def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'test'
conf = config.TestConfig()
cls.username = conf.USERNAME
cls.password = conf.PASSWORD
cls.MongoDB = conf.SERVER
cls.src = query_taxon_tree.QueryTaxonTree(
cache_dirname=cls.cache_dirname, MongoDB=cls.MongoDB, db=cls.db, collection_str='test_taxon_tree',
verbose=True, max_entries=20, username = cls.username, password = cls.password,
readPreference='primary')
dic_0 = {'tax_id': 0, 'tax_name': 's0', 'anc_id': [5,4,3,2,1], 'anc_name': ['s5', 's4', 's3', 's2', 's1']}
dic_1 = {'tax_id': 1, 'tax_name': 's1', 'anc_id': [5,4,3,2], 'anc_name': ['s5', 's4', 's3', 's2']}
dic_2 = {'tax_id': 2, 'tax_name': 's2', 'anc_id': [5,4,3], 'anc_name': ['s5', 's4', 's3']}
dic_3 = {'tax_id': 3, 'tax_name': 's3', 'anc_id': [5,4], 'anc_name': ['s5', 's4']}
dic_4 = {'tax_id': 4, 'tax_name': 's4', 'anc_id': [5], 'anc_name': ['s5']}
dic_5 = {'tax_id': 5, 'tax_name': 's5', 'anc_id': [], 'anc_name': []}
dic_6 = {'tax_id': 6, 'tax_name': 's6', 'anc_id': [5,4,3,2], 'anc_name': ['s5', 's4', 's3', 's2']}
dic_7 = {'tax_id': 7, 'tax_name': 's7', 'anc_id': [5,4,3,2,6], 'anc_name': ['s5', 's4', 's3', 's2', 's6']}
dic_8 = {'tax_id': 8, 'tax_name': 's8', 'anc_id': [5,4,3,2,6,7], 'anc_name': ['s5', 's4', 's3', 's2', 's6', 's7']}
dic_9 = {'tax_id': 9, 'tax_name': 's9', 'anc_id': [5,4,3], 'anc_name': ['s5', 's4', 's3']}
dic_10 = {'tax_id': 10, 'tax_name': 's10', 'anc_id': [5,4,3,9], 'anc_name': ['s5', 's4', 's3', 's9']}
dic_11 = {'tax_id': 11, 'tax_name': 's11', 'anc_id': [5,4,3,2,1,0], 'anc_name': ['s5', 's4', 's3', 's2', 's1', 's0']}
dic_12 = {'tax_id': 12, 'tax_name': 's12', 'anc_id': [5,4,3,2,1,0], 'anc_name': ['s5', 's4', 's3', 's2', 's1', 's0']}
dic_13 = {'tax_id': 13, 'tax_name': 's13', 'anc_id': [5,4,3,2,1], 'anc_name': ['s5', 's4', 's3', 's2', 's1']}
cls.src.collection.insert_many([dic_0,dic_1,dic_2,dic_3,dic_4,
dic_5,dic_6,dic_7,dic_8,dic_9,dic_10,dic_11,dic_12,dic_13])
def setUpClass(cls):
conf = config.TestConfig()
cls.src = query_demo.QueryDemo(MongoDB=conf.SERVER,
db='datanator-test',
collection_str="taxon_tree",
username=conf.USERNAME,
password=conf.PASSWORD)
def setUpClass(cls):
db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = tabu.Tabu(MongoDB=MongoDB, username=username, password=password,
db=db, max_entries=20, verbose=True, authSource='admin',
readPreference='nearest')
def setUpClass(cls):
conf = config.TestConfig()
cls.collection_str = 'brenda_reaction'
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = reaction.BrendaRxn(MongoDB=MongoDB, db='test', collection_str=cls.collection_str,
username=username, password=password, authSource='admin',
max_entries=20, verbose=True)
def setUpClass(cls):
des_db = 'test'
collection_str = 'metabolite_concentrations'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = doi_10_1038_nchembio_2077.Concentration(MongoDB=MongoDB, db=des_db, collection_str=collection_str,
username=username, password=password, authSource='admin', readPreference='nearest',
verbose=True, max_entries=float('inf'))
def setUpClass(cls):
db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.col_str = 'rna_halflife_new'
