UNDER CONSTRUCTION
Simple library to compress/uncompress Async streams using file iterator and readers.
It supports the following compression format:
- gzip
- bzip2
- snappy
- zstandard
- parquet (experimental)
- orc (experimental)
Install the library as follows:
pip install asyncstream
Compress a regular file to gzip (examples/simple_compress_gzip.py):
importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('samples/animals.txt', 'rb') asfd:
asyncwithasyncstream.open('samples/animals.txt.gz', compression='gzip') asgzfd:
asyncforlineinfd:
awaitgzfd.write(line)
if__name__=='__main__':
asyncio.run(run())or you can also open from an async file descriptor using aiofiles (examples/simple_compress_gzip_with_aiofiles.py):
pip install aiofiles
And then run the following code:
importaiofilesimportasyncstreamimportasyncioasyncdefrun():
asyncwithaiofiles.open('examples/animals.txt', 'rb') asfd:
asyncwithaiofiles.open('/tmp/animals.txt.gz', 'wb') aswfd:
asyncwithasyncstream.open(wfd, 'wb', compression='gzip') asgzfd:
asyncforlineinfd:
awaitgzfd.write(line)
if__name__=='__main__':
asyncio.run(run())You can also uncompress an S3 file on the fly using aiobotocore:
pip install aiobotocore
And then run the following code (examples/simple_uncompress_bzip2_from_s3.py):
importaiobotocoreimportasyncstreamimportasyncioasyncdefrun():
session=aiobotocore.get_session()
asyncwithsession.create_client('s3') ass3:
obj=awaits3.get_object(Bucket='test-bucket', Key='path/to/file.bz2')
asyncwithasyncstream.open(obj['Body'], 'rt', compression='bzip2') asfd:
asyncforlineinfd:
print(line)
if__name__=='__main__':
asyncio.run(run())importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('samples/animals.txt.gz', 'rb', compression='gzip') asinc_fd:
asyncwithasyncstream.open('samples/animals.txt.snappy', 'wb', compression='snappy') asoutc_fd:
asyncforlineininc_fd:
awaitoutc_fd.write(line)
if__name__=='__main__':
asyncio.run(run())importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('/tmp/animals.txt.bz2', 'rb') asin_fd:
asyncwithasyncstream.open('/tmp/animals.txt.snappy', 'wb') asout_fd:
asyncwithasyncstream.reader(in_fd) asreader:
asyncwithasyncstream.writer(out_fd) aswriter:
asyncforname, color, ageinreader:
ifcolor!='white':
awaitwriter.writerow([name, color, age*2])
asyncio.run(run())You will need to install pyarrow and pandas:
pip install pyarrow pandas
To compress using snappy, you can install snappy:
pip install snappy
The code below converts a csv file and convert it to parquet
importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('examples/animals.txt', 'rb') asfd:
asyncwithasyncstream.open('output.parquet', 'wb', encoding='parquet', compression='snappy') aswfd:
asyncwithasyncstream.writer(wfd) aswriter:
asyncforlineinfd:
awaitwriter.write(line)
asyncio.run(run())importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('output.parquet', 'rb', encoding='parquet') asfd:
asyncwithasyncstream.reader(fd) asreader:
asyncforlineinreader:
print(line)
asyncio.run(run())importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('examples/animals.txt', 'rb') asfd:
asyncwithasyncstream.open('output.orc.snappy', 'wb', encoding='orc', compression='snappy') aswfd:
asyncwithasyncstream.writer(wfd) aswriter:
asyncforlineinfd:
awaitwriter.write(line)
asyncio.run(run())importasyncstreamimportasyncioasyncdefrun():
asyncwithasyncstream.open('output.orc.snappy', 'rb', encoding='orc') asfd:
asyncwithasyncstream.reader(fd) asreader:
asyncforlineinreader:
print(line)
asyncio.run(run())asyncstream.open(afd: Union[str, AsyncBufferedIOBase], mode=None, encoding=None, compression=None, compress_level=-1)
Open an async file (using its filename or an AsyncBufferedIOBase) and compress or decompress on the fly depending on
the mode (r or w).
Inputs:
mode:rorwandt(text) orb(binary)encoding:None,parquetororccompression: See the compression supported sectioncompress_level: Optional if compression is used
The AsyncFileObj object returned has the following methods:
flush(): used when open in write modeclose(): close file descriptor and release resources. It is done automatically when theasync withblock is exited
asyncstream.reader(afd: AsyncFileObj, columns=Optional[Iterable[str]], column_types=Optional[Iterable[str]], has_header=False, sep=',', eol='\n')
Create an async reader using AsyncFileObj returned by the asyncstream.open method. It must be open in text mode (t).
Inputs:
afd: AsyncFileObj created withasyncstream.opencolumns: optional list of column names to use. If it is not set and has_header is true, then it will use the first row as the column namescolumn_types: optional list of column types (by default it will consider all the columns to bestring)has_header: the file has the first line set as headersep: separator between valueseol: end of line character
asyncstream.writer(afd: AsyncFileObj, columns: Optional[Iterable[str]] = None, column_types: Optional[Iterable[str]] = None, has_header: bool = True, sep=',', eol='\n')
Create an async writer using AsyncFileObj returned by the asyncstream.open method. It must be open in text mode (t).
Inputs:
afd: AsyncFileObj created withasyncstream.openin text modetand writewcolumns: optional list of column names to use. If it is not set and has_header is true, then it will use the first row as the column namescolumn_types: optional list of column types (by default it will consider all the columns to bestring)has_header: the file has the first line set as headersep: separator between valueseol: end of line character
| Compression | Status |
|---|---|
gzip / zlib | ✅ |
bzip2 | ✅ |
snappy | ✅ |
zstd | ✅ |
| Compression | Status |
|---|---|
| none | ✅ |
brotli | ✅ |
bzip2 | ❌ |
gzip | ❌ |
snappy | ✅ |
zstd | ❌ |
zlib | ✅ |
| Compression | Status |
|---|---|
| none | ✅ |
bzip2 | ❌ |
gzip / zlib | ✅ |
snappy | ✅ |
zlib | ✅ |
zstd | ✅ |