to-file-like-obj

Python utility function to convert an iterable of bytes or str to a readable file-like object.

It can be seen as the inverse of the two-argument iter function. The iter function allows conversion of file-like objects to iterables, but the function here converts from iterables to file-like objects. This allows you to bridge the gap between incompatible streaming APIs - passing data from sources that offer data as iterables to destinations that only accept file-like objects.

Features

• Inherits from IOBase - some APIs require this
• The resulting file-like object is well-behaved - it does not return more data than requested
• It evaluates the iterable lazily - avoiding loading all its data into memory
• Under the hood copying is avoided as much as possible
• Converts iterables of bytes to bytes-based file-like objects, which can be passed to boto3's upload_fileobj or to io.TextIOWrapper which is useful in stream CSV parsing.
• Converts iterables of str to text-based file-like objects, which can be passed to psycopg2's copy_expert

Installation

pip install to-file-like-obj

Usage

If you have an iterable of bytes instances, you can pass them to the to_file_like_obj function, and it will return the corresponding file-like object.

from to_file_like_obj import to_file_like_obj

f = to_file_like_obj((b'one', b'two', b'three',))

print(f.read(5))  # b'onetw'
print(f.read(6))  # b'othree'

If you have an iterable of str instances, you can pass them to the to_file_like_obj, along with base=str as a named argument, and it will return the corresponding file-like object.

from to_file_like_obj import to_file_like_obj

f = to_file_like_obj(('one', 'two', 'three',), base=str)

print(f.read(5))  # 'onetw'
print(f.read(6))  # 'othree'

These examples have the iterables hard coded and so loaded all into memory. However, to_file_like_obj works equally well with iterables that are generated dynamically, and without loading them all into memory.

Recipe: parsing a CSV file while downloading it

Using httpx it's possible to use the to_file_like_obj function to parse a CSV file while downloading it.

import csv
import io

import httpx
from to_file_like_obj import to_file_like_obj

with httpx.stream("GET", "https://www.example.com/my.csv") as r:
    bytes_iter = r.iter_bytes()
    f = to_file_like_obj(bytes_iter)
    lines_iter = io.TextIOWrapper(f, newline='', encoding='utf=8')
    rows_iter = csv.reader(lines):
    for row in rows_iter:
        print(row)

Recipe: parsing a zipped CSV file while downloading it

Similarly, using httpx and stream-unzip, it's possible to use the to_file_like_obj function to robustly parse a zipped CSV file while downloading it.

import csv
import io

import httpx
from stream_unzip import stream_unzip
from to_file_like_obj import to_file_like_obj

with httpx.stream("GET", "https://www.example.com/my.zip") as r:
    zipped_bytes_iter = r.iter_bytes()
    # Assumes a single CSV file in the ZIP (in the case of more, this will concatanate them together)
    unzipped_bytes_iter = (
        chunk
        for _, _, chunks in stream_unzip(zipped_bytes_iter)
        for chunk in chunks
    )
    f = to_file_like_obj(unzipped_bytes_iter)
    lines_iter = io.TextIOWrapper(f, newline='', encoding='utf=8')
    rows_iter = csv.reader(lines):
    for row in rows_iter:
        print(row)

Recipe: uploading large objects to S3 while receiving their contents

boto3's upload_fileobj is a powerful function, but it's not obvious that it can be used with iterables of bytes that are returned from various APIs, such as those in httpx.

import httpx
from to_file_like_obj import to_file_like_obj

s3 = boto3.client('s3')

with httpx.stream("GET", "https://www.example.com/my.zip") as r:
    bytes_iter = r.iter_bytes()
    f = to_file_like_obj(bytes_iter)
    s3.upload_fileobj(f, 'my-bucket', 'my.zip')

Recipe: stream-zipping while uploading to S3

stream-zip can be used with boto3 and this package to upload objects to S3 while zipping them.

import datetime
import httpx
from stat import S_IFREG
from to_file_like_obj import to_file_like_obj
from stream_zip import ZIP_32, stream_zip

s3 = boto3.client('s3')

with httpx.stream("GET", "https://www.example.com/my.txt") as r:
    unzipped_bytes_iter = r.iter_bytes()
    member_files = (
        (
            'my.txt',
            datetime.now(),
            S_IFREG | 0o600,
            ZIP_32,
            unzipped_bytes_iter,
        ),
    )
    zipped_bytes_iter = stream_zip(member_files)
    f = to_file_like_obj(zipped_bytes_iter)
    s3.upload_fileobj(f, 'my-bucket', 'my.zip')