Mercurial > repos > iuc > data_manager_mothur_toolsuite
view data_manager/fetch_mothur_reference_data.py @ 0:ab7a7e798c34 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/data_managers/data_manager_mothur_toolsuite/ commit c1b936b54b7133106b3181df1e104986613a5bea
author | iuc |
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date | Mon, 06 Nov 2017 06:21:50 -0500 |
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children | aec831b54a5b |
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#!/usr/bin/env python # # Data manager for reference data for the 'mothur_toolsuite' Galaxy tools import json import optparse import os import shutil import sys import tarfile import tempfile import urllib2 import zipfile # When extracting files from archives, skip names that # start with the following strings IGNORE_PATHS = ('.', '__MACOSX/', '__') # Map file extensions to data table names MOTHUR_FILE_TYPES = {".map": "map", ".fasta": "aligndb", ".align": "aligndb", ".pat": "lookup", ".tax": "taxonomy"} # Reference data URLs MOTHUR_REFERENCE_DATA = { # Look up data # http://www.mothur.org/wiki/Lookup_files "lookup_titanium": { "GS FLX Titanium": ["http://www.mothur.org/w/images/9/96/LookUp_Titanium.zip", ] }, "lookup_gsflx": { "GSFLX": ["http://www.mothur.org/w/images/8/84/LookUp_GSFLX.zip", ] }, "lookup_gs20": { "GS20": ["http://www.mothur.org/w/images/7/7b/LookUp_GS20.zip", ] }, # RDP reference files # http://www.mothur.org/wiki/RDP_reference_files "RDP_v16": { "16S rRNA RDP training set 16": ["https://mothur.org/w/images/d/dc/Trainset16_022016.rdp.tgz", ], "16S rRNA PDS training set 16": ["https://mothur.org/w/images/c/c3/Trainset16_022016.pds.tgz", ], }, "RDP_v14": { "16S rRNA RDP training set 14": ["https://mothur.org/w/images/6/6c/Trainset14_032015.rdp.tgz", ], "16S rRNA PDS training set 14": ["https://mothur.org/w/images/8/88/Trainset14_032015.pds.tgz", ], }, "RDP_v10": { "16S rRNA RDP training set 10": ["http://www.mothur.org/w/images/b/b5/Trainset10_082014.rdp.tgz", ], "16S rRNA PDS training set 10": ["http://www.mothur.org/w/images/2/24/Trainset10_082014.pds.tgz", ], }, "RDP_v9": { "16S rRNA RDP training set 9": ["http://www.mothur.org/w/images/7/72/Trainset9_032012.rdp.zip", ], "16S rRNA PDS training set 9": ["http://www.mothur.org/w/images/5/59/Trainset9_032012.pds.zip", ], }, "RDP_v7": { "16S rRNA RDP training set 7": ["http://www.mothur.org/w/images/2/29/Trainset7_112011.rdp.zip", ], "16S rRNA PDS training set 7": ["http://www.mothur.org/w/images/4/4a/Trainset7_112011.pds.zip", ], "8S rRNA Fungi training set 7": ["http://www.mothur.org/w/images/3/36/FungiLSU_train_v7.zip", ], }, "RDP_v6": { "RDP training set 6": ["http://www.mothur.org/w/images/4/49/RDPTrainingSet.zip", ], }, # Silva reference files # http://www.mothur.org/wiki/Silva_reference_files "silva_release_128": { "SILVA release 128": ["https://mothur.org/w/images/b/b4/Silva.nr_v128.tgz", "https://mothur.org/w/images/a/a4/Silva.seed_v128.tgz", ], }, "silva_release_123": { "SILVA release 123": ["https://mothur.org/w/images/b/be/Silva.nr_v123.tgz", "https://mothur.org/w/images/1/15/Silva.seed_v123.tgz", ], }, "silva_release_119": { "SILVA release 119": ["http://www.mothur.org/w/images/2/27/Silva.nr_v119.tgz", "http://www.mothur.org/w/images/5/56/Silva.seed_v119.tgz", ], }, "silva_release_102": { "SILVA release 102": ["http://www.mothur.org/w/images/9/98/Silva.bacteria.zip", "http://www.mothur.org/w/images/3/3c/Silva.archaea.zip", "http://www.mothur.org/w/images/1/1a/Silva.eukarya.zip", ], }, "silva_gold_bacteria": { "SILVA gold": ["http://www.mothur.org/w/images/f/f1/Silva.gold.bacteria.zip", ], }, # Greengenes # http://www.mothur.org/wiki/Greengenes-formatted_databases "greengenes_August2013": { "Greengenes August 2013": ["http://www.mothur.org/w/images/1/19/Gg_13_8_99.refalign.tgz", "http://www.mothur.org/w/images/6/68/Gg_13_8_99.taxonomy.tgz", ], }, "greengenes_May2013": { "Greengenes May 2013": ["http://www.mothur.org/w/images/c/cd/Gg_13_5_99.refalign.tgz", "http://www.mothur.org/w/images/9/9d/Gg_13_5_99.taxonomy.tgz", ], }, "greengenes_old": { "Greengenes pre-May 