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)
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 = urllib.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, e:
file_err('Unable to fetch %s\n%s' % (dataset.path, str(e)),
dataset, json_file)
return
dataset.path = temp_name
def stream_url_to_file(path):
page = urlopen(path) # page will be .close()ed in stream_to_file
temp_name = stream_to_file(
page,
prefix='url_paste',
source_encoding=util.get_charset_from_http_headers(page.headers))
return temp_name
def stream_url_to_file(path, file_sources=None):
prefix = "url_paste"
if file_sources and file_sources.looks_like_uri(path):
file_source_path = file_sources.get_file_source_path(path)
_, temp_name = tempfile.mkstemp(prefix=prefix)
os.close(_)
file_source_path.file_source.realize_to(file_source_path.path, temp_name)
return temp_name
else:
page = urllib.request.urlopen(path) # page will be .close()ed in stream_to_file
temp_name = stream_to_file(page, prefix=prefix, source_encoding=util.get_charset_from_http_headers(page.headers))
return temp_name
def stream_url_to_file(path, file_sources=None):
prefix = "url_paste"
if file_sources and file_sources.looks_like_uri(path):
file_source_path = file_sources.get_file_source_path(path)
with tempfile.NamedTemporaryFile(prefix=prefix, delete=False) as temp:
temp_name = temp.name
file_source_path.file_source.realize_to(file_source_path.path, temp_name)
return temp_name
else:
page = urllib.request.urlopen(path, timeout=util.DEFAULT_SOCKET_TIMEOUT) # page will be .close()ed in stream_to_file
temp_name = stream_to_file(page, prefix=prefix, source_encoding=util.get_charset_from_http_headers(page.headers))
return temp_name
def url_upload(dataset):
"""
@summary: Upload an URL file and update dataset information.
@param dataset: [Bunch] The dataset for the uploaded file.
"""
url = dataset.path
page = urllib.urlopen(url)
temp_name, dataset.is_multi_byte = sniff.stream_to_file(
page,
prefix='url_paste',
source_encoding=util.get_charset_from_http_headers(page.headers))
dataset.path = temp_name
dataset.name = url.split('/')[-1]
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)
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 = urllib.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, e:
file_err("Unable to fetch %s\n%s" % (dataset.path, str(e)), dataset, json_file)
return
dataset.path = temp_name
def __main__():
filename = sys.argv[1]
try:
max_file_size = int( sys.argv[2] )
except:
max_file_size = 0
job_params, params = load_input_parameters( filename )
if job_params is None: # using an older tabular file
enhanced_handling = False
job_params = dict( param_dict=params )
job_params[ 'output_data' ] = [ dict( out_data_name='output',
ext='data',
file_name=filename,
extra_files_path=None ) ]
job_params[ 'job_config' ] = dict( GALAXY_ROOT_DIR=GALAXY_ROOT_DIR, GALAXY_DATATYPES_CONF_FILE=GALAXY_DATATYPES_CONF_FILE, TOOL_PROVIDED_JOB_METADATA_FILE=TOOL_PROVIDED_JOB_METADATA_FILE )
else:
enhanced_handling = True
json_file = open( job_params[ 'job_config' ][ 'TOOL_PROVIDED_JOB_METADATA_FILE' ], 'w' ) # specially named file for output junk to pass onto set metadata
datatypes_registry = Registry()
datatypes_registry.load_datatypes( root_dir=job_params[ 'job_config' ][ 'GALAXY_ROOT_DIR' ], config=job_params[ 'job_config' ][ 'GALAXY_DATATYPES_CONF_FILE' ] )
URL = params.get( 'URL', None ) # using exactly URL indicates that only one dataset is being downloaded
URL_method = params.get( 'URL_method', None )
