Helper

1. Function

Boltic Workflow supports the execution of custom JavaScript/Python code using the Function activity. This allows you to write complex logic and manipulate data within your workflows.

JavaScript

JavaScript is the main tool for data manipulation and transformation in Boltic Workflow. Use the Function activity to write custom JavaScript code that can transform data and execute complex logic. Additionally, you can integrate popular JavaScript libraries to further enhance the capabilities of your workflows.

Write and Execute JavaScript Code

You can create complex logic or manipulate data using JavaScript methods like map(). For example, you can use map() to transform an array of customer records:

const customers = API_1.result.customers;

return customers.map((customer) => ({
    fullName: customer.name,
    emailAddress: customer.email,
}));

Built-in libraries

The following built-in libraries are available for use in your JavaScript code:

Library	Description
axios	A promise-based HTTP client for making requests to APIs and handling responses.
Buffer	A global object in Node.js used for handling binary data.
crypto	A module for implementing cryptographic functionality like hashing and encryption.
FormData	A class to construct form-data streams for HTTP requests, supporting file uploads.
lodash	A utility library providing modular functions for manipulating arrays, objects, and strings.
papaparse	A powerful and fast CSV (Comma-Separated Values) parser for JavaScript, also supports streaming and web workers.
pdfParse	A simple and efficient Node.js library to extract text and metadata from PDF files.
querystring	A module for parsing and formatting URL query strings.
url	A module for parsing, constructing, and resolving URLs.
xlsx	A library for parsing and writing spreadsheet files (Excel), supporting formats like .xlsx.

Examples

1. axios

const req = {
    url: "<your_url>",
    data: {
        a: 1,
    },
    headers: {
        "x-data": 1,
    },
};
const res = await axios.post(req.url, req.data, { headers: req.headers });

return res.data;

2. lodash

return _.defaults({ a: 1 }, { a: 3, b: 2 });

3. crypto

const hash = crypto.createHash("sha256").update("example").digest("hex");

return hash;

4. Buffer

const buffer = Buffer.from("Hello World", "utf-8");

return buffer.toString("base64");

5. querystring

const parsed = querystring.parse("name=boltic&status=active");

return parsed.name; // Output: "boltic"

6. url

const parsedUrl = url.parse("https://example.com/path?name=boltic");

return parsedUrl.query; // Output: "name=boltic"

7. FormData

const form = new FormData();
form.append("key", "value");

return form.getBuffer();

8. xlsx

const url = "<your_url>"
const response = await axios.get(url, {
    responseType: 'arraybuffer',
});

const workbook = xlsx.read(response.data, { type: 'buffer' });

// Get the first sheet
const sheetName = workbook.SheetNames[0];
const worksheet = workbook.Sheets[sheetName];

// Convert the sheet to JSON
const data = xlsx.utils.sheet_to_json(worksheet);
return data;

9. papaparse

const readCSV = async (url) => {
    try {
        // Download entire file into memory
        const response = await axios.get(url, { responseType: 'text' });

        // Parse CSV from plain text
        const parsed = papaparse.parse(response.data, {
            header: true, // Treat first row as headers
            skipEmptyLines: true,
        });

        console.log('Parsed CSV:', parsed.data);
        return parsed.data;
    } catch (error) {
        console.error('Failed to fetch or parse CSV:', error);
        throw error;
    }
};

const csvUrl = '<your_url>';
const v = await readCSV(csvUrl);
return v;

10. PDF Parser

async function convertPdfUrlToMarkdown(pdfUrl) {
  try {
    const response = await axios.get(pdfUrl, { responseType: 'arraybuffer' });

    const data = await pdfParse(response.data);

    // Clean and format text for markdown
    const markdown = data.text
      .split('\n')
      .map(line => line.trim())
      .filter(line => line.length > 0)
      .map(line => `- ${line}`)  // simple bullet formatting
      .join('\n\n');

    return markdown
  } catch (error) {
    console.error('❌ Error processing PDF:', error.message);
    return error
  }
}

const pdfUrl = '<your_pdf_url>'
return convertPdfUrlToMarkdown(pdfUrl, 'output.md');

Accessing Data from Previous Integrations

Data from previous integrations can be accessed directly using the integration's name as a reference. This simplifies data retrieval by eliminating the need to access data using {{}} syntax.

Example:

const customerData = API_1.result.customers;
// Here API_1 is the name of any of the previous activity

return customerData.payload.map((customer) => customer.email);

Python

Python is a versatile and widely used programming language known for its simplicity and readability. Use the Function activity to write custom Python code that can transform data and execute complex logic. Additionally, you can integrate popular Python libraries to further enhance the capabilities of your workflows.

