Mercurial > repos > xuebing > sharplabtool
diff tools/data_source/data_source.py @ 0:9071e359b9a3
Uploaded
author | xuebing |
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date | Fri, 09 Mar 2012 19:37:19 -0500 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tools/data_source/data_source.py Fri Mar 09 19:37:19 2012 -0500 @@ -0,0 +1,110 @@ +#!/usr/bin/env python +# Retrieves data from external data source applications and stores in a dataset file. +# Data source application parameters are temporarily stored in the dataset file. +import socket, urllib, sys, os +from galaxy import eggs #eggs needs to be imported so that galaxy.util can find docutils egg... +from galaxy.util.json import from_json_string, to_json_string +import galaxy.model # need to import model before sniff to resolve a circular import dependency +from galaxy.datatypes import sniff +from galaxy.datatypes.registry import Registry +from galaxy.jobs import TOOL_PROVIDED_JOB_METADATA_FILE + +assert sys.version_info[:2] >= ( 2, 4 ) + +def stop_err( msg ): + sys.stderr.write( msg ) + sys.exit() + +GALAXY_PARAM_PREFIX = 'GALAXY' +GALAXY_ROOT_DIR = os.path.realpath( os.path.join( os.path.split( os.path.realpath( __file__ ) )[0], '..', '..' ) ) +GALAXY_DATATYPES_CONF_FILE = os.path.join( GALAXY_ROOT_DIR, 'datatypes_conf.xml' ) + +def load_input_parameters( filename, erase_file = True ): + datasource_params = {} + try: + json_params = from_json_string( open( filename, 'r' ).read() ) + datasource_params = json_params.get( 'param_dict' ) + except: + json_params = None + for line in open( filename, 'r' ): + try: + line = line.strip() + fields = line.split( '\t' ) + datasource_params[ fields[0] ] = fields[1] + except: + continue + if erase_file: + open( filename, 'w' ).close() #open file for writing, then close, removes params from file + return json_params, datasource_params + +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( 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 urllib.urlopen() will use the above default timeout + try: + if not URL_method or URL_method == 'get': + page = urllib.urlopen( cur_URL ) + elif URL_method == 'post': + page = urllib.urlopen( cur_URL, urllib.urlencode( params ) ) + except Exception, 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 ) + except Exception, 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, e: + stop_err( str( e ) ) + info = dict( type = 'dataset', + dataset_id = data_dict[ 'dataset_id' ], + ext = ext) + + json_file.write( "%s\n" % to_json_string( info ) ) + +if __name__ == "__main__": __main__()