Execute SQL Query with Snowflake API on New Job Opening Added from PredictLeads API

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Trigger workflow on

New Job Opening Added from the PredictLeads API

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Execute SQL Query with the Snowflake API

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Getting Started#

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

Select this integration
Configure the New Job Opening Added trigger
1. Connect your PredictLeads account
2. Configure timer
3. Configure Domain
4. Optional- Configure Active Only
5. Optional- Configure With Description Only
6. Optional- Configure With Location Only
7. Optional- Select one or more Categories
Configure the Execute SQL Query action
1. Connect your Snowflake account
2. Configure SQL Query
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 Job Opening Added on PredictLeads

Description:Emit new event for each new job opening for a specific company. [See the documentation](https://docs.predictleads.com/v3/api_endpoints/job_openings_dataset/retrieve_job_openings_from_specific_company)

Version:0.0.1

Key:predictleads-new-job-opening

View on GitHub

Trigger Code#

import common from "../common/polling.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  ...common,
  key: "predictleads-new-job-opening",
  name: "New Job Opening Added",
  description: "Emit new event for each new job opening for a specific company. [See the documentation](https://docs.predictleads.com/v3/api_endpoints/job_openings_dataset/retrieve_job_openings_from_specific_company)",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    domain: {
      description: "The domain of the company to retrieve job openings for (e.g., `google.com`).",
      propDefinition: [
        common.props.app,
        "domain",
      ],
    },
    activeOnly: {
      type: "boolean",
      label: "Active Only",
      description: "Set to `true` to receive Job Openings that are not closed",
      optional: true,
    },
    withDescriptionOnly: {
      type: "boolean",
      label: "With Description Only",
      description: "Set to `true` to only return Job Openings that have a description.",
      optional: true,
    },
    withLocationOnly: {
      type: "boolean",
      label: "With Location Only",
      description: "Set to `true` to only return Job Openings that have a location.",
      optional: true,
    },
    categories: {
      type: "string[]",
      label: "Categories",
      description: "Filter job openings by specific categories.",
      optional: true,
      options: [
        "administration",
        "consulting",
        "data_analysis",
        "design",
        "directors",
        "education",
        "engineering",
        "finance",
        "healthcare_services",
        "human_resources",
        "information_technology",
        "internship",
        "legal",
        "management",
        "marketing",
        "military_and_protective_services",
        "operations",
        "purchasing",
        "product_management",
        "quality_assurance",
        "real_estate",
        "research",
        "sales",
        "software_development",
        "support",
        "manual_work",
        "food",
      ],
    },
  },
  methods: {
    ...common.methods,
    getDateField() {
      return "last_seen_at";
    },
    getResourcesFn() {
      return this.app.retrieveJobOpenings;
    },
    getResourcesFnArgs() {
      const {
        domain,
        activeOnly,
        withDescriptionOnly,
        withLocationOnly,
        categories,
      } = this;
      return {
        domain,
        params: {
          active_only: activeOnly,
          with_description_only: withDescriptionOnly,
          with_location_only: withLocationOnly,
          categories: categories?.join(","),
        },
      };
    },
    generateMeta(resource) {
      return {
        id: resource.id,
        summary: `New Job Opening: ${resource.attributes.title}`,
        ts: Date.parse(resource.attributes.first_seen_at),
      };
    },
  },
  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
PredictLeads	`app`	`app`	This component uses the PredictLeads app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Domain	`domain`	`string`	The domain of the company to retrieve job openings for (e.g., `google.com`).
Active Only	`activeOnly`	`boolean`	Set to `true` to receive Job Openings that are not closed
With Description Only	`withDescriptionOnly`	`boolean`	Set to `true` to only return Job Openings that have a description.
With Location Only	`withLocationOnly`	`boolean`	Set to `true` to only return Job Openings that have a location.
Categories	`categories`	`string[]`	Select a value from the drop down menu:`administrationconsultingdata_analysisdesigndirectorseducationengineeringfinancehealthcare_serviceshuman_resourcesinformation_technologyinternshiplegalmanagementmarketingmilitary_and_protective_servicesoperationspurchasingproduct_managementquality_assurancereal_estateresearchsalessoftware_developmentsupportmanual_workfood`

Trigger Authentication#

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

About PredictLeads#

Company Intelligence Data

Action#

Execute SQL Query on Snowflake

Description:Execute a custom Snowflake query. See [our docs](https://pipedream.com/docs/databases/working-with-sql) to learn more about working with SQL in Pipedream.

Version:0.2.0

Key:snowflake-execute-sql-query

View on GitHub

Snowflake Overview#

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University

Action Code#

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

export default {
  name: "Execute SQL Query",
  version: "0.2.0",
  key: "snowflake-execute-sql-query",
  description: "Execute a custom Snowflake query. See [our docs](https://pipedream.com/docs/databases/working-with-sql) to learn more about working with SQL in Pipedream.",
  type: "action",
  props: {
    snowflake,
    // eslint-disable-next-line pipedream/props-description
    sql: {
      type: "sql",
      auth: {
        app: "snowflake",
      },
      label: "SQL Query",
    },
  },
  async run({ $ }) {
    const args = this.snowflake.executeQueryAdapter(this.sql);

    const data = await this.snowflake.executeQuery(args);

    $.export("$summary", `Returned ${data.length} ${data.length === 1
      ? "row"
      : "rows"}`);

    return data;
  },
};

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
Snowflake	`snowflake`	`app`	This component uses the Snowflake app.
SQL Query	`sql`	`sql`