def looks_like_xml(path, regex=TOOL_REGEX):
full_path = os.path.abspath(path)
if not full_path.endswith(".xml"):
return False
if not os.path.getsize(full_path):
return False
if(checkers.check_binary(full_path) or
checkers.check_image(full_path) or
checkers.is_gzip(full_path) or
checkers.is_bz2(full_path) or
checkers.is_zip(full_path)):
return False
with open(path, encoding='utf-8') as f:
try:
start_contents = f.read(5 * 1024)
except UnicodeDecodeError:
return False
if regex.search(start_contents):
return True
return False
def check_file_content_for_html_and_images(file_path):
message = ''
if checkers.check_html(file_path):
message = 'The file "%s" contains HTML content.\n' % str(file_path)
elif checkers.check_image(file_path):
message = 'The file "%s" contains image content.\n' % str(file_path)
return message
def check_file_content_for_html_and_images(file_path):
message = ''
if checkers.check_html(file_path):
message = 'The file "%s" contains HTML content.\n' % str(file_path)
elif checkers.check_image(file_path):
message = 'The file "%s" contains image content.\n' % str(file_path)
return message
def looks_like_a_tool_xml(path):
full_path = os.path.abspath(path)
if not full_path.endswith(".xml"):
return False
if not os.path.getsize(full_path):
return False
if (checkers.check_binary(full_path) or checkers.check_image(full_path)
or checkers.check_gzip(full_path)[0]
or checkers.check_bz2(full_path)[0]
or checkers.check_zip(full_path)):
return False
with open(path, "r") as f:
start_contents = f.read(5 * 1024)
if TOOL_REGEX.search(start_contents):
return True
return False
def looks_like_a_tool_xml(path):
"""Quick check to see if a file looks like it may be a Galaxy XML tool file."""
full_path = os.path.abspath(path)
if not full_path.endswith(".xml"):
return False
if not os.path.getsize(full_path):
return False
if (checkers.check_binary(full_path) or checkers.check_image(full_path)
or checkers.is_gzip(full_path) or checkers.is_bz2(full_path)
or checkers.is_zip(full_path)):
return False
with open(path, "r") as f:
start_contents = f.read(5 * 1024)
if TOOL_REGEX.search(start_contents):
return True
return False
def looks_like_xml(path, regex=TOOL_REGEX):
full_path = os.path.abspath(path)
if not full_path.endswith(".xml"):
return False
if not os.path.getsize(full_path):
return False
if(checkers.check_binary(full_path) or
checkers.check_image(full_path) or
checkers.is_gzip(full_path) or
checkers.is_bz2(full_path) or
checkers.is_zip(full_path)):
return False
with open(path, "r") as f:
start_contents = f.read(5 * 1024)
if regex.search(start_contents):
return True
return False
def looks_like_a_tool_xml(path):
"""Quick check to see if a file looks like it may be a Galaxy XML tool file."""
full_path = os.path.abspath(path)
if not full_path.endswith(".xml"):
return False
if not os.path.getsize(full_path):
return False
if(checkers.check_binary(full_path) or
checkers.check_image(full_path) or
checkers.check_gzip(full_path)[0] or
checkers.check_bz2(full_path)[0] or
checkers.check_zip(full_path)):
return False
with open(path, "r") as f:
start_contents = f.read(5 * 1024)
if TOOL_REGEX.search(start_contents):
return True
return False
def is_data_index_sample_file( file_path ):
"""
Attempt to determine if a .sample file is appropriate for copying to ~/tool-data when
a tool shed repository is being installed into a Galaxy instance.