2013": ["http://www.mothur.org/w/images/7/72/Greengenes.alignment.zip", "http://www.mothur.org/w/images/1/16/Greengenes.tax.tgz", ], }, "greengenes_gold_alignment": { "Greengenes gold alignment": ["http://www.mothur.org/w/images/2/21/Greengenes.gold.alignment.zip", ], }, # Secondary structure maps # http://www.mothur.org/wiki/Secondary_structure_map "secondary_structure_maps_silva": { "SILVA": ["http://www.mothur.org/w/images/6/6d/Silva_ss_map.zip", ], }, "secondary_structure_maps_greengenes": { "Greengenes": ["http://www.mothur.org/w/images/4/4b/Gg_ss_map.zip", ], }, # Lane masks: not used here? "lane_masks": { "Greengenes-compatible": ["http://www.mothur.org/w/images/2/2a/Lane1241.gg.filter", "http://www.mothur.org/w/images/a/a0/Lane1287.gg.filter", "http://www.mothur.org/w/images/3/3d/Lane1349.gg.filter", ], "SILVA-compatible": ["http://www.mothur.org/w/images/6/6d/Lane1349.silva.filter", ] }, } # Utility functions for interacting with Galaxy JSON def read_input_json(jsonfile): """Read the JSON supplied from the data manager tool Returns a tuple (param_dict,extra_files_path) 'param_dict' is an arbitrary dictionary of parameters input into the tool; 'extra_files_path' is the path to a directory where output files must be put for the receiving data manager to pick them up. NB the directory pointed to by 'extra_files_path' doesn't exist initially, it is the job of the script to create it if necessary. """ params = json.loads(open(jsonfile).read()) return (params['param_dict'], params['output_data'][0]['extra_files_path']) # Utility functions for creating data table dictionaries # # Example usage: # >>> d = create_data_tables_dict() # >>> add_data_table(d,'my_data') # >>> add_data_table_entry(dict(dbkey='hg19',value='human')) # >>> add_data_table_entry(dict(dbkey='mm9',value='mouse')) # >>> print str(json.dumps(d)) def create_data_tables_dict(): """Return a dictionary for storing data table information Returns a dictionary that can be used with 'add_data_table' and 'add_data_table_entry' to store information about a data table. It can be converted to JSON to be sent back to the data manager. """ d = {} d['data_tables'] = {} return d def add_data_table(d, table): """Add a data table to the data tables dictionary Creates a placeholder for a data table called 'table'. """ d['data_tables'][table] = [] def add_data_table_entry(d, table, entry): """Add an entry to a data table Appends an entry to the data table 'table'. 'entry' should be a dictionary where the keys are the names of columns in the data table. Raises an exception if the named data table doesn't exist. """ try: d['data_tables'][table].append(entry) except KeyError: raise Exception("add_data_table_entry: no table '%s'" % table) # Utility functions for downloading and unpacking archive files def download_file(url, target=None, wd=None): """Download a file from a URL Fetches a file from the specified URL. If 'target' is specified then the file is saved to this name; otherwise it's saved as the basename of the URL. If 'wd' is specified then it is used as the 'working directory' where the file will be save on the local system. Returns the name that the file is saved with. """ print "Downloading %s" % url if not target: target = os.path.basename(url) if wd: target = os.path.join(wd, target) print "Saving to %s" % target open(target, 'wb').write(urllib2.urlopen(url).read()) return target def unpack_zip_archive(filen, wd=None): """Extract files from a ZIP archive Given a ZIP archive, extract the files it contains and return a list of the resulting file names and paths. 'wd' specifies the working directory to extract the files to, otherwise they are extracted to the current working directory. Once all the files are extracted the ZIP archive file is deleted from the file system. """ if not zipfile.is_zipfile(filen): print "%s: not ZIP formatted file" return [filen] file_list = [] z = zipfile.ZipFile(filen) for name in z.namelist(): if reduce(lambda x, y: x or name.startswith(y), IGNORE_PATHS, False): print "Ignoring %s" % name continue if wd: target = os.path.join(wd, name) else: target = name if name.endswith('/'): # Make directory print "Creating dir %s" % target try: os.makedirs(target) except OSError: pass else: # Extract file print "Extracting %s" % name try: os.makedirs(os.path.dirname(target)) except OSError: pass open(target, 'wb').write(z.read(name)) file_list.append(target) print "Removing %s" % filen os.remove(filen) return file_list def unpack_tar_archive(filen, wd=None): """Extract files from a TAR archive Given a TAR archive (which optionally can be compressed with either gzip or bz2), extract the files it contains and return a list of the resulting file names and paths. 