cls.src = query_rna_halflife.QueryRNA(server=MongoDB, username=username, password=password,
verbose=True, db=db, collection_str=cls.col_str,
readPreference='nearest')
def setUpClass(cls):
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = query_metabolite_concentrations.QueryMetaboliteConcentrations(
MongoDB=MongoDB,
password=password,
username=username,
db='datanator',
collection_str='metabolite_concentrations')
def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'datanator'
conf = config.TestConfig()
cls.username = conf.USERNAME
cls.password = conf.PASSWORD
cls.MongoDB = conf.SERVER
cls.src = query_taxon_tree.QueryTaxonTree(
cache_dirname=cls.cache_dirname, MongoDB=cls.MongoDB, db=cls.db,
verbose=True, max_entries=20, username = cls.username, password = cls.password,
readPreference='nearest')
def init_query_pax():
db = 'datanator'
conf = config_query.TestConfig()
username = conf.MONGO_TEST_USERNAME
password = conf.MONGO_TEST_PASSWORD
MongoDB = conf.SERVER
pax_manager = query_pax.QueryPax(MongoDB=MongoDB,
db=db,
verbose=True,
username=username,
password=password)
return pax_manager
def setUpClass(cls):
db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = query_kegg_organism_code.QueryKOC(
username=username,
password=password,
server=MongoDB,
database=db,
collection_str='kegg_organism_code')
def setUpClass(cls):
des_db = 'test'
src_db = 'datanator'
cls.protein_col = 'uniprot'
cls.rna_col = 'rna_halflife'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = doi_10_1038_srep01318.Halflife(server=MongoDB, src_db=src_db,
protein_col=cls.protein_col, authDB='admin', readPreference='nearest',
username=username, password=password, verbose=True, max_entries=20,
des_db=des_db, rna_col=cls.rna_col)
def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = query_metabolites.QueryMetabolites(
cache_dirname=cls.cache_dirname,
MongoDB=MongoDB,
db=cls.db,
verbose=True,
max_entries=20,
username=username,
password=password)
def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_kegg_orthology.QueryKO(server=cls.MongoDB,
database=cls.db,
verbose=True,
max_entries=20,
username=cls.username,
password=cls.password)
cls.file_manager = file_util.FileUtil()
def setUpClass(cls):
db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = query_uniprot.QueryUniprot(username=username,
password=password,
server=MongoDB,
database=db,
collection_str='uniprot')
cls.src_test = query_uniprot.QueryUniprot(username=username,
password=password,
server=MongoDB,
database='test',
collection_str='uniprot')
record_0 = {'uniprot_id': 'Q9VB24'}
cls.src_test.collection.insert_many([record_0])
def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_sabio_reaction_entries.QuerySabioRxn(
cache_dirname=cls.cache_dirname,
MongoDB=cls.MongoDB,
db=cls.db,
verbose=True,
max_entries=20,
username=cls.username,
password=cls.password)
def setUpClass(cls):
cls.db = 'test'
conf = query_config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_xmdb.QueryXmdb(server=cls.MongoDB,
database=cls.db,
verbose=True,
max_entries=20,
username=cls.username,
password=cls.password,
collection_str='test_query_ecmdb')