"""
# Currently most data index files are tabular, so check that first. We'll assume that
# if the file is tabular, it's ok to copy.
if is_column_based( file_path ):
return True
# If the file is any of the following, don't copy it.
if checkers.check_html( file_path ):
return False
if checkers.check_image( file_path ):
return False
if checkers.check_binary( name=file_path ):
return False
if checkers.is_bz2( file_path ):
return False
if checkers.is_gzip( file_path ):
return False
if checkers.check_zip( file_path ):
return False
# Default to copying the file if none of the above are true.
return True
def is_data_index_sample_file(file_path):
"""
Attempt to determine if a .sample file is appropriate for copying to ~/tool-data when
a tool shed repository is being installed into a Galaxy instance.
"""
# Currently most data index files are tabular, so check that first. We'll assume that
# if the file is tabular, it's ok to copy.
if is_column_based(file_path):
return True
# If the file is any of the following, don't copy it.
if checkers.check_html(file_path):
return False
if checkers.check_image(file_path):
return False
if checkers.check_binary(name=file_path):
return False
if checkers.is_bz2(file_path):
return False
if checkers.is_gzip(file_path):
return False
if checkers.is_zip(file_path):
return False
# Default to copying the file if none of the above are true.
return True
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists( dataset.path ):
file_err( 'Uploaded temporary file (%s) does not exist.' % dataset.path, dataset, json_file )
return
if not os.path.getsize( dataset.path ) > 0:
file_err( 'The uploaded file is empty', dataset, json_file )
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = multi_byte.is_multi_byte( codecs.open( dataset.path, 'r', 'utf-8' ).read( 100 ) )
except UnicodeDecodeError, e:
dataset.is_multi_byte = False
# Is dataset an image?
image = check_image( dataset.path )
if image:
if not PIL:
image = None
# get_image_ext() returns None if nor a supported Image type
ext = get_image_ext( dataset.path, image )
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext( dataset.path, is_multi_byte=True )
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary( dataset.path )
def add_file( dataset, registry, json_file, output_path ):
data_type = None
line_count = None
converted_path = None
stdout = None
link_data_only = dataset.get( 'link_data_only', 'copy_files' )
in_place = dataset.get( 'in_place', True )
purge_source = dataset.get( 'purge_source', True )
try:
ext = dataset.file_type
except AttributeError:
file_err( 'Unable to process uploaded file, missing file_type parameter.', dataset, json_file )
return
if dataset.type == 'url':
try:
page = urlopen( dataset.path ) # page will be .close()ed by sniff methods
temp_name, dataset.is_multi_byte = sniff.stream_to_file( page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers( page.headers ) )
except Exception as e:
file_err( 'Unable to fetch %s\n%s' % ( dataset.path, str( e ) ), dataset, json_file )
return
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists( dataset.path ):
file_err( 'Uploaded temporary file (%s) does not exist.' % dataset.path, dataset, json_file )
return
if not os.path.getsize( dataset.path ) > 0:
file_err( 'The uploaded file is empty', dataset, json_file )
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = multi_byte.is_multi_byte( codecs.open( dataset.path, 'r', 'utf-8' ).read( 100 ) )
except UnicodeDecodeError as e:
