vercel_blob 0.4.2

A Python Wrapper for Vercel Blob Storage API

vercel_blob

A Python wrapper for the Vercel Blob Storage API

Installation

pip3 install vercel_blob

Getting Started

Python Version

This package (vercel_blob) was written using Python 3 in mind, and Python 2 will not work properly.

Set Environment Variable for Authorization

export BLOB_READ_WRITE_TOKEN="superssecretkey"

Add vercel_blob to your code

import vercel_blob
#or
import vercel_blob.blob_store
# or if you want to use an alias
import vercel_blob.blob_store as vb_store

Using vercel_blob

Currently only supports the basic list, put, delete, copy and head(get file metadata) operations. Here's a quick overview:

List all files in the Blob Storage

The list method will return a list of all files in the blob storage. You can pass 'limit' to limit the returned number of blobs.

def list_all_blobs():
    blobs = vercel_blob.list({
        'limit': '5',
    })

list() returns a JSON object in the following format:

blobs: {
  size: `number`;
  uploadedAt: `Date`;
  pathname: `string`;
  url: `string`;
  downloadUrl: `string`
}[]
cursor?: `string`;
hasMore: `boolean`;
folders?: `string[]`

For a long list of blob objects (the default list limit is 1000), you can use the cursor and hasMore parameters to paginate through the results as shown in the example below:

blobs = vercel_blob.list({
        'limit': '4',
        'cursor': cursor,
    })

Upload File / Blob to the Storage

The put method can be used to upload a blob to the blob store. If the blob is already present in the store, it will be overwritten.

def upload_a_blob():
    with open('file.txt', 'rb') as f:
        resp = vercel_blob.put('test.txt', f.read(), verbose=True)
        print(resp)

The method takes in the filename as the first argument, and the bytes of the file as the second argument. The third parameters can be the options dictionary. The verbose parameter (default: False) can be used to show detailed progress information during upload.

For large files, you can enable multipart uploads by passing multipart=True to the put method. This splits the file into smaller parts, offering resilience against network issues and potentially speeding up the upload process. Vercel Blob Storage supports multipart uploads for files up to 5TB.

def upload_large_file_multipart():
    with open('large_video.mp4', 'rb') as f:
        resp = vercel_blob.put('large_video.mp4', f.read(), multipart=True, verbose=True)
        print(resp)

The response object would look something like this:

pathname: `string`,
contentType: `string`,
contentDisposition: `string`,
url: `string`
downloadUrl: `string`

By default, blobs are uploaded without a random suffix. If you want to add a random suffix to prevent overwriting existing files, you can set the 'addRandomSuffix' parameter to "true" in the options dictionary. Here's an example:

def upload_a_blob():
    with open('file.txt', 'rb') as f:
        resp = vercel_blob.put('test.txt', f.read(), {
                "addRandomSuffix": "true",
            })
        print(resp)

Delete a blob or a list of blobs from the Blob Storage

The delete method will delete a file from the Blob Storage. It takes in the URL of the blob, or a list of blobs. Here's an example:

def delete_a_list_of_blobs():
    resp = vercel_blob.delete([
            'blob_url_1',
            'blob_url_2'
        ])
    print(resp)

Printing the response will result in "None", since the delete method does not return anything. If a blob is present, it will be deleted. If a blob is not present, it will not result in any error.

Get blob metadata

The head method will return the blob object's metadata.

def get_blob_metadata():
    resp = vercel_blob.head('blob_url')
    print(resp)

The JSON object returned will contain the following properties:

  size: `number`;
  uploadedAt: `Date`;
  pathname: `string`;
  contentType: `string`;
  contentDisposition: `string`;
  url: `string`;
  downloadUrl: `string`
  cacheControl: `string`;

If the blob url provided is not valid, an Exception will be thrown.

Copy blob from one folder to another

The copy method can be used to copy an existing blob to another location inside the same blob store. Note that the addRandomSuffix option is False by default for copy operations, hence it overwrites by default. To prevent this behavior, you can set the 'addRandomSuffix' option to "true".

def copy_a_blob():
    resp = vercel_blob.copy("https://surya.public.blob.vercel-storage.com/test.txt", "new-folder/test.txt", verbose=True)
    print(resp)

The verbose parameter (default: False) can be used to show detailed progress information during the copy operation.

The JSON representation of the response should look something like this:

  pathname: `string`,
  contentType: `string`,
  contentDisposition: `string`,
  url: `string`
  downloadUrl: `string`

Download a file on the server

If you want to make the client download a file, you just redirect him to the downloadUrl. But for the server, you can use the download_file() method.

def download_a_file_on_the_server():
    vercel_blob.download_file('blob_url', 'path/to/directory/', {'token': 'my_token'}, verbose=True)

The file will be downloaded to the specified directory. If no directory is specified, it will be downloaded to the program's base directory. The verbose parameter (default: False) can be used to show detailed progress information during download.

Common Issues

1. Since this storage is still in beta, the requests sometimes results in unexpected Connection Errors. To mitigate this, I used a 'retry request' function, that attempts 3 requests with exponential backoff between requests.

   This might result in error messages like Request failed on attempt 1 (HTTPSConnectionPool(host='blob.vercel-storage.com', port=443): Read timed out. (read timeout=10)) in the terminal.