doc_0 = {
'm2m_id': 'm2m_0',
'concentrations': ['some values 0'],
'inchikey': 'key0',
'name': 'name0'
}
doc_1 = {
'm2m_id': 'm2m_1',
'not_concentrations': ['some values'],
'inchikey': 'key1',
'name': 'name1'
}
doc_2 = {
'm2m_id': 'm2m_2',
'concentrations': ['some values 1'],
'inchikey': 'key2',
'name': 'name2'
}
doc_3 = {
'm2m_id': 'm2m_2',
'field_0': ['some values 1'],
'field_2': 'add',
'inchikey': 'key3',
'name': 'name3'
}
cls.src.collection.insert_many([doc_0, doc_1, doc_2, doc_3])
def setUpClass(cls):
cls.db = 'test'
conf = query_config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_corum.QueryCorum(server=cls.MongoDB, database=cls.db,
verbose=True, max_entries=20, username = cls.username,
password = cls.password, collection_str='test_query_corum',
readPreference='primary')
doc_0 = {'subunits_uniprot_id': ['P0', 'P1'], 'SWISSPROT_organism_NCBI_ID': 9606}
doc_1 = {'subunits_uniprot_id': ['P1', 'P2'], 'SWISSPROT_organism_NCBI_ID': 9606}
doc_2 = {'subunits_uniprot_id': ['P1', 'P2', 'P3'], 'SWISSPROT_organism_NCBI_ID': 9606}
doc_3 = {'subunits_uniprot_id': ['P1', 'P2'], 'SWISSPROT_organism_NCBI_ID': 9607}
doc_4 = {'subunits_uniprot_id': ['P1', 'P3'], 'SWISSPROT_organism_NCBI_ID': 9607}
cls.src.collection.insert_many([doc_0,doc_1,doc_2,doc_3,doc_4])
def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_sabiork_old.QuerySabioOld(
cache_dirname=cls.cache_dirname,
MongoDB=cls.MongoDB,
db=cls.db,
verbose=True,
max_entries=20,
username=cls.username,
password=cls.password,
readPreference='primary')
def setUpClass(cls):
des_db = 'test'
src_db = 'datanator'
cls.src_collection = 'rna_halflife_new'
cls.des_collection = 'rna_halflife_test'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = order_by_ko.Reorg(MongoDB=MongoDB,
src_db=src_db,
verbose=False,
max_entries=20,
username=username,
password=password,
authSource='admin',
readPreference='nearest',
des_collection=cls.des_collection,
src_collection=cls.src_collection,
des_db=des_db)
def setUpClass(cls):
src_db = 'datanator'
des_db = 'test'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
username = username
password = password
cls.cache_dir = tempfile.mkdtemp()
cls.protein_col = 'uniprot'
cls.rna_col = 'rna_halflife'
cls.src = rna_halflife_util.RnaHLUtil(server=MongoDB,
username=username,
password=password,
src_db=src_db,
des_db=des_db,
protein_col=cls.protein_col,
rna_col=cls.rna_col,
readPreference='nearest',
cache_dir=cls.cache_dir)
def setUpClass(cls):
cls.cache_dirname = tempfile.mkdtemp()
cls.db = 'datanator'
cls.duplicate = 'duplicate_test'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = mongo_util.MongoUtil(cache_dirname=cls.cache_dirname,
MongoDB=MongoDB,
db=cls.db,
verbose=True,
max_entries=20,
username=username,
password=password)
cls.collection_str = 'ecmdb'
cls.src_test = mongo_util.MongoUtil(cache_dirname=cls.cache_dirname,
MongoDB=MongoDB,
db='test',
verbose=True,
max_entries=20,
username=username,
password=password)
docs = [{
"name": "mike",
"num": 0
}, {
"name": "jon",
"num": 1
}, {
"name": "john",
"num": 2
}, {
"name": "mike",
"num": 3
}]
cls.src_test.db_obj[cls.duplicate].insert_many(docs)
