← Google Cloud + Python integrations

Run Python Code with Python API on BigQuery - New Row from Google Cloud API

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BigQuery - New Row from the Google Cloud API
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Run Python Code with the Python API
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Developers Pipedream

Getting Started

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

  1. Select this integration
  2. Configure the BigQuery - New Row trigger
    1. Connect your Google Cloud account
    2. Configure Polling interval
    3. Configure Event Size
    4. Select a Dataset ID
    5. Select a Table Name
    6. Select a Unique Key
  3. Configure the Run Python Code action
    1. Connect your Python account
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new events when a new row is added to a table
Version:0.1.6
Key:google_cloud-bigquery-new-row

Google Cloud Overview

The Google Cloud API allows developers to access a variety of Google Cloud
services from their own applications. Services that can be accessed include
Google Cloud Storage, Google Cloud Datastore, Google Cloud Functions, and
Google Cloud Pub/Sub. With the Google Cloud API, developers can build a variety
of applications that take advantage of Google Cloud services.

Trigger Code

import crypto from "crypto";
import { isString } from "lodash-es";
import googleCloud from "../../google_cloud.app.mjs";
import common from "../common/bigquery.mjs";

export default {
  ...common,
  key: "google_cloud-bigquery-new-row",
  // eslint-disable-next-line pipedream/source-name
  name: "BigQuery - New Row",
  description: "Emit new events when a new row is added to a table",
  version: "0.1.6",
  dedupe: "unique",
  type: "source",
  props: {
    ...common.props,
    tableId: {
      propDefinition: [
        googleCloud,
        "tableId",
        ({ datasetId }) => ({
          datasetId,
        }),
      ],
    },
    uniqueKey: {
      type: "string",
      label: "Unique Key",
      description: "The name of a column in the table to use for deduplication. See [the docs](https://github.com/PipedreamHQ/pipedream/tree/master/components/google_cloud/sources/bigquery-new-row#technical-details) for more info.",
      async options(context) {
        const { page } = context;
        if (page !== 0) {
          return [];
        }

        const columnNames = await this._getColumnNames();
        return columnNames.sort();
      },
    },
  },
  hooks: {
    ...common.hooks,
    async deploy() {
      await this._validateColumn(this.uniqueKey);
      const lastResultId = await this._getIdOfLastRow(this.getInitialEventCount());
      this._setLastResultId(lastResultId);
    },
    async activate() {
      if (this._getLastResultId()) {
        // ID of the last result has already been initialised during deploy(),
        // so we skip the rest of the activation.
        return;
      }

      await this._validateColumn(this.uniqueKey);
      const lastResultId = await this._getIdOfLastRow();
      this._setLastResultId(lastResultId);
    },
    deactivate() {
      this._setLastResultId(null);
    },
  },
  methods: {
    ...common.methods,
    _getLastResultId() {
      return this.db.get("lastResultId");
    },
    _setLastResultId(lastResultId) {
      this.db.set("lastResultId", lastResultId);
      console.log(`
        Next scan of table '${this.tableId}' will start at ${this.uniqueKey}=${lastResultId}
      `);
    },
    /**
     * Utility method to make sure that a certain column exists in the target
     * table. Useful for SQL query sanitizing.
     *
     * @param {string} columnNameToValidate The name of the column to validate
     * for existence
     */
    async _validateColumn(columnNameToValidate) {
      if (!isString(columnNameToValidate)) {
        throw new Error("columnNameToValidate must be a string");
      }

      const columnNames = await this._getColumnNames();
      if (!columnNames.includes(columnNameToValidate)) {
        throw new Error(`Nonexistent column: ${columnNameToValidate}`);
      }
    },
    async _getColumnNames() {
      const table = this.googleCloud
        .getBigQueryClient()
        .dataset(this.datasetId)
        .table(this.tableId);
      const [
        metadata,
      ] = await table.getMetadata();
      const { fields } = metadata.schema;
      return fields.map(({ name }) => name);
    },
    async _getIdOfLastRow(offset = 0) {
      const limit = offset + 1;
      const query = `
        SELECT *
        FROM \`${this.tableId}\`
        ORDER BY \`${this.uniqueKey}\` DESC
        LIMIT @limit
      `;
      const queryOpts = {
        query,
        params: {
          limit,
        },
      };
      const rows = await this.getRowsForQuery(queryOpts, this.datasetId);
      if (rows.length === 0) {
        console.log(`
          No records found in the target table, will start scanning from the beginning
        `);
        return;
      }