# The Python support for fetching resources from the web is layered. urllib uses the httplib
# library, which in turn uses the socket library. As of Python 2.3 you can specify how long
# a socket should wait for a response before timing out. By default the socket module has no
# timeout and can hang. Currently, the socket timeout is not exposed at the httplib or urllib2
# levels. However, you can set the default timeout ( in seconds ) globally for all sockets by
# doing the following.
socket.setdefaulttimeout( 600 )
for data_dict in job_params[ 'output_data' ]:
cur_filename = data_dict.get( 'file_name', filename )
cur_URL = params.get( '%s|%s|URL' % ( GALAXY_PARAM_PREFIX, data_dict[ 'out_data_name' ] ), URL )
if not cur_URL:
open( cur_filename, 'w' ).write( "" )
stop_err( 'The remote data source application has not sent back a URL parameter in the request.' )
# The following calls to urlopen() will use the above default timeout
try:
if not URL_method or URL_method == 'get':
page = urlopen( cur_URL )
elif URL_method == 'post':
page = urlopen( cur_URL, urlencode( params ) )
except Exception as e:
stop_err( 'The remote data source application may be off line, please try again later. Error: %s' % str( e ) )
if max_file_size:
file_size = int( page.info().get( 'Content-Length', 0 ) )
if file_size > max_file_size:
stop_err( 'The size of the data (%d bytes) you have requested exceeds the maximum allowed (%d bytes) on this server.' % ( file_size, max_file_size ) )
# do sniff stream for multi_byte
try:
cur_filename, is_multi_byte = sniff.stream_to_open_named_file( page, os.open( cur_filename, os.O_WRONLY | os.O_CREAT ), cur_filename, source_encoding=get_charset_from_http_headers( page.headers ) )
except Exception as e:
stop_err( 'Unable to fetch %s:\n%s' % ( cur_URL, e ) )
# here import checks that upload tool performs
if enhanced_handling:
try:
ext = sniff.handle_uploaded_dataset_file( filename, datatypes_registry, ext=data_dict[ 'ext' ], is_multi_byte=is_multi_byte )
except Exception as e:
stop_err( str( e ) )
info = dict( type='dataset',
dataset_id=data_dict[ 'dataset_id' ],
ext=ext)
json_file.write( "%s\n" % dumps( info ) )
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')
run_as_real_user = in_place = dataset.get('in_place', True)
purge_source = dataset.get('purge_source', True)
# in_place is True if there is no external chmod in place,
# however there are other instances where modifications should not occur in_place:
# when a file is added from a directory on the local file system (ftp import folder or any other path).
if dataset.type in ('server_dir', 'path_paste', 'ftp_import'):
in_place = False
check_content = dataset.get('check_content' , True)
auto_decompress = dataset.get('auto_decompress', 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?
i_ext = get_image_ext(dataset.path)
if i_ext:
ext = i_ext
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, check_content=check_content)
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 and auto_decompress:
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 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:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2(dataset.path, check_content)
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 and auto_decompress:
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 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 and auto_decompress:
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 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 check_content and 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_content and 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' and data_type not in ('gzip', 'bz2', 'zip'):
# Convert universal line endings to Posix line endings if to_posix_lines is True
# and the data is not binary or gzip-, bz2- or zip-compressed.
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 data_type == 'binary':
ext = 'data'
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 converted_path:
# Move the dataset to its "real" path
try:
shutil.move(converted_path, output_path)
except OSError as e:
# We may not have permission to remove converted_path
if e.errno != errno.EACCES:
raise
elif link_data_only == 'copy_files':
if purge_source and not run_as_real_user:
# if the upload tool runs as a real user the real user
# can't move dataset.path as this path is owned by galaxy.
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 and datatype.dataset_content_needs_grooming(output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_path)
def stream_url_to_file(path):
page = urlopen(path) # page will be .close()ed in stream_to_file
temp_name = stream_to_file(page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers(page.headers))
return temp_name
def __main__():
filename = sys.argv[1]
try:
max_file_size = int(sys.argv[2])
except Exception:
max_file_size = 0
job_params, params = load_input_parameters(filename)
if job_params is None: # using an older tabular file
enhanced_handling = False
job_params = dict(param_dict=params)
job_params['output_data'] = [dict(out_data_name='output',
ext='data',
file_name=filename,
extra_files_path=None)]
job_params['job_config'] = dict(GALAXY_ROOT_DIR=GALAXY_ROOT_DIR, GALAXY_DATATYPES_CONF_FILE=GALAXY_DATATYPES_CONF_FILE, TOOL_PROVIDED_JOB_METADATA_FILE=TOOL_PROVIDED_JOB_METADATA_FILE)
else:
enhanced_handling = True
json_file = open(job_params['job_config']['TOOL_PROVIDED_JOB_METADATA_FILE'], 'w') # specially named file for output junk to pass onto set metadata
datatypes_registry = Registry()
datatypes_registry.load_datatypes(root_dir=job_params['job_config']['GALAXY_ROOT_DIR'], config=job_params['job_config']['GALAXY_DATATYPES_CONF_FILE'])
URL = params.get('URL', None) # using exactly URL indicates that only one dataset is being downloaded
URL_method = params.get('URL_method', None)