'wd' specifies the working directory to extract the files to, otherwise they are extracted to the current working directory. Once all the files are extracted the TAR archive file is deleted from the file system. """ file_list = [] if not tarfile.is_tarfile(filen): print "%s: not TAR file" return [filen] t = tarfile.open(filen) for name in t.getnames(): # Check for unwanted files if reduce(lambda x, y: x or name.startswith(y), IGNORE_PATHS, False): print "Ignoring %s" % name continue # Extract file print "Extracting %s" % name t.extract(name, wd) if wd: target = os.path.join(wd, name) else: target = name file_list.append(target) print "Removing %s" % filen os.remove(filen) return file_list def unpack_archive(filen, wd=None): """Extract files from an archive Wrapper function that calls the appropriate unpacking function depending on the archive type, and returns a list of files that have been extracted. 'wd' specifies the working directory to extract the files to, otherwise they are extracted to the current working directory. """ print "Unpack %s" % filen ext = os.path.splitext(filen)[1] print "Extension: %s" % ext if ext == ".zip": return unpack_zip_archive(filen, wd=wd) elif ext == ".tgz": return unpack_tar_archive(filen, wd=wd) else: return [filen] def fetch_files(urls, wd=None, files=None): """Download and unpack files from a list of URLs Given a list of URLs, download and unpack each one, and return a list of the extracted files. 'wd' specifies the working directory to extract the files to, otherwise they are extracted to the current working directory. If 'files' is given then the list of extracted files will be appended to this list before being returned. """ if files is None: files = [] for url in urls: filen = download_file(url, wd=wd) files.extend(unpack_archive(filen, wd=wd)) return files # Utility functions specific to the Mothur reference data def identify_type(filen): """Return the data table name based on the file name """ ext = os.path.splitext(filen)[1] try: return MOTHUR_FILE_TYPES[ext] except KeyError: print "WARNING: unknown file type for " + filen + ", skipping" return None def get_name(filen): """Generate a descriptive name based on the file name """ # type_ = identify_type(filen) name = os.path.splitext(os.path.basename(filen))[0] for delim in ('.', '_'): name = name.replace(delim, ' ') return name def fetch_from_mothur_website(data_tables, target_dir, datasets): """Fetch reference data from the Mothur website For each dataset in the list 'datasets', download (and if necessary unpack) the related files from the Mothur website, copy them to the data manager's target directory, and add references to the files to the appropriate data table. The 'data_tables' dictionary should have been created using the 'create_data_tables_dict' and 'add_data_table' functions. Arguments: data_tables: a dictionary containing the data table info target_dir: directory to put the downloaded files datasets: a list of dataset names corresponding to keys in the MOTHUR_REFERENCE_DATA dictionary """ # Make working dir wd = tempfile.mkdtemp(suffix=".mothur", dir=os.getcwd()) print "Working dir %s" % wd # Iterate over all requested reference data URLs for dataset in datasets: print "Handling dataset '%s'" % dataset for name in MOTHUR_REFERENCE_DATA[dataset]: for f in fetch_files(MOTHUR_REFERENCE_DATA[dataset][name], wd=wd): type_ = identify_type(f) entry_name = "%s (%s)" % (os.path.splitext(os.path.basename(f))[0], name) print "%s\t\'%s'\t.../%s" % (type_, entry_name, os.path.basename(f)) if type_ is not None: # Move to target dir ref_data_file = os.path.basename(f) f1 = os.path.join(target_dir, ref_data_file) print "Moving %s to %s" % (f, f1) os.rename(f, f1) # Add entry to data table table_name = "mothur_%s" % type_ add_data_table_entry(data_tables, table_name, dict(name=entry_name, value=ref_data_file)) # Remove working dir print "Removing %s" % wd shutil.rmtree(wd) def files_from_filesystem_paths(paths): """Return list of file paths from arbitrary input paths Given a list of filesystem paths, return a list of full paths corresponding to all files found recursively from under those paths. """ # Collect files to add files = [] for path in paths: path = os.path.abspath(path) print "Examining '%s'..." % path if os.path.isfile(path): # Store full path for file files.append(path) elif os.path.isdir(path): # Descend into directory and collect the files for f in os.listdir(path): files.extend(files_from_filesystem_paths((os.path.join(path, f), ))) else: print "Not a file or directory, ignored" return files def import_from_server(data_tables, target_dir, paths, description, link_to_data=False): """Import reference data from filesystem paths Creates references to the specified file(s) on the Galaxy server in the appropriate data table (determined from the file extension). The 'data_tables' dictionary should have been created using the 'create_data_tables_dict' and 'add_data_table' functions. Arguments: data_tables: a dictionary containing the data table info target_dir: directory to put copy or link to the data file paths: list of file and/or directory paths to import description: text to associate with the files link_to_data: boolean, if False then copy the data file into Galaxy (default); if True then make a symlink to the data file """ # Collect list of files based on input paths files = files_from_filesystem_paths(paths) # Handle each file individually for f in files: type_ = identify_type(f) if type_ is None: print "%s: unrecognised type, skipped" % f continue ref_data_file = os.path.basename(f) target_file = os.path.join(target_dir, ref_data_file) entry_name = "%s" % os.path.splitext(ref_data_file)[0] if description: entry_name += " (%s)" % description print "%s\t\'%s'\t.../%s" % (type_, entry_name, ref_data_file) # Link to or copy the data if link_to_data: os.symlink(f, target_file) else: shutil.copyfile(f, target_file) # Add entry to data table table_name = "mothur_%s" % type_ add_data_table_entry(data_tables, table_name, dict(name=entry_name, value=ref_data_file)) if __name__ == "__main__": print "Starting..." # Read command line parser = optparse.OptionParser() parser.add_option('--source', action='store', dest='data_source') parser.add_option('--datasets', action='store', dest='datasets', default='') parser.add_option('--paths', action='store', dest='paths', default=[]) parser.add_option('--description', action='store', dest='description', default='') parser.add_option('--link', action='store_true', dest='link_to_data') options, args = parser.parse_args() print "options: %s" % options print "args : %s" % args # Check for JSON file if len(args) != 1: sys.stderr.write("Need to supply JSON file name") sys.exit(1) jsonfile = args[0] # Read the input JSON params, target_dir = read_input_json(jsonfile) # Make the target directory print "Making %s" % target_dir os.mkdir(target_dir) # Set up data tables dictionary data_tables = create_data_tables_dict() add_data_table(data_tables, 'mothur_lookup') add_data_table(data_tables, 'mothur_aligndb') add_data_table(data_tables, 'mothur_map') add_data_table(data_tables, 'mothur_taxonomy') # Fetch data from specified data sources if options.data_source == 'mothur_website': datasets = options.datasets.split(',') fetch_from_mothur_website(data_tables, target_dir, datasets) elif options.data_source == 'filesystem_paths': # Check description text description = options.description.strip() # Get list of paths (need to remove any escapes for '\n' and '\r' # that might have been inserted by Galaxy) paths = options.paths.replace('__cn__', '\n').replace('__cr__', '\r').split() import_from_server(data_tables, target_dir, paths, description, link_to_data=options.link_to_data) # Write output JSON print "Outputting JSON" print str(json.dumps(data_tables)) open(jsonfile, 'wb').write(json.dumps(data_tables)) print "Done."