cls.schema_test = "schema_test"
time.sleep(1)
def setUpClass(cls):
des_db = 'test'
src_db = 'datanator'
cls.protein_col = 'uniprot'
cls.rna_col = 'rna_halflife'
cls.cache_dir = tempfile.mkdtemp()
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.src = doi_10_1371_journal_pone_0059059.Halflife(
server=MongoDB,
src_db=src_db,
protein_col=cls.protein_col,
authDB='admin',
readPreference='nearest',
username=username,
password=password,
verbose=True,
max_entries=20,
des_db=des_db,
rna_col=cls.rna_col,
cache_dir=cls.cache_dir)
def setUpClass(cls):
cls.db = 'test'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_sabio_compound.QuerySabioCompound(
server=cls.MongoDB,
database=cls.db,
verbose=True,
max_entries=20,
username=cls.username,
password=cls.password,
collection_str='test_query_sabio_compound',
readPreference='nearest')
compound_0 = {
'_id': 0,
'name': 'a',
'synonyms': ['a0', 'a1', 'a2'],
'inchi_key': 'asdf0'
}
compound_1 = {
'_id': 1,
'name': 'b',
'synonyms': ['b0', 'b1', 'b2'],
'inchi_key': 'asdf1'
}
compound_2 = {
'_id': 2,
'name': 'c',
'synonyms': ['c0', 'c1', 'c2'],
'inchi_key': 'asdf2'
}
cls.src.collection.insert_many([compound_0, compound_1, compound_2])
def setUpClass(cls):
cls.db = 'test'
conf = query_config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_intact_complex.QueryIntactComplex(
server=cls.MongoDB,
database=cls.db,
verbose=True,
max_entries=20,
username=cls.username,
password=cls.password,
collection_str='test_query_intact_complex',
readPreference='primary')
doc_0 = {'name': 'name_0', 'ncbi_id': 9606}
doc_1 = {'name': 'name_1', 'ncbi_id': 9607}
doc_2 = {'name': 'name_2', 'ncbi_id': 9606}
doc_3 = {'name': 'name_3', 'ncbi_id': 9607}
cls.src.collection.insert_many([doc_0, doc_1, doc_2, doc_3])
time.sleep(1)
def setUpClass(cls):
cls.db = 'test'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
cls.MongoDB = MongoDB
cls.username = username
cls.password = password
cls.src = query_protein.QueryProtein(server=cls.MongoDB, database=cls.db,
verbose=True, max_entries=20, username = cls.username,
password = cls.password, collection_str='test_query_protein', readPreference='primary')
cls.src_1 = query_protein.QueryProtein(server=cls.MongoDB, database='datanator',
verbose=True, username = cls.username,
password = cls.password, readPreference='nearest')
cls.src_2 = query_protein.QueryProtein(server=cls.MongoDB, database='datanator-test',
verbose=True, username = cls.username,
password = cls.password, readPreference='nearest')
cls.src.db_obj.drop_collection('test_query_protein')
mock_doc_0 = {'uniprot_id': 'MOCK_0', 'ancestor_taxon_id': [105,104,103,102,101],
'ancestor_name': ['name_5', 'name_4','name_3','name_2','name_1'],
'ko_number': 'MOCK_0', 'ncbi_taxonomy_id': 100, 'abundances': 0}
mock_doc_1 = {'uniprot_id': 'MOCK_1', 'ko_number': 'MOCK_0'} # missing ancestor_taxon_id
mock_doc_2 = {'uniprot_id': 'MOCK_2', 'ancestor_taxon_id': [105,104,103],
'ancestor_name': ['name_5', 'name_4','name_3'],
'ko_number': 'MOCK_0', 'ncbi_taxonomy_id': 102, 'abundances': 2}
mock_doc_3 = {'uniprot_id': 'MOCK_3', 'ancestor_taxon_id': [105,104],
