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408 lines
19 KiB
Python
408 lines
19 KiB
Python
#!/usr/bin/env python
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#Processes uploads from the user.
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# WARNING: Changes in this tool (particularly as related to parsing) may need
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# to be reflected in galaxy.web.controllers.tool_runner and galaxy.tools
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import urllib, sys, os, gzip, tempfile, shutil, re, gzip, zipfile, codecs, binascii
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from galaxy import eggs
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# need to import model before sniff to resolve a circular import dependency
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import galaxy.model
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from galaxy.datatypes.checkers import *
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from galaxy.datatypes import sniff
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from galaxy.datatypes.binary import *
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from galaxy.datatypes.images import Pdf
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from galaxy.datatypes.registry import Registry
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from galaxy import util
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from galaxy.datatypes.util.image_util import *
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from galaxy.util.json import *
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try:
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import Image as PIL
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except ImportError:
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try:
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from PIL import Image as PIL
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except:
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PIL = None
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try:
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import bz2
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except:
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bz2 = None
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assert sys.version_info[:2] >= ( 2, 4 )
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def stop_err( msg, ret=1 ):
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sys.stderr.write( msg )
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sys.exit( ret )
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def file_err( msg, dataset, json_file ):
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json_file.write( to_json_string( dict( type = 'dataset',
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ext = 'data',
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dataset_id = dataset.dataset_id,
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stderr = msg ) ) + "\n" )
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# never remove a server-side upload
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if dataset.type in ( 'server_dir', 'path_paste' ):
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return
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try:
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os.remove( dataset.path )
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except:
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pass
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def safe_dict(d):
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"""
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Recursively clone json structure with UTF-8 dictionary keys
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http://mellowmachines.com/blog/2009/06/exploding-dictionary-with-unicode-keys-as-python-arguments/
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"""
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if isinstance(d, dict):
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return dict([(k.encode('utf-8'), safe_dict(v)) for k,v in d.iteritems()])
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elif isinstance(d, list):
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return [safe_dict(x) for x in d]
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else:
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return d
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def parse_outputs( args ):
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rval = {}
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for arg in args:
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id, files_path, path = arg.split( ':', 2 )
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rval[int( id )] = ( path, files_path )
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return rval
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def add_file( dataset, registry, json_file, output_path ):
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data_type = None
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line_count = None
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converted_path = None
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stdout = None
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link_data_only = dataset.get( 'link_data_only', 'copy_files' )
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in_place = dataset.get( 'in_place', True )
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try:
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ext = dataset.file_type
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except AttributeError:
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file_err( 'Unable to process uploaded file, missing file_type parameter.', dataset, json_file )
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return
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if dataset.type == 'url':
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try:
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page = urllib.urlopen( dataset.path ) #page will be .close()ed by sniff methods
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temp_name, dataset.is_multi_byte = sniff.stream_to_file( page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers( page.headers ) )
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except Exception, e:
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file_err( 'Unable to fetch %s\n%s' % ( dataset.path, str( e ) ), dataset, json_file )
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return
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dataset.path = temp_name
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# See if we have an empty file
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if not os.path.exists( dataset.path ):
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file_err( 'Uploaded temporary file (%s) does not exist.' % dataset.path, dataset, json_file )
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return
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if not os.path.getsize( dataset.path ) > 0:
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file_err( 'The uploaded file is empty', dataset, json_file )
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return
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if not dataset.type == 'url':
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# Already set is_multi_byte above if type == 'url'
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try:
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dataset.is_multi_byte = util.is_multi_byte( codecs.open( dataset.path, 'r', 'utf-8' ).read( 100 ) )
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except UnicodeDecodeError, e:
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dataset.is_multi_byte = False
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# Is dataset an image?
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image = check_image( dataset.path )
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if image:
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if not PIL:
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image = None
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# get_image_ext() returns None if nor a supported Image type
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ext = get_image_ext( dataset.path, image )
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data_type = ext
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# Is dataset content multi-byte?