# The Python support for fetching resources from the web is layered. urllib uses the httplib
# library, which in turn uses the socket library. As of Python 2.3 you can specify how long
# a socket should wait for a response before timing out. By default the socket module has no
# timeout and can hang. Currently, the socket timeout is not exposed at the httplib or urllib2
# levels. However, you can set the default timeout ( in seconds ) globally for all sockets by
# doing the following.
socket.setdefaulttimeout(600)
for data_dict in job_params['output_data']:
cur_filename = data_dict.get('file_name', filename)
cur_URL = params.get('%s|%s|URL' % (GALAXY_PARAM_PREFIX, data_dict['out_data_name']), URL)
if not cur_URL or urlparse(cur_URL).scheme not in ('http', 'https', 'ftp'):
open(cur_filename, 'w').write("")
stop_err('The remote data source application has not sent back a URL parameter in the request.')
# The following calls to urlopen() will use the above default timeout
try:
if not URL_method or URL_method == 'get':
page = urlopen(cur_URL)
elif URL_method == 'post':
page = urlopen(cur_URL, urlencode(params).encode("utf-8"))
except Exception as e:
stop_err('The remote data source application may be off line, please try again later. Error: %s' % str(e))
if max_file_size:
file_size = int(page.info().get('Content-Length', 0))
if file_size > max_file_size:
stop_err('The size of the data (%d bytes) you have requested exceeds the maximum allowed (%d bytes) on this server.' % (file_size, max_file_size))
try:
cur_filename = sniff.stream_to_open_named_file(page, os.open(cur_filename, os.O_WRONLY | os.O_CREAT), cur_filename, source_encoding=get_charset_from_http_headers(page.headers))
except Exception as e:
stop_err('Unable to fetch %s:\n%s' % (cur_URL, e))
# here import checks that upload tool performs
if enhanced_handling:
try:
ext = sniff.handle_uploaded_dataset_file(filename, datatypes_registry, ext=data_dict['ext'])
except Exception as e:
stop_err(str(e))
info = dict(type='dataset',
dataset_id=data_dict['dataset_id'],
ext=ext)
json_file.write("%s\n" % dumps(info))
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') != 'copy_files'
# run_as_real_user is estimated from galaxy config (external chmod indicated of inputs executed)
# If this is True we always purge supplied upload inputs so they are cleaned up and we reuse their
# paths during data conversions since this user already owns that path.
# Older in_place check for upload jobs created before 18.01, TODO remove in 19.XX. xref #5206
run_as_real_user = dataset.get('run_as_real_user', False) or dataset.get("in_place", False)
# purge_source defaults to True unless this is an FTP import and
# ftp_upload_purge has been overridden to False in Galaxy's config.
# We set purge_source to False if:
# - the job does not have write access to the file, e.g. when running as the
# real user
# - the files are uploaded from external paths.
purge_source = dataset.get('purge_source', True) and not run_as_real_user and dataset.type not in ('server_dir', 'path_paste')
# in_place is True unless we are running as a real user or importing external paths (i.e.
# this is a real upload and not a path paste or ftp import).
# in_place should always be False if running as real user because the uploaded file will
# be owned by Galaxy and not the user and it should be False for external paths so Galaxy doesn't
# modify files not controlled by Galaxy.
in_place = not run_as_real_user and dataset.type not in ('server_dir', 'path_paste', 'ftp_import')
# Base on the check_upload_content Galaxy config option and on by default, this enables some
# security related checks on the uploaded content, but can prevent uploads from working in some cases.
check_content = dataset.get('check_content' , True)
# auto_decompress is a request flag that can be swapped off to prevent Galaxy from automatically
# decompressing archive files before sniffing.
auto_decompress = dataset.get('auto_decompress', True)
try:
ext = dataset.file_type
except AttributeError:
raise UploadProblemException('Unable to process uploaded file, missing file_type parameter.')
