read_csv(compression='gzip') fails while reading compressed file from s3

[mandarup]

reading gzipped csv from s3 bucket (private)

import pandas as pd
import boto3

session = boto3.Session()
s3client = session.client('s3')
obj = s3client.get_object(Bucket=bucket_name, Key=objkey)
df = pd.read_csv(obj['Body'], compression='gzip', nrows=5, engine='python')

Error

 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 562, in parser_f
   return _read(filepath_or_buffer, kwds)
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 315, in _read
   parser = TextFileReader(filepath_or_buffer, **kwds)
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 645, in __init__
   self._make_engine(self.engine)
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 805, in _make_engine
   self._engine = klass(self.f, **self.options)
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 1608, in __init__
   self.columns, self.num_original_columns = self._infer_columns()
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 1823, in _infer_columns
   line = self._buffered_line()
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 1975, in _buffered_line
   return self._next_line()
 File "/Users/username/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py", line 2006, in _next_line
   orig_line = next(self.data)
 File "/Users/username/anaconda/lib/python2.7/gzip.py", line 464, in readline
   c = self.read(readsize)
 File "/Users/username/anaconda/lib/python2.7/gzip.py", line 268, in read
   self._read(readsize)
 File "/Users/username/anaconda/lib/python2.7/gzip.py", line 295, in _read
   pos = self.fileobj.tell()   # Save current position
AttributeError: 'StreamingBody' object has no attribute 'tell'

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 20.3
Cython: 0.23.4
numpy: 1.11.1
scipy: 0.18.0
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: 1.4.5
patsy: 0.4.0
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: None

[jreback]

see #13137 I don't think this is fully compat with pandas (boto3). @TomAugspurger

[TomAugspurger]

@mandarup, our current implementation isn't file-like enough for the gzip decompression. As a workaround for now you can use https://github.com/dask/s3fs, which implements more file operations (like .tell), and is what pandas might use in the future. For now, it'd be

import pandas as pd
import s3fs

fs = s3fs.S3FileSystem()

with fs.open('s3://bucket_name/objkey') as f:
    df = pd.read_csv(f, compression='gzip', nrows=5)

Going to close this for now, as it'll be taken care of with #13137.