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elif dataset.is_multi_byte:
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data_type = 'multi-byte char'
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ext = sniff.guess_ext( dataset.path, is_multi_byte=True )
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# Is dataset content supported sniffable binary?
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else:
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type_info = Binary.is_sniffable_binary( dataset.path )
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if type_info:
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data_type = type_info[0]
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ext = type_info[1]
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if not data_type:
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# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
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is_gzipped, is_valid = check_gzip( dataset.path )
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if is_gzipped and not is_valid:
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file_err( 'The gzipped uploaded file contains inappropriate content', dataset, json_file )
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return
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elif is_gzipped and is_valid:
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if link_data_only == 'copy_files':
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# We need to uncompress the temp_name file, but BAM files must remain compressed in the BGZF format
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CHUNK_SIZE = 2**20 # 1Mb
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fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_gunzip_' % dataset.dataset_id, dir=os.path.dirname( output_path ), text=False )
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gzipped_file = gzip.GzipFile( dataset.path, 'rb' )
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while 1:
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try:
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chunk = gzipped_file.read( CHUNK_SIZE )
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except IOError:
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os.close( fd )
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os.remove( uncompressed )
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file_err( 'Problem decompressing gzipped data', dataset, json_file )
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return
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if not chunk:
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break
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os.write( fd, chunk )
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os.close( fd )
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gzipped_file.close()
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# Replace the gzipped file with the decompressed file if it's safe to do so
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if dataset.type in ( 'server_dir', 'path_paste' ) or not in_place:
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dataset.path = uncompressed
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else:
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shutil.move( uncompressed, dataset.path )
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os.chmod(dataset.path, 0644)
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dataset.name = dataset.name.rstrip( '.gz' )
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data_type = 'gzip'
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if not data_type and bz2 is not None:
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# See if we have a bz2 file, much like gzip
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is_bzipped, is_valid = check_bz2( dataset.path )
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if is_bzipped and not is_valid:
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file_err( 'The gzipped uploaded file contains inappropriate content', dataset, json_file )
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return
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elif is_bzipped and is_valid:
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if link_data_only == 'copy_files':
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# We need to uncompress the temp_name file
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CHUNK_SIZE = 2**20 # 1Mb
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fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_bunzip2_' % dataset.dataset_id, dir=os.path.dirname( output_path ), text=False )
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bzipped_file = bz2.BZ2File( dataset.path, 'rb' )
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while 1:
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try:
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chunk = bzipped_file.read( CHUNK_SIZE )
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except IOError:
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os.close( fd )
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os.remove( uncompressed )
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file_err( 'Problem decompressing bz2 compressed data', dataset, json_file )
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return
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if not chunk:
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break
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os.write( fd, chunk )
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os.close( fd )
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bzipped_file.close()
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# Replace the bzipped file with the decompressed file if it's safe to do so
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if dataset.type in ( 'server_dir', 'path_paste' ) or not in_place:
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dataset.path = uncompressed
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else:
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shutil.move( uncompressed, dataset.path )
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os.chmod(dataset.path, 0644)
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dataset.name = dataset.name.rstrip( '.bz2' )
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data_type = 'bz2'
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if not data_type:
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# See if we have a zip archive
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is_zipped = check_zip( dataset.path )
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if is_zipped:
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if link_data_only == 'copy_files':
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CHUNK_SIZE = 2**20 # 1Mb
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uncompressed = None
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uncompressed_name = None
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unzipped = False
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z = zipfile.ZipFile( dataset.path )
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for name in z.namelist():
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if name.endswith('/'):
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continue
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if unzipped:
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stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
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break
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fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_zip_' % dataset.dataset_id, dir=os.path.dirname( output_path ), text=False )
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if sys.version_info[:2] >= ( 2, 6 ):
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zipped_file = z.open( name )
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while 1:
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try:
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chunk = zipped_file.read( CHUNK_SIZE )
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except IOError:
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os.close( fd )
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os.remove( uncompressed )
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file_err( 'Problem decompressing zipped data', dataset, json_file )
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return
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if not chunk:
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break
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os.write( fd, chunk )
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os.close( fd )
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zipped_file.close()
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uncompressed_name = name
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unzipped = True
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else:
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# python < 2.5 doesn't have a way to read members in chunks(!)