      const startingRow = rows.pop();
      return startingRow[this.uniqueKey];
    },
    getQueryOpts() {
      const lastResultId = this._getLastResultId();
      const query = `
        SELECT *
        FROM \`${this.tableId}\`
        WHERE \`${this.uniqueKey}\` >= @lastResultId
        ORDER BY \`${this.uniqueKey}\` ASC
      `;
      const params = {
        lastResultId,
      };
      return {
        query,
        params,
      };
    },
    generateMeta(row, ts) {
      const id = row[this.uniqueKey];
      const summary = `New row: ${id}`;
      return {
        id,
        summary,
        ts,
      };
    },
    generateMetaForCollection(rows, ts) {
      const hash = crypto.createHash("sha1");
      rows
        .map((i) => i[this.uniqueKey])
        .map((i) => i.toString())
        .forEach((i) => hash.update(i));
      const id = hash.digest("base64");

      const rowCount = rows.length;
      const entity = rowCount === 1
        ? "row"
        : "rows";
      const summary = `${rowCount} new ${entity}`;

      return {
        id,
        summary,
        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.
LabelPropTypeDescription
Google CloudgoogleCloudappThis component uses the Google Cloud app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
Polling intervaltimer$.interface.timer

How often to run your query

Event SizeeventSizeinteger

The number of rows to include in a single event (by default, emits 1 event per row)

Dataset IDdatasetIdstringSelect a value from the drop down menu.
Table NametableIdstringSelect a value from the drop down menu.
Unique KeyuniqueKeystringSelect a value from the drop down menu.

Trigger Authentication

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

  1. Create a service account in GCP and set the permissions you need for Pipedream workflows.

  2. Generate a service account key

  3. Download the key details in JSON format

  4. Open the JSON in a text editor, and copy and paste its contents here.

About Google Cloud

The Google Cloud Platform, including BigQuery

Action

Description:Write Python and use any of the 350k+ PyPi packages available. Refer to the [Pipedream Python docs](https://pipedream.com/docs/code/python) to learn more.
Version:0.0.2
Key:python-run-python-code

Python Overview

Python API on Pipedream offers developers to build or automate a variety of
tasks from their web and cloud apps. With the Python API, users are able to
create comprehensive and flexible scripts, compose and manage environment
variables, and configure resources to perform a range of functions.

By using Pipedream, you can easily:

  • Create automated workflows that run on a specific schedule
  • Compose workflows across various apps and services
  • React to events in cloud services or form data
  • Automatically create content and notifications
  • Construct classifications and predictions
  • Analyze and react to sentiment, sentiment analysis and sentiment score
  • Connect backends to the frontend with serverless functions
  • Work with files and databases
  • Perform web requests and fetch data
  • Integrate third-party APIs into your apps
  • Orchestrate data processing tasks and pipelines
  • Create powerful application APIs with authentication and authorization
  • Design CI/CD pipelines and Continuous Delivery services
  • Connect databases like MongoDB and MySQL
  • Monitor connections and events
  • Generate alerts and notifications for corresponding events

Action Code

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

export default {
  name: "Run Python Code",
  version: "0.0.2",
  key: "python-run-python-code",
  description: "Write Python and use any of the 350k+ PyPi packages available. Refer to the [Pipedream Python docs](https://pipedream.com/docs/code/python) to learn more.",
  props: {
    python,
  },
  type: "action",
  methods: {},
  async run({
    steps, $,
  }) {
    // Placeholder action for Python code app
  },
};

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.

LabelPropTypeDescription
PythonpythonappThis component uses the Python app.

Action Authentication

The Python API does not require authentication.

About Python

Anything you can do in Python can be done in a Pipedream Workflow. This includes using any of the 350,000+ PyPi packages available in your Python powered workflows.

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