dataset.is_multi_byte = False
# Is dataset an image?
image = check_image( dataset.path )
if image:
if not PIL:
image = None
# get_image_ext() returns None if nor a supported Image type
ext = get_image_ext( dataset.path, image )
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext( dataset.path, registry.sniff_order, is_multi_byte=True )
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary( dataset.path )
if type_info:
data_type = type_info[0]
ext = type_info[1]
if not data_type:
root_datatype = registry.get_datatype_by_extension( dataset.file_type )
if getattr( root_datatype, 'compressed', False ):
data_type = 'compressed archive'
ext = dataset.file_type
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip( dataset.path )
if is_gzipped and not is_valid:
file_err( 'The gzipped uploaded file contains inappropriate content', dataset, json_file )
return
elif is_gzipped and is_valid:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file, but BAM files must remain compressed in the BGZF format
CHUNK_SIZE = 2 ** 20 # 1Mb
fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_gunzip_' % dataset.dataset_id, dir=os.path.dirname( output_path ), text=False )
gzipped_file = gzip.GzipFile( dataset.path, 'rb' )
while 1:
try:
chunk = gzipped_file.read( CHUNK_SIZE )
except IOError:
os.close( fd )
os.remove( uncompressed )
file_err( 'Problem decompressing gzipped data', dataset, json_file )
return
if not chunk:
break
os.write( fd, chunk )
os.close( fd )
gzipped_file.close()
# Replace the gzipped file with the decompressed file if it's safe to do so
if dataset.type in ( 'server_dir', 'path_paste' ) or not in_place:
dataset.path = uncompressed
else:
shutil.move( uncompressed, dataset.path )
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip( '.gz' )
data_type = 'gzip'
if not data_type and bz2 is not None:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2( dataset.path )
if is_bzipped and not is_valid:
file_err( 'The gzipped uploaded file contains inappropriate content', dataset, json_file )
return
elif is_bzipped and is_valid:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file
CHUNK_SIZE = 2 ** 20 # 1Mb
fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_bunzip2_' % dataset.dataset_id, dir=os.path.dirname( output_path ), text=False )
bzipped_file = bz2.BZ2File( dataset.path, 'rb' )
while 1:
try:
chunk = bzipped_file.read( CHUNK_SIZE )
except IOError:
os.close( fd )
os.remove( uncompressed )
file_err( 'Problem decompressing bz2 compressed data', dataset, json_file )
return
if not chunk:
break
os.write( fd, chunk )
os.close( fd )
bzipped_file.close()
# Replace the bzipped file with the decompressed file if it's safe to do so
if dataset.type in ( 'server_dir', 'path_paste' ) or not in_place:
dataset.path = uncompressed
else:
shutil.move( uncompressed, dataset.path )
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip( '.bz2' )
data_type = 'bz2'
if not data_type:
# See if we have a zip archive
is_zipped = check_zip( dataset.path )
if is_zipped:
if link_data_only == 'copy_files':
CHUNK_SIZE = 2 ** 20 # 1Mb
uncompressed = None
uncompressed_name = None
unzipped = False
z = zipfile.ZipFile( dataset.path )
for name in z.namelist():
if name.endswith('/'):
continue
if unzipped:
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
break
fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_zip_' % dataset.dataset_id, dir=os.path.dirname( output_path ), text=False )
if sys.version_info[:2] >= ( 2, 6 ):
zipped_file = z.open( name )
while 1:
try:
chunk = zipped_file.read( CHUNK_SIZE )
except IOError:
os.close( fd )
os.remove( uncompressed )
file_err( 'Problem decompressing zipped data', dataset, json_file )
return
if not chunk:
break
os.write( fd, chunk )
os.close( fd )
zipped_file.close()
uncompressed_name = name
unzipped = True
else:
# python < 2.5 doesn't have a way to read members in chunks(!)
try:
outfile = open( uncompressed, 'wb' )
outfile.write( z.read( name ) )
outfile.close()
uncompressed_name = name
unzipped = True
except IOError:
os.close( fd )
os.remove( uncompressed )
file_err( 'Problem decompressing zipped data', dataset, json_file )
return
z.close()
# Replace the zipped file with the decompressed file if it's safe to do so
if uncompressed is not None:
if dataset.type in ( 'server_dir', 'path_paste' ) or not in_place:
dataset.path = uncompressed
else:
shutil.move( uncompressed, dataset.path )
os.chmod(dataset.path, 0o644)
dataset.name = uncompressed_name
data_type = 'zip'
if not data_type:
# TODO refactor this logic. check_binary isn't guaranteed to be
# correct since it only looks at whether the first 100 chars are
# printable or not. If someone specifies a known unsniffable
# binary datatype and check_binary fails, the file gets mangled.
if check_binary( dataset.path ) or Binary.is_ext_unsniffable(dataset.file_type):
# We have a binary dataset, but it is not Bam, Sff or Pdf
data_type = 'binary'
# binary_ok = False
parts = dataset.name.split( "." )
if len( parts ) > 1:
ext = parts[-1].strip().lower()
if not Binary.is_ext_unsniffable(ext):
file_err( 'The uploaded binary file contains inappropriate content', dataset, json_file )
return
elif Binary.is_ext_unsniffable(ext) and dataset.file_type != ext:
err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % ( ext.capitalize(), ext )
file_err( err_msg, dataset, json_file )
return
if not data_type:
# We must have a text file
if check_html( dataset.path ):
file_err( 'The uploaded file contains inappropriate HTML content', dataset, json_file )
return
if data_type != 'binary':
if link_data_only == 'copy_files':
if dataset.type in ( 'server_dir', 'path_paste' ) and data_type not in [ 'gzip', 'bz2', 'zip' ]:
in_place = False
# Convert universal line endings to Posix line endings, but allow the user to turn it off,
# so that is becomes possible to upload gzip, bz2 or zip files with binary data without
# corrupting the content of those files.
if dataset.to_posix_lines:
tmpdir = output_adjacent_tmpdir( output_path )
tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
if dataset.space_to_tab:
line_count, converted_path = sniff.convert_newlines_sep2tabs( dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix )
else:
line_count, converted_path = sniff.convert_newlines( dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix )
if dataset.file_type == 'auto':
ext = sniff.guess_ext( dataset.path, registry.sniff_order )
else:
ext = dataset.file_type
data_type = ext
# Save job info for the framework
if ext == 'auto' and dataset.ext:
ext = dataset.ext
if ext == 'auto':
ext = 'data'
datatype = registry.get_datatype_by_extension( ext )
if dataset.type in ( 'server_dir', 'path_paste' ) and link_data_only == 'link_to_files':
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming( dataset.path ):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
file_err( err_msg, dataset, json_file )
return
if link_data_only == 'copy_files' and dataset.type in ( 'server_dir', 'path_paste' ) and data_type not in [ 'gzip', 'bz2', 'zip' ]:
# Move the dataset to its "real" path
if converted_path is not None:
shutil.copy( converted_path, output_path )
try:
os.remove( converted_path )
except:
pass
else:
# This should not happen, but it's here just in case
shutil.copy( dataset.path, output_path )
elif link_data_only == 'copy_files':
if purge_source:
shutil.move( dataset.path, output_path )
else:
shutil.copy( dataset.path, output_path )
# Write the job info
stdout = stdout or 'uploaded %s file' % data_type
info = dict( type='dataset',
dataset_id=dataset.dataset_id,
ext=ext,
stdout=stdout,
name=dataset.name,
line_count=line_count )
if dataset.get('uuid', None) is not None:
info['uuid'] = dataset.get('uuid')
json_file.write( dumps( info ) + "\n" )
if link_data_only == 'copy_files' and datatype.dataset_content_needs_grooming( output_path ):
# Groom the dataset content if necessary
datatype.groom_dataset_content( output_path )
if not os.path.exists(dataset.path):
file_err('Uploaded temporary file (%s) does not exist.' % dataset.path,
dataset, json_file)
return
if not os.path.getsize(dataset.path) > 0:
file_err('The uploaded file is empty', dataset, json_file)
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = multi_byte.is_multi_byte(
codecs.open(dataset.path, 'r', 'utf-8').read(100))
except UnicodeDecodeError, e:
dataset.is_multi_byte = False
# Is dataset an image?
image = check_image(dataset.path)
if image:
if not PIL:
image = None
# get_image_ext() returns None if nor a supported Image type
ext = get_image_ext(dataset.path, image)
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext(dataset.path, is_multi_byte=True)
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary(dataset.path)
def add_file(dataset, registry, json_file, output_path):
data_type = None
line_count = None
converted_path = None
stdout = None
link_data_only = dataset.get('link_data_only', 'copy_files')
in_place = dataset.get('in_place', True)
purge_source = dataset.get('purge_source', True)
try:
ext = dataset.file_type
except AttributeError:
file_err(
'Unable to process uploaded file, missing file_type parameter.',
dataset, json_file)
return
if dataset.type == 'url':
try:
page = urlopen(
dataset.path) # page will be .close()ed by sniff methods
temp_name, dataset.is_multi_byte = sniff.stream_to_file(
page,
prefix='url_paste',
source_encoding=util.get_charset_from_http_headers(
page.headers))
except Exception as e:
file_err('Unable to fetch %s\n%s' % (dataset.path, str(e)),
dataset, json_file)
return
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists(dataset.path):
file_err('Uploaded temporary file (%s) does not exist.' % dataset.path,
dataset, json_file)
return
if not os.path.getsize(dataset.path) > 0:
file_err('The uploaded file is empty', dataset, json_file)
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = multi_byte.is_multi_byte(
codecs.open(dataset.path, 'r', 'utf-8').read(100))
except UnicodeDecodeError as e:
dataset.is_multi_byte = False
# Is dataset an image?
image = check_image(dataset.path)
if image:
if not PIL:
image = None
# get_image_ext() returns None if nor a supported Image type
ext = get_image_ext(dataset.path, image)
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext(dataset.path,
registry.sniff_order,
is_multi_byte=True)
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary(dataset.path)
if type_info:
data_type = type_info[0]
ext = type_info[1]
if not data_type:
root_datatype = registry.get_datatype_by_extension(dataset.file_type)
if getattr(root_datatype, 'compressed', False):
data_type = 'compressed archive'
ext = dataset.file_type
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip(dataset.path)
if is_gzipped and not is_valid:
file_err(
'The gzipped uploaded file contains inappropriate content',
dataset, json_file)
return
elif is_gzipped and is_valid:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file, but BAM files must remain compressed in the BGZF format
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp(
prefix='data_id_%s_upload_gunzip_' %
dataset.dataset_id,
dir=os.path.dirname(output_path),
text=False)
gzipped_file = gzip.GzipFile(dataset.path, 'rb')
while 1:
try:
chunk = gzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err('Problem decompressing gzipped data',
dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
gzipped_file.close()
# Replace the gzipped file with the decompressed file if it's safe to do so
if dataset.type in ('server_dir',
'path_paste') or not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.gz')
data_type = 'gzip'
if not data_type and bz2 is not None:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2(dataset.path)
if is_bzipped and not is_valid:
file_err(
'The gzipped uploaded file contains inappropriate content',
dataset, json_file)
return
elif is_bzipped and is_valid:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp(
prefix='data_id_%s_upload_bunzip2_' %
dataset.dataset_id,
dir=os.path.dirname(output_path),
text=False)
bzipped_file = bz2.BZ2File(dataset.path, 'rb')
while 1:
try:
chunk = bzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err(
'Problem decompressing bz2 compressed data',
dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
bzipped_file.close()
# Replace the bzipped file with the decompressed file if it's safe to do so
if dataset.type in ('server_dir',
'path_paste') or not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.bz2')
data_type = 'bz2'
if not data_type:
# See if we have a zip archive
is_zipped = check_zip(dataset.path)
if is_zipped:
if link_data_only == 'copy_files':
CHUNK_SIZE = 2**20 # 1Mb
uncompressed = None
uncompressed_name = None
unzipped = False
z = zipfile.ZipFile(dataset.path)
for name in z.namelist():
if name.endswith('/'):
continue
if unzipped:
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
break
fd, uncompressed = tempfile.mkstemp(
prefix='data_id_%s_upload_zip_' %
dataset.dataset_id,
dir=os.path.dirname(output_path),
text=False)
if sys.version_info[:2] >= (2, 6):
zipped_file = z.open(name)
while 1:
try:
chunk = zipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err(
'Problem decompressing zipped data',
dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
zipped_file.close()
uncompressed_name = name
unzipped = True
else:
# python < 2.5 doesn't have a way to read members in chunks(!)
try:
outfile = open(uncompressed, 'wb')
outfile.write(z.read(name))
outfile.close()
uncompressed_name = name
unzipped = True
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err(
'Problem decompressing zipped data',
dataset, json_file)
return
z.close()
# Replace the zipped file with the decompressed file if it's safe to do so
if uncompressed is not None:
if dataset.type in ('server_dir',
'path_paste') or not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = uncompressed_name
data_type = 'zip'
if not data_type:
# TODO refactor this logic. check_binary isn't guaranteed to be
# correct since it only looks at whether the first 100 chars are
# printable or not. If someone specifies a known unsniffable
# binary datatype and check_binary fails, the file gets mangled.
if check_binary(dataset.path) or Binary.is_ext_unsniffable(
dataset.file_type):
# We have a binary dataset, but it is not Bam, Sff or Pdf
data_type = 'binary'
# binary_ok = False
parts = dataset.name.split(".")
if len(parts) > 1:
ext = parts[-1].strip().lower()
if not Binary.is_ext_unsniffable(ext):
file_err(
'The uploaded binary file contains inappropriate content',
dataset, json_file)
return
elif Binary.is_ext_unsniffable(
ext) and dataset.file_type != ext:
err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % (
ext.capitalize(), ext)
file_err(err_msg, dataset, json_file)
return
if not data_type:
# We must have a text file
if check_html(dataset.path):
file_err(
'The uploaded file contains inappropriate HTML content',
dataset, json_file)
return
if data_type != 'binary':
if link_data_only == 'copy_files':
if dataset.type in ('server_dir',
'path_paste') and data_type not in [
'gzip', 'bz2', 'zip'
]:
in_place = False
# Convert universal line endings to Posix line endings, but allow the user to turn it off,
# so that is becomes possible to upload gzip, bz2 or zip files with binary data without
# corrupting the content of those files.
if dataset.to_posix_lines:
tmpdir = output_adjacent_tmpdir(output_path)
tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
if dataset.space_to_tab:
line_count, converted_path = sniff.convert_newlines_sep2tabs(
dataset.path,
in_place=in_place,
tmp_dir=tmpdir,
tmp_prefix=tmp_prefix)
else:
line_count, converted_path = sniff.convert_newlines(
dataset.path,
in_place=in_place,
tmp_dir=tmpdir,
tmp_prefix=tmp_prefix)
if dataset.file_type == 'auto':
ext = sniff.guess_ext(dataset.path, registry.sniff_order)
else:
ext = dataset.file_type
data_type = ext
# Save job info for the framework
if ext == 'auto' and dataset.ext:
ext = dataset.ext
if ext == 'auto':
ext = 'data'
datatype = registry.get_datatype_by_extension(ext)
if dataset.type in ('server_dir',
'path_paste') and link_data_only == 'link_to_files':
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming(dataset.path):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
file_err(err_msg, dataset, json_file)
return
if link_data_only == 'copy_files' and dataset.type in (
'server_dir',
'path_paste') and data_type not in ['gzip', 'bz2', 'zip']:
# Move the dataset to its "real" path
if converted_path is not None:
shutil.copy(converted_path, output_path)
try:
os.remove(converted_path)
except:
pass
else:
# This should not happen, but it's here just in case
shutil.copy(dataset.path, output_path)
elif link_data_only == 'copy_files':
if purge_source:
shutil.move(dataset.path, output_path)
else:
shutil.copy(dataset.path, output_path)
# Write the job info
stdout = stdout or 'uploaded %s file' % data_type
info = dict(type='dataset',
dataset_id=dataset.dataset_id,
ext=ext,
stdout=stdout,
name=dataset.name,
line_count=line_count)
if dataset.get('uuid', None) is not None:
info['uuid'] = dataset.get('uuid')
json_file.write(dumps(info) + "\n")
if link_data_only == 'copy_files' and datatype.dataset_content_needs_grooming(
output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_path)
