The Best Way to Send multipart/form-data Requests for Large Files in Python

Discover how to effectively upload large files using Python with multipart/form-data requests, even given API constraints.
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The Best Way to Send multipart/form-data Requests for Large Files in Python

When working with large datasets, such as a CSV file containing over 37 million lines, uploading the data can become quite a challenge—especially if the destination API imposes strict limitations on the size of each request. If you find yourself faced with a situation where you need to send a sizable file but only have a limited space to work with, you are not alone. This guide will guide you through a practical solution to efficiently upload large files in manageable chunks using Python.

The Challenge

You might have encountered the following scenario:

File Size: You have a CSV file that is approximately 6GB in size.

API Limitations: The API restricts you to sending only around 2MB or 12,000 lines of data at a time.

Disk Constraints: You encounter a limitation on disk space, which prevents you from splitting the large file into multiple smaller files.

Given these challenges, iterating through the data and sending it in chunks becomes a necessity. Instead of creating multiple smaller files, we can read the file and upload it directly in segments.

The Solution

The solution lies in streaming the file and sending segments of data without needing to write intermediate files on disk. Here’s how you can accomplish this in Python.

Step-by-Step Guide

Import Required Libraries: Make sure you have the requests library installed to facilitate the HTTP request.

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Set Up Your Endpoint: Define the URL of your API endpoint where you need to send the data.

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Create a Function to Read the File: This function will read your large file line by line and yield chunks of data (12,000 lines in each chunk).

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Iterate Through Chunks: Use a loop to process each chunk of lines from your large file and prepare the HTTP request accordingly.

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Key Considerations

Efficiency: This approach minimizes the usage of disk space by not creating temporary files.

Error Handling: Consider adding error handling mechanisms in your code to catch possible exceptions during file access or HTTP requests.

Logging: Implement logging to keep track of the number of chunks sent and any errors encountered during the process.

Conclusion

Using the above method, you can efficiently upload large files to APIs with size constraints without running out of disk space. By reading the input file in chunks and sending each segment in a multipart/form-data request, you can manage your data transfers effectively. With this approach, you'll be able to tackle the challenges posed by large file uploads with confidence!

We hope this guide has been helpful in finding a better way to send multipart/form-data requests for large files in Python. Happy coding!