How to Save the downloaded file to local system in load runner

In certain scenarios, downloading files becomes a requirement. Instead of needing to store the files on your local machine for later verification, you may want to measure the transaction time of the download process. To do this, you can capture data from the server response and save it to a file using standard file operations. Just be sure you know the type of file you will be downloading.

Here's an example of downloading a `.pdf` file and saving it to your local system:

// Declare variables

int filePointer;

long fileSize;

// Create a file for writing

filePointer = fopen("c://test_file.pdf", "wb");

// Start a transaction to measure download time

lr_start_transaction("file_download");

// Increase the parameter size to accommodate the data

web_set_max_html_param_len("100000");

// Use web_reg_save_param with the appropriate boundaries to capture server response data for the download

web_reg_save_param("FILEDATA", "LB=", "RB=", "Search=Body", LAST);

// HTTP request to download the .pdf file

web_url("http://serverURL:port/app/resource/getme.pdf");

// Retrieve the download size

fileSize = web_get_int_property(HTTP_INFO_DOWNLOAD_SIZE);

// Write the captured data to an output file

fwrite(lr_eval_string("{FILEDATA}"), fileSize, 1, filePointer);

// End the transaction

lr_end_transaction("file_download", LR_AUTO);

// Close the file

fclose(filePointer);

This code snippet demonstrates how to use file operations and LoadRunner functions to download a PDF file from a server, capture the download data, save it to a local file, and measure the transaction time. By following this process, you can efficiently analyze the download performance without needing to store the downloaded files on your machine for later verification.

Python Script for Dynamically Generating LoadRunner Transaction Names | Automate Transaction Names in LoadRunner

In performance testing and monitoring, it's crucial to understand how different parts of your application are performing under various conditions. Monitoring transactions around key sections of code, such as API calls and critical functions, helps identify performance bottlenecks and areas for optimization. LoadRunner provides powerful tools for performance testing, including functions like `lr_start_transaction` and `lr_end_transaction` that enable you to measure the execution time of specific code blocks. However, adding these functions manually can be a time-consuming and error-prone process. To streamline this task, I've developed a script that automatically inserts transaction monitoring statements around key function calls in a C file. This script simplifies the process and helps you achieve more efficient and consistent performance testing results. Let's explore how this script works.

import re

# Open the data file

with open('C:\\Users\\easyloadrunner\\Downloads\\FeatureChange-V1\\Action.c', 'r') as file:

    data = file.read()

# Split the data into lines

lines = data.split('\n')

# Initialize a variable to store the captured value

captured_value = ""

# Open the output file

with open('C:\\Users\\easyloadrunner\\Downloads\\FeatureChange-V1\\ModifiedAction.C', 'w') as output_file:

    # Loop through each line

    for line in lines:

        # Check if the line contains "web_custom_request "

        if "web_custom_request(" in line:

            # Use regular expression to capture the dynamic value

            captured_value = re.search(r'web_custom_request\("(.+?)"', line).group(1)

            # Add the captured value to the start of the transaction

            new_line = 'lr_start_transaction("' + captured_value + '");\n' + line

        elif "LAST);" in line:

            # Add the end of the transaction

            new_line = line + '\n' + 'lr_end_transaction("' + captured_value + '", LR_AUTO);'

        else:

            new_line = line

        # Write the modified line to the output file

        output_file.write(new_line + '\n')