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try:
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outfile = open( uncompressed, 'wb' )
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outfile.write( z.read( name ) )
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outfile.close()
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uncompressed_name = name
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unzipped = True
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except IOError:
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os.close( fd )
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os.remove( uncompressed )
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file_err( 'Problem decompressing zipped data', dataset, json_file )
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return
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z.close()
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# Replace the zipped file with the decompressed file if it's safe to do so
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if uncompressed is not None:
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if dataset.type in ( 'server_dir', 'path_paste' ) or not in_place:
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dataset.path = uncompressed
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else:
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shutil.move( uncompressed, dataset.path )
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os.chmod(dataset.path, 0644)
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dataset.name = uncompressed_name
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data_type = 'zip'
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if not data_type:
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# TODO refactor this logic. check_binary isn't guaranteed to be
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# correct since it only looks at whether the first 100 chars are
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# printable or not. If someone specifies a known unsniffable
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# binary datatype and check_binary fails, the file gets mangled.
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if check_binary( dataset.path ) or Binary.is_ext_unsniffable(dataset.file_type):
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# We have a binary dataset, but it is not Bam, Sff or Pdf
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data_type = 'binary'
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#binary_ok = False
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parts = dataset.name.split( "." )
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if len( parts ) > 1:
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ext = parts[-1].strip().lower()
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if not Binary.is_ext_unsniffable(ext):
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file_err( 'The uploaded binary file contains inappropriate content', dataset, json_file )
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return
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elif Binary.is_ext_unsniffable(ext) and dataset.file_type != ext:
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err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % ( ext.capitalize(), ext )
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file_err( err_msg, dataset, json_file )
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return
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if not data_type:
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# We must have a text file
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if check_html( dataset.path ):
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file_err( 'The uploaded file contains inappropriate HTML content', dataset, json_file )
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return
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if data_type != 'binary':
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if link_data_only == 'copy_files':
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if dataset.type in ( 'server_dir', 'path_paste' ) and data_type not in [ 'gzip', 'bz2', 'zip' ]:
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in_place = False
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# Convert universal line endings to Posix line endings, but allow the user to turn it off,
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# so that is becomes possible to upload gzip, bz2 or zip files with binary data without
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# corrupting the content of those files.
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if dataset.to_posix_lines:
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tmpdir = output_adjacent_tmpdir( output_path )
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tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
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if dataset.space_to_tab:
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line_count, converted_path = sniff.convert_newlines_sep2tabs( dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix )
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else:
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line_count, converted_path = sniff.convert_newlines( dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix )
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if dataset.file_type == 'auto':
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ext = sniff.guess_ext( dataset.path, registry.sniff_order )
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else:
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ext = dataset.file_type
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data_type = ext
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# Save job info for the framework
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if ext == 'auto' and dataset.ext:
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ext = dataset.ext
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if ext == 'auto':
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ext = 'data'
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datatype = registry.get_datatype_by_extension( ext )
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if dataset.type in ( 'server_dir', 'path_paste' ) and link_data_only == 'link_to_files':
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# Never alter a file that will not be copied to Galaxy's local file store.
