Mercurial > repos > yating-l > data_manager_fetch_reference_data
comparison data_manager/fetch_reference_data.py @ 5:2f926e7d623d draft
planemo upload
author | yating-l |
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date | Wed, 03 May 2017 17:43:57 -0400 |
parents | 464d75111b16 |
children | 2eb398f3649c |
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4:464d75111b16 | 5:2f926e7d623d |
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24 def get_reference_id_name(params): | 24 def get_reference_id_name(params): |
25 genome_id = params['param_dict']['genome_id'] | 25 genome_id = params['param_dict']['genome_id'] |
26 genome_name = params['param_dict']['genome_name'] | 26 genome_name = params['param_dict']['genome_name'] |
27 return genome_id, genome_name | 27 return genome_id, genome_name |
28 | 28 |
29 def download_from_GlimmerHMM(data_manager_dict, params, target_directory, sequence_id, sequence_name ): | 29 def get_url(params): |
30 GlimmerHMM_DOWNLOAD_URL = 'ftp://ccb.jhu.edu/pub/software/glimmerhmm/GlimmerHMM-3.0.4.tar.gz' | 30 trained_url = params['param_dict']['trained_url'] |
31 GlimmerHMM_TRAINED_DIR = os.path.join('GlimmerHMM', 'trained_dir', sequence_id) | 31 return trained_url |
32 with tarfile.open('GlimmerHMM-3.0.4.tar', mode='r:*') as tar: | 32 |
33 def download_from_GlimmerHMM(data_manager_dict, target_directory, sequence_id, sequence_name, trained_dir): | |
34 if not trained_dir: | |
35 trained_dir = 'ftp://ccb.jhu.edu/pub/software/glimmerhmm/GlimmerHMM-3.0.4.tar.gz' | |
36 #Download trained data, ref: https://dzone.com/articles/how-download-file-python | |
37 f = urllib2.urlopen(trained_dir) | |
38 data = f.read() | |
39 downloadpath = 'tmp' | |
40 os.mkdir(downloadpath) | |
41 filepath = os.path.join(downloadpath, 'GlimmerHMM-3.0.4.tar') | |
42 with open(filepath, 'wb') as code: | |
43 code.write(data) | |
44 with tarfile.open(filepath, mode='r:*') as tar: | |
33 subdir = [ | 45 subdir = [ |
34 tarinfo for tarinfo in tar.getmembers() | 46 tarinfo for tarinfo in tar.getmembers() |
35 if sequence_id in tarinfo.name | 47 if sequence_id in tarinfo.name |
36 ] | 48 ] |
37 tar.extractall(members=subdir) | 49 tar.extractall(members=subdir) |
50 GlimmerHMM_TRAINED_DIR = os.path.join(downloadpath, 'GlimmerHMM', 'trained_dir', sequence_id) | |
38 glimmerhmm_trained_target_dir = os.path.join(target_directory, sequence_id) | 51 glimmerhmm_trained_target_dir = os.path.join(target_directory, sequence_id) |
39 shutil.copytree(GlimmerHMM_TRAINED_DIR, glimmerhmm_trained_target_dir) | 52 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) | 53 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) | 54 _add_data_table_entry(data_manager_dict, data_table_entry) |
55 | |
56 cleanup_before_exit('tmp') | |
42 | 57 |
43 cleanup_before_exit(GlimmerHMM_TRAINED_DIR) | 58 def _add_data_table_entry(data_manager_dict, data_table_entry): |
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', {} ) | 59 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', []) | 60 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 ) | 61 data_manager_dict['data_tables']['reference_data'].append( data_table_entry ) |
49 return data_manager_dict | 62 return data_manager_dict |
50 | |
51 REFERENCE_SOURCE_TO_DOWNLOAD = dict(glimmerhmm=download_from_GlimmerHMM) | |
52 | 63 |
53 def main(): | 64 def main(): |
54 #Parse Command Line | 65 #Parse Command Line |
55 parser = argparse.ArgumentParser() | 66 parser = argparse.ArgumentParser() |
56 parser.add_argument('-o', '--out', help='Output file') | 67 parser.add_argument('-o', '--out', help='Output file') |
62 target_directory = params['output_data'][0]['extra_files_path'] | 73 target_directory = params['output_data'][0]['extra_files_path'] |
63 os.mkdir(target_directory) | 74 os.mkdir(target_directory) |
64 data_manager_dict = {} | 75 data_manager_dict = {} |
65 | 76 |
66 sequence_id, sequence_name = get_reference_id_name(params) | 77 sequence_id, sequence_name = get_reference_id_name(params) |
67 | 78 trained_dir = get_url(params) |
68 #Fetch the FASTA | 79 #Fetch the FASTA |
69 REFERENCE_SOURCE_TO_DOWNLOAD[params['param_dict']['trained_dir']](data_manager_dict, params, target_directory, sequence_id, sequence_name) | 80 download_from_GlimmerHMM(data_manager_dict, target_directory, sequence_id, sequence_name, trained_dir) |
70 | |
71 #save info to json file | 81 #save info to json file |
72 open(filename, 'wb').write(to_json_string(data_manager_dict)) | 82 open(filename, 'wb').write(to_json_string(data_manager_dict)) |
73 | 83 |
74 if __name__ == "__main__": | 84 if __name__ == "__main__": |
75 main() | 85 main() |