Write and Execute Python Code

You can create complex logic or manipulate data using Python methods, such as map(). For example, you can use map() to transform an array of customer records:

customers = API_1.result.customers
return [{'fullName': customer.name, 'emailAddress': customer.email} for customer in customers]

Built-in Libraries

The following built-in libraries are available for use in your Python code:

Library	Description
base64	A module for encoding and decoding data using base64 encoding.
bcrypt	A library for secure password hashing and verification.
Jinja2	A library for templating, allowing you to generate dynamic content using placeholders.
json	A built-in library for working with JSON data.
numpy	A library for numerical computing, providing support for large, multi-dimensional arrays.
pandas	A powerful library for data manipulation and analysis, offering data structures and tools.
regex	A library for regular expression matching and manipulation.
requests	A popular library for making HTTP requests to APIs and handling responses.
ruamel.yaml	A library for working with YAML files, providing a flexible and extensible format.

Example

1. Requests

import requests
url = "<your_url>"
data = {
    "a": 1
}
headers = {
    "x-data": 1
}
response = requests.post(url, json=data, headers=headers)
return response.json()

2. JSON

import json
data = {
    "a": 1
}
return json.dumps(data)

3. base64

import base64
data = b"Hello World"
return base64.b64encode(data).decode('utf-8')

4. numpy

import numpy as np
data = np.array([1, 2, 3, 4, 5])
return data.tolist()

5. pandas

import pandas as pd
data = {
    "a": [1, 2, 3],
    "b": [4, 5, 6]
}
df = pd.DataFrame(data)
return df.to_dict(orient='records')

6. ruamel.yaml

import ruamel.yaml
data = {
    "a": 1,
    "b": 2
}
yaml = ruamel.yaml.YAML()
return yaml.dump(data)

7. jinja2

from jinja2 import Template
template = Template("Hello, {{ name }}!")
return template.render(name="John")

8. bcrypt

import bcrypt
password = "my_password"
hashed_password = bcrypt.hashpw(password.encode('utf-8'), bcrypt.gensalt())
return hashed_password.decode('utf-8')

9. regex

import regex
text = "Hello, World!"
pattern = r"Hello"
match = regex.search(pattern, text)
return match.group()

Accessing Data from Previous Integrations

Data from previous integrations can be accessed directly using the integration's name as a reference. This simplifies data retrieval by eliminating the need to access data using {{}} syntax.

Example:

customer_data = API_1.result.customers
# Here API_1 is the name of any of the previous activity
return [customer.email for customer in customer_data]

Reserved System Keys

Certain keys are reserved by the system and cannot be used as variable names within your JavaScript code. Avoid using the following keys as variables:

Key	Description
activity	Reserved for referencing activity-related metadata.
chunk	Represents data chunking during execution.
entity_id	Identifies the entity ID relevant to the current operation.
execute_meta	Contains metadata about the execution context.
execution_id	Identifies the unique ID for the current workflow execution.
global_variables	Stores global variables accessible across all activities.
is_single_execution	Indicates whether the execution is a single instance.
maximum_activity_completion_timeout	Defines the maximum time allowed for activity completion.
operator	Represents the current operator executing the function.
payload	Represents the input data provided to the function.
resource	Reserved for resource-specific data.
result	Previously used for accessing the result of an activity; direct activity name references are now recommended.
secret	Reserved for handling sensitive credential data.
taskQueue	Refers to the task queue being used.
version	Represents the version of the workflow or activity.
workflow	Reserved for referencing the current workflow.
workflow_id	Stores the unique ID of the workflow.
workflow_meta	Stores metadata about the workflow.

Using these names will cause conflicts and may result in errors or unexpected behavior.

1. Function​

JavaScript​

Write and Execute JavaScript Code​

Built-in libraries​

Examples​

1. axios​

2. lodash​

3. crypto​

4. Buffer​

5. querystring​

6. url​

7. FormData​

8. xlsx​

9. papaparse​

10. PDF Parser​

Accessing Data from Previous Integrations​

Python​

Write and Execute Python Code​

Built-in Libraries​

Example​

1. Requests​

2. JSON​

3. base64​

4. numpy​

5. pandas​

6. ruamel.yaml​

7. jinja2​

8. bcrypt​

9. regex​

Accessing Data from Previous Integrations​

Reserved System Keys​

1. Function

JavaScript

Write and Execute JavaScript Code

Built-in libraries

Examples

1. axios

2. lodash

3. crypto

4. Buffer

5. querystring

6. url

7. FormData

8. xlsx

9. papaparse

10. PDF Parser

Accessing Data from Previous Integrations

Python

Write and Execute Python Code

Built-in Libraries

Example

1. Requests

2. JSON

3. base64

4. numpy

5. pandas

6. ruamel.yaml

7. jinja2

8. bcrypt

9. regex

Accessing Data from Previous Integrations

Reserved System Keys