if dataset.type == 'url':
try:
page = urlopen(dataset.path) # page will be .close()ed by sniff methods
temp_name = sniff.stream_to_file(page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers(page.headers))
except Exception as e:
raise UploadProblemException('Unable to fetch %s\n%s' % (dataset.path, str(e)))
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists(dataset.path):
raise UploadProblemException('Uploaded temporary file (%s) does not exist.' % dataset.path)
if not os.path.getsize(dataset.path) > 0:
raise UploadProblemException('The uploaded file is empty')
# Is dataset content supported sniffable binary?
is_binary = check_binary(dataset.path)
if is_binary:
# Sniff the data type
guessed_ext = sniff.guess_ext(dataset.path, registry.sniff_order)
# Set data_type only if guessed_ext is a binary datatype
datatype = registry.get_datatype_by_extension(guessed_ext)
if isinstance(datatype, Binary):
data_type = guessed_ext
ext = guessed_ext
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, check_content=check_content)
if is_gzipped and not is_valid:
raise UploadProblemException('The gzipped uploaded file contains inappropriate content')
elif is_gzipped and is_valid and auto_decompress:
if not link_data_only:
# 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)
raise UploadProblemException('Problem decompressing gzipped data')
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 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:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2(dataset.path, check_content)
if is_bzipped and not is_valid:
raise UploadProblemException('The gzipped uploaded file contains inappropriate content')
elif is_bzipped and is_valid and auto_decompress:
if not link_data_only:
# 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)
raise UploadProblemException('Problem decompressing bz2 compressed data')
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 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 and auto_decompress:
if not link_data_only:
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)
raise UploadProblemException('Problem decompressing zipped data')
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:
with open(uncompressed, 'wb') as outfile:
outfile.write(z.read(name))
uncompressed_name = name
unzipped = True
except IOError:
os.close(fd)
os.remove(uncompressed)
raise UploadProblemException('Problem decompressing zipped data')
z.close()
# Replace the zipped file with the decompressed file if it's safe to do so
if uncompressed is not None:
if 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:
if is_binary or registry.is_extension_unsniffable_binary(dataset.file_type):
# We have a binary dataset, but it is not Bam, Sff or Pdf
data_type = 'binary'
parts = dataset.name.split(".")
if len(parts) > 1:
ext = parts[-1].strip().lower()
is_ext_unsniffable_binary = registry.is_extension_unsniffable_binary(ext)
if check_content and not is_ext_unsniffable_binary:
raise UploadProblemException('The uploaded binary file contains inappropriate content')
elif is_ext_unsniffable_binary and dataset.file_type != ext:
err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % (ext, ext)
raise UploadProblemException(err_msg)
if not data_type:
# We must have a text file
if check_content and check_html(dataset.path):
raise UploadProblemException('The uploaded file contains inappropriate HTML content')
if data_type != 'binary':
if not link_data_only and data_type not in ('gzip', 'bz2', 'zip'):
# Convert universal line endings to Posix line endings if to_posix_lines is True
# and the data is not binary or gzip-, bz2- or zip-compressed.
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(converted_path or dataset.path, registry.sniff_order)
else:
ext = dataset.file_type
data_type = ext
# Save job info for the framework
if ext == 'auto' and data_type == 'binary':
ext = 'data'
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:
# 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.'
raise UploadProblemException(err_msg)
if not link_data_only and converted_path:
# Move the dataset to its "real" path
try:
shutil.move(converted_path, output_path)
except OSError as e:
# We may not have permission to remove converted_path
if e.errno != errno.EACCES:
raise
elif not link_data_only:
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 not link_data_only and datatype and datatype.dataset_content_needs_grooming(output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_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?
i_ext = get_image_ext(dataset.path)
if i_ext:
ext = i_ext
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)
def url_upload(dataset):
"""
@summary: Upload an URL file and update dataset information.
@param dataset: [Bunch] The dataset for the uploaded file.
"""
url = dataset.path
page = urllib.urlopen( url )
temp_name, dataset.is_multi_byte = sniff.stream_to_file( page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers( page.headers ) )
dataset.path = temp_name
dataset.name = url.split('/')[-1]
