Mercurial > repos > yating-l > data_manager_fetch_reference_data
comparison data_manager/fetch_reference_data.py @ 1:5349705442d0 draft
planemo upload
author | yating-l |
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date | Wed, 03 May 2017 16:27:19 -0400 |
parents | |
children | 2804b5f00dc7 |
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0:099d2508bcc3 | 1:5349705442d0 |
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1 #!/usr/bin/env python | |
2 # ref: https://galaxyproject.org/admin/tools/data-managers/how-to/define/ | |
3 | |
4 import sys | |
5 import os | |
6 import tempfile | |
7 import shutil | |
8 import argparse | |
9 import urllib2 | |
10 import tarfile | |
11 | |
12 from galaxy.util.json import from_json_string, to_json_string | |
13 | |
14 CHUNK_SIZE = 2**20 #1mb | |
15 | |
16 def cleanup_before_exit(tmp_dir): | |
17 if tmp_dir and os.path.exists(tmp_dir): | |
18 shutil.rmtree(tmp_dir) | |
19 | |
20 def stop_err(msg): | |
21 sys.stderr.write(msg) | |
22 sys.exit(1) | |
23 | |
24 def get_reference_id_name(params): | |
25 genome_id = params['param_dict']['genome_id'] | |
26 genome_name = params['param_dict']['genome_name'] | |
27 return genome_id, genome_name | |
28 | |
29 def download_from_GlimmerHMM(data_manager_dict, params, target_directory, sequence_id, sequence_name ): | |
30 GlimmerHMM_DOWNLOAD_URL = 'ftp://ccb.jhu.edu/pub/software/glimmerhmm/GlimmerHMM-3.0.4.tar.gz' | |
31 GlimmerHMM_TRAINED_DIR = os.path.join('GlimmerHMM', 'trained_dir', sequence_id) | |
32 with tarfile.open('GlimmerHMM-3.0.4.tar', mode='r:*') as tar: | |
33 subdir = [ | |
34 tarinfo for tarinfo in tar.getmembers() | |
35 if sequence_id in tarinfo.name | |
36 ] | |
37 tar.extractall(members=subdir) | |
38 glimmerhmm_trained_target_dir = os.path.join(target_directory, sequence_id) | |
39 shutil.copytree(GlimmerHMM_TRAINED_DIR, glimmerhmm_trained_target_dir) | |
40 data_table_entry = dict(value=sequence_id, name=sequence_name, path=glimmerhmm_trained_target_dir) | |
41 _add_data_table_entry(data_manager_dict, data_table_entry) | |
42 | |
43 cleanup_before_exit(GlimmerHMM_TRAINED_DIR) | |
44 | |
45 def _add_data_table_entry( data_manager_dict, data_table_entry ): | |
46 data_manager_dict['data_tables'] = data_manager_dict.get( 'data_tables', {} ) | |
47 data_manager_dict['data_tables']['reference_data'] = data_manager_dict['data_tables'].get('reference_data', []) | |
48 data_manager_dict['data_tables']['reference_data'].append( data_table_entry ) | |
49 return data_manager_dict | |
50 | |
51 REFERENCE_SOURCE_TO_DOWNLOAD = dict(glimmerhmm=download_from_GlimmerHMM) | |
52 | |
53 def main(): | |
54 #Parse Command Line | |
55 parser = argparse.ArgumentParser() | |
56 args = parser.parse_args() | |
57 | |
58 filename = args[0] | |
59 | |
60 params = from_json_string(open(filename).read()) | |
61 target_directory = params['output_data'][0]['extra_files_path'] | |
62 os.mkdir(target_directory) | |
63 data_manager_dict = {} | |
64 | |
65 sequence_id, sequence_name = get_reference_id_name(params) | |
66 | |
67 #Fetch the FASTA | |
68 REFERENCE_SOURCE_TO_DOWNLOAD[params['param_dict']['file_path']](data_manager_dict, params, target_directory, sequence_id, sequence_name) | |
69 | |
70 #save info to json file | |
71 open(filename, 'wb').write(to_json_string(data_manager_dict)) | |
72 | |
73 if __name__ == "__main__": | |
74 main() | |
75 |