'ancestor_name': ['name_5', 'name_4'],
'ko_number': 'MOCK_1', 'ncbi_taxonomy_id': 103, 'abundances': 3} # different ko_number
mock_doc_4 = {'uniprot_id': 'MOCK_4', 'ancestor_taxon_id': [105],
'ancestor_name': ['name_5'],
'ko_number': 'MOCK_0', 'ncbi_taxonomy_id': 104, 'abundances': 4}
mock_doc_5 = {'uniprot_id': 'MOCK_5', 'ancestor_taxon_id': [105],
'ancestor_name': ['name_5'],
'ncbi_taxonomy_id': 104, 'abundances': 5}
mock_doc_6 = {'uniprot_id': 'MOCK_6', 'ancestor_taxon_id': [105],
'ancestor_name': ['name_5'],
'ko_number': 'MOCK_0', 'ncbi_taxonomy_id': 104, 'abundances': 6}
dic_0 = {'ncbi_taxonomy_id': 0, 'species_name': 's0', 'ancestor_taxon_id': [5,4,3,2,1], 'ancestor_name': ['s5', 's4', 's3', 's2', 's1'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot0', "protein_name": 'special name one', 'kinetics': [{'ncbi_taxonomy_id': 100, 'kinlaw_id': 1},
{'ncbi_taxonomy_id': 101, 'kinlaw_id': 2}], 'abundances': [], 'ko_name': ['KO0 name']}
dic_1 = {'ncbi_taxonomy_id': 1, 'species_name': 's1', 'ancestor_taxon_id': [5,4,3,2], 'ancestor_name': ['s5', 's4', 's3', 's2'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot1', "protein_name": 'nonspeciali name one'}
dic_2 = {'ncbi_taxonomy_id': 2, 'species_name': 's2', 'ancestor_taxon_id': [5,4,3], 'ancestor_name': ['s5', 's4', 's3'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot2', "protein_name": 'nonspeciali name two'}
dic_3 = {'ncbi_taxonomy_id': 3, 'species_name': 's3', 'ancestor_taxon_id': [5,4], 'ancestor_name': ['s5', 's4'], 'ko_number': 'ko3',
'uniprot_id': 'uniprot3', "protein_name": 'your name one'}
dic_4 = {'ncbi_taxonomy_id': 4, 'species_name': 's4', 'ancestor_taxon_id': [5], 'ancestor_name': ['s5'], 'ko_number': 'KO0', 'uniprot_id': 'uniprot4'}
dic_5 = {'ncbi_taxonomy_id': 5, 'species_name': 's5', 'ancestor_taxon_id': [], 'ancestor_name': [], 'ko_number': 'KO0', 'uniprot_id': 'uniprot5'}
dic_6 = {'ncbi_taxonomy_id': 6, 'species_name': 's6', 'ancestor_taxon_id': [5,4,3,2], 'ancestor_name': ['s5', 's4', 's3', 's2'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot6', "protein_name": 'your name two', 'ko_name': 'ko name 0', 'abundances': []}
dic_15 = {'ncbi_taxonomy_id': 6, 'species_name': 's6', 'ancestor_taxon_id': [5,4,3,2], 'ancestor_name': ['s5', 's4', 's3', 's2'],
'ko_number': 'KO1', 'uniprot_id': 'uniprot15', "protein_name": 'your name fifteen', 'ko_name': ['ko name 1']}
dic_14 = {'ncbi_taxonomy_id': 14, 'species_name': 's6 something', 'ancestor_taxon_id': [5,4,3,2], 'ancestor_name': ['s5', 's4', 's3', 's2'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot6', "protein_name": 'your name three'}
dic_7 = {'ncbi_taxonomy_id': 7, 'species_name': 's7', 'ancestor_taxon_id': [5,4,3,2,6], 'ancestor_name': ['s5', 's4', 's3', 's2', 's6'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot7', "protein_name": 'special name two'}
dic_8 = {'ncbi_taxonomy_id': 8, 'species_name': 's8', 'ancestor_taxon_id': [5,4,3,2,6,7], 'ancestor_name': ['s5', 's4', 's3', 's2', 's6', 's7'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot8'}
dic_9 = {'ncbi_taxonomy_id': 9, 'species_name': 's9', 'ancestor_taxon_id': [5,4,3], 'ancestor_name': ['s5', 's4', 's3'], 'ko_number': 'KO0',
