title: Can python fastparquet module read in compressed parquet file?
body: <p>Our parquet files are stored in aws S3 bucket and are compressed by SNAPPY. 
  I was able to use python fastparquet module to read in the uncompressed version of the parquet file but not the compressed version. </p>
  
  <p>This is the code I am using for uncompressed </p>
  
  <pre><code>s3 = s3fs.S3FileSystem(key='XESF',    secret='dsfkljsf')
  myopen = s3.open
  pf = ParquetFile('sample/py_test_snappy/part-r-12423423942834.parquet', open_with=myopen)
  df=pf.to_pandas()
  </code></pre>
  
  <p>This return no error but when I am trying to read in the snappy compressed version of the file:</p>
  
  <pre><code>pf = ParquetFile('sample/py_test_snappy/part-r-12423423942834.snappy.parquet', open_with=myopen)
  </code></pre>
  
  <p>I got error with to_pandas()</p>
  
  <pre><code>df=pf.to_pandas()
  </code></pre>
  
  <p>Error message</p>
  
  <blockquote>
    <p>KeyErrorTraceback (most recent call last)
     in ()
    ----> 1 df=pf.to_pandas()</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/api.py in
    to_pandas(self, columns, categories, filters, index)
        293                              for (name, v) in views.items()}
        294                     self.read_row_group(rg, columns, categories, infile=f,
    --> 295                                         index=index, assign=parts)
        296                     start += rg.num_rows
        297         else:</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/api.py in
    read_row_group(self, rg, columns, categories, infile, index, assign)
        151         core.read_row_group(
        152                 infile, rg, columns, categories, self.helper, self.cats,
    --> 153                 self.selfmade, index=index, assign=assign)
        154         if ret:
        155             return df</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/core.py in
    read_row_group(file, rg, columns, categories, schema_helper, cats,
    selfmade, index, assign)
        300         raise RuntimeError('Going with pre-allocation!')
        301     read_row_group_arrays(file, rg, columns, categories, schema_helper,
    --> 302                           cats, selfmade, assign=assign)
        303 
        304     for cat in cats:</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/core.py in
    read_row_group_arrays(file, rg, columns, categories, schema_helper,
    cats, selfmade, assign)
        289         read_col(column, schema_helper, file, use_cat=use,
        290                  selfmade=selfmade, assign=out[name],
    --> 291                  catdef=out[name+'-catdef'] if use else None)
        292 
        293 </p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/core.py in
    read_col(column, schema_helper, infile, use_cat, grab_dict, selfmade,
    assign, catdef)
        196     dic = None
        197     if ph.type == parquet_thrift.PageType.DICTIONARY_PAGE:
    --> 198         dic = np.array(read_dictionary_page(infile, schema_helper, ph, cmd))
        199         ph = read_thrift(infile, parquet_thrift.PageHeader)
        200         dic = convert(dic, se)</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/core.py in
    read_dictionary_page(file_obj, schema_helper, page_header,
    column_metadata)
        152     Consumes data using the plain encoding and returns an array of values.
        153     """
    --> 154     raw_bytes = _read_page(file_obj, page_header, column_metadata)
        155     if column_metadata.type == parquet_thrift.Type.BYTE_ARRAY:
        156         # no faster way to read variable-length-strings?</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/core.py in
    _read_page(file_obj, page_header, column_metadata)
         28     """Read the data page from the given file-object and convert it to raw, uncompressed bytes (if necessary)."""
         29     raw_bytes = file_obj.read(page_header.compressed_page_size)
    ---> 30     raw_bytes = decompress_data(raw_bytes, column_metadata.codec)
         31 
         32     assert len(raw_bytes) == page_header.uncompressed_page_size, \</p>
    
    <p>/opt/conda/lib/python3.5/site-packages/fastparquet/compression.py in
    decompress_data(data, algorithm)
         48 def decompress_data(data, algorithm='gzip'):
         49     if isinstance(algorithm, int):
    ---> 50         algorithm = rev_map[algorithm]
         51     if algorithm.upper() not in decompressions:
         52         raise RuntimeError("Decompression '%s' not available.  Options: %s" %</p>
    
    <p>KeyError: 1</p>
  </blockquote>