetFilter: {
      type: "boolean",
      label: "Facet Filter",
      description: "Have facet counts use filters.",
      optional: true,
    },
    fl: {
      type: "string[]",
      label: "Field List",
      description: "The list of fields to return in the result set.",
      optional: true,
    },
    fq: {
      type: "string",
      label: "Filtered Query",
      description: "A query to filter the search results.",
      optional: true,
    },
    q: {
      type: "string",
      label: "Query",
      description: "Search query term. Search is performed on the article body, headline, and byline.",
      optional: true,
    },
    alert: {
      type: "alert",
      alertType: "info",
      content: "To learn more about filters you can download the [New York Times specification here](https://developer.nytimes.com/portals/api/sites/nyt-devportal/liveportal/apis/articlesearch-product/download_spec).",
    },
  },
  methods: {
    _getLastDate() {
      return this.db.get("lastDate") || moment().subtract(1, "day");
    },
    _setLastDate(created) {
      this.db.set("lastDate", created);
    },
    generateMeta(item) {
      return {
        id: item._id,
        summary: `A new article was just published with Id: ${item._id}.`,
        ts: item.pub_date,
      };
    },
    async startEvent(maxResults = 0) {
      const lastDate = this._getLastDate();

      const data = this.app.paginate({
        fn: this.app.searchArticles,
        maxResults,
        params: {
          begin_date: moment(lastDate).format("YYYYMMDD"),
          facet: this.facet,
          facet_fields: this.facetFields && this.facetFields.join(),
          facet_filter: this.facetFilter,
          fl: this.fl && this.fl.join(),
          fq: this.fq,
          q: this.q,
          sort: "newest",
        },
      });

      const responseArray = [];
      for await (const item of data) {
        if (Date.parse(item.pub_date) <= Date.parse(lastDate)) break;
        responseArray.push(item);
      }

      if (responseArray.length) this._setLastDate(responseArray[0].pub_date);

      for (const item of responseArray.reverse()) {
        this.$emit(item, this.generateMeta(item));
      }
    },
  },
  hooks: {
    async deploy() {
      await this.startEvent(25);
    },
  },
  async run() {
    await this.startEvent();
  },
  sampleEmit,
};

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
New York Times	`app`	`app`	This component uses the New York Times app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Facet	`facet`	`boolean`	Whether to show facet counts.
Facet Fields	`facetFields`	`string[]`	Select a value from the drop down menu:`day_of_weekdocument_typeingredientsnews_deskpub_monthpub_yearsection_namesourcesubsection_nametype_of_material`
Facet Filter	`facetFilter`	`boolean`	Have facet counts use filters.
Field List	`fl`	`string[]`	The list of fields to return in the result set.
Filtered Query	`fq`	`string`	A query to filter the search results.
Query	`q`	`string`	Search query term. Search is performed on the article body, headline, and byline.

Trigger Authentication#

New York Times uses API keys for authentication. When you connect your New York Times account, Pipedream securely stores the keys so you can easily authenticate to New York Times APIs in both code and no-code steps.

About New York Times#

The New York Times is an American daily newspaper which features top articles across many sections, including politics, technology, and opinion.

Action#

Update Row on PostgreSQL

Description:Updates an existing row. [See the documentation](https://node-postgres.com/features/queries)

Version:2.0.6

Key:postgresql-update-row

View on GitHub

PostgreSQL Overview#

On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.

Action Code#

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

export default {
  name: "Update Row",
  key: "postgresql-update-row",
  description: "Updates an existing row. [See the documentation](https://node-postgres.com/features/queries)",
  version: "2.0.6",
  type: "action",
  props: {
    postgresql,
    schema: {
      propDefinition: [
        postgresql,
        "schema",
      ],
    },
    table: {
      propDefinition: [
        postgresql,
        "table",
        (c) => ({
          schema: c.schema,
        }),
      ],
    },
    column: {
      propDefinition: [
        postgresql,
        "column",
        (c) => ({
          table: c.table,
          schema: c.schema,
        }),
      ],
      label: "Lookup Column",
      description: "Find row to update by searching for a value in this column. Returns first row found",
    },
    value: {
      propDefinition: [
        postgresql,
        "value",
        (c) => ({
          table: c.table,
          column: c.column,
          schema: c.schema,
        }),
      ],
    },
    rowValues: {
      propDefinition: [
        postgresql,
        "rowValues",
      ],
    },
  },
  async run({ $ }) {
    const {
      schema,
      table,
      column,
      value,
      rowValues,
    } = this;
    try {
      const res = await this.postgresql.updateRow(
        schema,
        table,
        column,
        value,
        rowValues,
      );
      const summary = res
        ? "Row updated"
        : "Row not found";
      $.export("$summary", summary);
      return res;
    } catch (error) {
      let errorMsg = "Row not updated due to an error. ";
      errorMsg += `${error}`.includes("SSL verification failed")
        ? "This could be because SSL verification failed. To resolve this, reconnect your account and set SSL Verification Mode: Skip Verification, and try again."
        : `${error}`;
      throw new Error(errorMsg);
    }
  },
};

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
PostgreSQL	`postgresql`	`app`	This component uses the PostgreSQL app.
Schema	`schema`	`string`	Select a value from the drop down menu.
Table	`table`	`string`	Select a value from the drop down menu.
Lookup Column	`column`	`string`	Select a value from the drop down menu.
Lookup Value	`value`	`string`	Select a value from the drop down menu.
Row Values	`rowValues`	`object`	Enter the column names and respective values as key/value pairs, or with structured mode off as `{{{columnName:"columnValue"}}}`

Action Authentication#

PostgreSQL uses API keys for authentication. When you connect your PostgreSQL account, Pipedream securely stores the keys so you can easily authenticate to PostgreSQL APIs in both code and no-code steps.

Connecting to Restricted Databases

Either enable the shared static IP for this account below, or configure a VPC to deploy any workflow in your workspace to a private network with a dedicated static IP. Learn more in our docs.

SSL Setup

Configure SSL on your PostgreSQL database by providing the CA (Certificate Authority), and choosing between Full Verification, Verify Certificate Authority (CA), or Skip Verification. Skipping verification is not recommended as this has serious security implications.