Chunked Uploads of Binary Files in Python: A Comprehensive Guide
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Handling large files in Python can be a challenge, especially when it comes to chunked uploads. While there are numerous tutorials available, many tend to focus on text files. However, for scenarios involving binary files, such as videos, the approach differs slightly. In this article, I'll address common challenges and mistakes that may arise when you need to upload large binary files in chunks.
Handling Binary Files
When working with files that aren't text-based, the first issue you'll likely face is inadvertently treating them as text files. If you find a guide tailored for text files, it may still be applicable to binary files, provided you make a few adjustments to help Python identify the file type. Always use the binary mode when opening files. For instance:
f = open(content_path, "rb")
Instead of simply using "r". The same rule applies when writing to files; use "wb" for binary writing. Keeping this in mind will simplify your interactions with binary data.
Header Complications in Chunked Uploads
If you're not well-versed in header options, they can be tricky in the context of chunked uploads. Here are some common headers you might encounter:
- Custom headers
- application/octet-stream
- multipart/form-data
- content-type/whatever
- content-range
Let's quickly examine these headers.
Custom Headers
Different APIs have varying requirements. Always verify the necessary headers before initiating a chunked upload. Pay special attention to custom headers, as they can differ widely between services. Ensure you follow the correct format to avoid errors.
Application/Octet-Stream Header
The application/octet-stream header communicates that the file is binary and not intended for direct execution. This header is commonly used for files that need to be processed by specific applications. For instance, a .doc file can typically be opened with Microsoft Word or Google Docs. For video files, additional metadata may be required for correct assembly and playback based on the service you're using.
Multipart/Form-data Header
The multipart/form-data header can be confusing. It may seem to imply that you're sending multiple chunks, but in fact, you're usually submitting one chunk per request. This header indicates to the server that you're transmitting a series of files along with potentially some form data. You can send multiple files as permitted by the server.
Content-Type Header
The importance of the content-type header varies. Consult the documentation for the specific service you're working with to determine if it's necessary. An incorrect content-type can lead to request failures, so verify this if issues arise.
Content-Range Header
The content-range header is critical for chunked uploads and can lead to perplexing errors if not formatted correctly. The expected format is as follows:
Content-Range: bytes startofchunk-endofchunk/totalsize
Each content-range header specifies where the data in the request fits among the entire series of chunks. A common mistake is miscalculating byte ranges, leading to errors that may not seem related to headers. For example:
UnicodeDecodeError: ‘utf-8’ codec can’t decode byte -somebyte- in position -someposition-: invalid continuation byte
Such errors might mislead you to think the issue lies with file encoding. In reality, it could stem from incorrect byte values in the content-range header. Always ensure that the ending byte of one chunk is followed by the starting byte of the next chunk without overlap or skips.
Using a Generator with the Requests Library
Utilizing a generator with the requests library can streamline chunked uploads, provided you understand how generators function. A generator allows for the creation of an iterator, yielding values instead of returning them. This means a generator retains its state and can continue from where it last left off.
Here's a simple example of a generator:
def read_in_chunks(file_object, CHUNK_SIZE):
while True:
data = file_object.read(CHUNK_SIZE)
if not data:
breakyield data
This generator can be integrated into a function for uploading files:
def upload(file, url):
content_name = str(file)
content_path = os.path.abspath(file)
content_size = os.stat(content_path).st_size
print(content_name, content_path, content_size)
file_object = open(content_path, "rb")
index = 0
offset = 0
headers = {}
for chunk in read_in_chunks(file_object, CHUNK_SIZE):
offset = index + len(chunk)
headers['Content-Range'] = 'bytes %s-%s/%s' % (index, offset - 1, content_size)
headers['Authorization'] = auth_string
index = offset
try:
file = {"file": chunk}
r = requests.post(url, files=file, headers=headers)
print(r.json())
print("r: %s, Content-Range: %s" % (r, headers['Content-Range']))
except Exception as e:
print(e)
In this example, the generator function pauses and resumes, yielding new data each time it is called. Ensure that you correctly set the byte ranges to avoid off-by-one errors.
For further details on generators and chunked uploads, you can refer to the full code example [here](https://github.com/apivideo/python-examples/blob/main/uploads/upload_large_video.py).
I hope this guide helps you navigate the complexities of chunked uploads with binary files in Python. If you have any suggestions or questions, feel free to share them in the comments!