Mercurial > repos > iuc > data_manager_semibin
view data_manager/data_manager_semibin.py @ 0:676915c44e1e draft default tip
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/data_managers/data_manager_semibin commit aa9bfb2fb62547ee8bac34f0de5b3beaa0bfd1a4"
author | iuc |
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date | Fri, 14 Oct 2022 21:32:55 +0000 |
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#!/usr/bin/env python # # Data manager for reference data for the MetaPhlAn Galaxy tools import argparse import json import subprocess from datetime import date from pathlib import Path # Utility functions for interacting with Galaxy JSON def read_input_json(json_fp): """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. """ with open(json_fp) as fh: params = json.load(fh) return (params['param_dict'], Path(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(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 = { '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) def download_gtdb(data_tables, table_name, target_dp, test=False): """Download GTDB 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 table_name: name of the table target_dp: directory to put copy or link to the data file """ db_dp = target_dp if not test: cmd = "SemiBin download_GTDB --reference-db-data-dir %s" % (db_dp) subprocess.check_call(cmd, shell=True) dbkey = 'gtdb' name = "GTDB reference genome generated by MMseqs2 used in SemiBin" else: dbkey = 'test' name = "Test" empty_fp = db_dp / Path("empty") empty_fp.touch() add_data_table_entry( data_tables, table_name, dict( dbkey=dbkey, value='%s' % (date.today().strftime("%d%m%Y")), name=name, path=str(db_dp))) if __name__ == "__main__": print("Starting...") # Read command line parser = argparse.ArgumentParser(description='Download reference genomes (GTDB)') parser.add_argument('--json', help="Path to JSON file") parser.add_argument('--test', action='store_true', help="Test") args = parser.parse_args() print("args : %s" % args) # Read the input JSON json_fp = Path(args.json) params, target_dp = read_input_json(json_fp) # Make the target directory print("Making %s" % target_dp) target_dp.mkdir(parents=True, exist_ok=True) # Set up data tables dictionary data_tables = create_data_tables_dict() add_data_table(data_tables, "gtdb") # Fetch data from specified data sources print("Download and build database") download_gtdb( data_tables, "gtdb", target_dp, args.test) # Write output JSON print("Outputting JSON") with open(json_fp, 'w') as fh: json.dump(data_tables, fh, sort_keys=True) print("Done.")