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if datatype.dataset_content_needs_grooming( dataset.path ):
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err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
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'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
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file_err( err_msg, dataset, json_file )
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return
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if link_data_only == 'copy_files' and dataset.type in ( 'server_dir', 'path_paste' ) and data_type not in [ 'gzip', 'bz2', 'zip' ]:
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# Move the dataset to its "real" path
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if converted_path is not None:
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shutil.copy( converted_path, output_path )
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try:
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os.remove( converted_path )
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except:
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pass
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else:
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# This should not happen, but it's here just in case
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shutil.copy( dataset.path, output_path )
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elif link_data_only == 'copy_files':
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shutil.move( dataset.path, output_path )
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# Write the job info
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stdout = stdout or 'uploaded %s file' % data_type
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info = dict( type = 'dataset',
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dataset_id = dataset.dataset_id,
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ext = ext,
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stdout = stdout,
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name = dataset.name,
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line_count = line_count )
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if dataset.get('uuid', None) is not None:
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info['uuid'] = dataset.get('uuid')
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json_file.write( to_json_string( info ) + "\n" )
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if link_data_only == 'copy_files' and datatype.dataset_content_needs_grooming( output_path ):
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# Groom the dataset content if necessary
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datatype.groom_dataset_content( output_path )
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def add_composite_file( dataset, registry, json_file, output_path, files_path ):
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if dataset.composite_files:
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os.mkdir( files_path )
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for name, value in dataset.composite_files.iteritems():
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value = util.bunch.Bunch( **value )
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if dataset.composite_file_paths[ value.name ] is None and not value.optional:
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file_err( 'A required composite data file was not provided (%s)' % name, dataset, json_file )
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break
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elif dataset.composite_file_paths[value.name] is not None:
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dp = dataset.composite_file_paths[value.name][ 'path' ]
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isurl = dp.find('://') <> -1 # todo fixme
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if isurl:
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try:
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temp_name, dataset.is_multi_byte = sniff.stream_to_file( urllib.urlopen( dp ), prefix='url_paste' )
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except Exception, e:
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file_err( 'Unable to fetch %s\n%s' % ( dp, str( e ) ), dataset, json_file )
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return
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dataset.path = temp_name
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dp = temp_name
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if not value.is_binary:
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tmpdir = output_adjacent_tmpdir( output_path )
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tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
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if dataset.composite_file_paths[ value.name ].get( 'space_to_tab', value.space_to_tab ):
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sniff.convert_newlines_sep2tabs( dp, tmp_dir=tmpdir, tmp_prefix=tmp_prefix )
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else:
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sniff.convert_newlines( dp, tmp_dir=tmpdir, tmp_prefix=tmp_prefix )
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shutil.move( dp, os.path.join( files_path, name ) )
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# Move the dataset to its "real" path
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shutil.move( dataset.primary_file, output_path )
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# Write the job info
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info = dict( type = 'dataset',
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dataset_id = dataset.dataset_id,
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stdout = 'uploaded %s file' % dataset.file_type )
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json_file.write( to_json_string( info ) + "\n" )
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def output_adjacent_tmpdir( output_path ):
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""" For temp files that will ultimately be moved to output_path anyway
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just create the file directly in output_path's directory so shutil.move
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will work optimially.
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"""
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return os.path.dirname( output_path )
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def __main__():
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if len( sys.argv ) < 4:
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print >>sys.stderr, 'usage: upload.py <root> <datatypes_conf> <json paramfile> <output spec> ...'
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sys.exit( 1 )
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output_paths = parse_outputs( sys.argv[4:] )
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json_file = open( 'galaxy.json', 'w' )
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registry = Registry()
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registry.load_datatypes( root_dir=sys.argv[1], config=sys.argv[2] )
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for line in open( sys.argv[3], 'r' ):
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dataset = from_json_string( line )
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dataset = util.bunch.Bunch( **safe_dict( dataset ) )
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try:
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output_path = output_paths[int( dataset.dataset_id )][0]
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except:
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print >>sys.stderr, 'Output path for dataset %s not found on command line' % dataset.dataset_id
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sys.exit( 1 )
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if dataset.type == 'composite':
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files_path = output_paths[int( dataset.dataset_id )][1]
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add_composite_file( dataset, registry, json_file, output_path, files_path )
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else:
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add_file( dataset, registry, json_file, output_path )
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# clean up paramfile
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# TODO: this will not work when running as the actual user unless the
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# parent directory is writable by the user.
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try:
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os.remove( sys.argv[3] )
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except:
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pass
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if __name__ == '__main__':
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__main__()
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