'uniprot_id': 'uniprot9'}
dic_10 = {'ncbi_taxonomy_id': 10, 'species_name': 's10', 'ancestor_taxon_id': [5,4,3,9], 'ancestor_name': ['s5', 's4', 's3', 's9'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot10'}
dic_11 = {'ncbi_taxonomy_id': 11, 'species_name': 's11', 'ancestor_taxon_id': [5,4,3,2,1,0], 'ancestor_name': ['s5', 's4', 's3', 's2', 's1', 's0'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot11'}
dic_12 = {'ncbi_taxonomy_id': 12, 'species_name': 's12', 'ancestor_taxon_id': [5,4,3,2,1,0], 'ancestor_name': ['s5', 's4', 's3', 's2', 's1', 's0'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot12'}
dic_13 = {'ncbi_taxonomy_id': 13, 'species_name': 's13', 'ancestor_taxon_id': [5,4,3,2,1], 'ancestor_name': ['s5', 's4', 's3', 's2', 's1'],
'ko_number': 'KO0', 'uniprot_id': 'uniprot13', 'kinetics':[{'ncbi_taxonomy_id': 100, 'kinlaw_id': 1}, {'ncbi_taxonomy_id': 101, 'kinlaw_id': 2}]}
dic_16 = {'ncbi_taxonomy_id': 6, 'species_name': 's6', 'ancestor_taxon_id': [5,4,3,2], 'ancestor_name': ['s5', 's4', 's3', 's2'],
'ko_number': 'KO1', 'uniprot_id': 'uniprot16', "protein_name": 'your name fifteen'}
cls.src.collection.insert_many([mock_doc_0, mock_doc_1, mock_doc_2, mock_doc_3, mock_doc_4,mock_doc_5,mock_doc_6])
cls.src.collection.insert_many([dic_0,dic_1,dic_2,dic_3,dic_4,dic_5,dic_6,dic_7,dic_8,dic_9,dic_10,dic_11,dic_12,dic_13,dic_14,dic_15,dic_16])
def main():
db = 'datanator'
conf = config.TestConfig()
username = conf.USERNAME
password = conf.PASSWORD
MongoDB = conf.SERVER
src = Tabu(MongoDB=MongoDB,
username=username,
password=password,
db=db,
verbose=True,
authSource='admin',
readPreference='nearest',
max_entries=10)
uniprot_docs = src.uniprot_taxon_dist()
sabio_docs = src.taxon_dist("sabio_rk_old",
"taxon_id",
match={"$match": {
"taxon_id": {
"$ne": None
}
}})
rnamod_docs = src.taxon_dist(
"rna_modification",
"modifications.ncbi_taxonomy_id",
unwind={"$unwind": "$modifications"},
match={"$match": {
"modifications.ncbi_taxonomy_id": {
"$ne": None
}
}})
rnahalf_docs = src.taxon_dist("rna_halflife_new",
"halflives.ncbi_taxonomy_id",
unwind={"$unwind": "$halflives"})
conc_docs = src.taxon_dist("metabolite_concentrations",
"concentrations.ncbi_taxonomy_id",
unwind={"$unwind": "$concentrations"})
obj = defaultdict(int)
for (p_doc, s_doc, m_doc, l_doc,
c_doc) in itertools.zip_longest(uniprot_docs,
sabio_docs,
rnamod_docs,
rnahalf_docs,
conc_docs,
fillvalue={
'_id': 1,
'count': 0
}):
obj[p_doc['_id']] += p_doc['count']
obj[s_doc['_id']] += s_doc['count']
obj[m_doc['_id']] += m_doc['count']
obj[l_doc['_id']] += l_doc['count']
obj[c_doc['_id']] += c_doc['count']
# sort obj
new_obj = {
k: v
for k, v in sorted(obj.items(), key=lambda item: item[1], reverse=True)
}
with open("./docs/taxon_distribution.json", "w+") as outfile:
json.dump(new_obj, outfile)
final_obj = {"others": 0}
for i, (key, val) in enumerate(new_obj.items()):
if i < 11 and key != 1:
name = src.db_obj['taxon_tree'].find_one(
{"tax_id": int(key)}, projection={"tax_name": 1})["tax_name"]
final_obj[name] = val
else:
final_obj["others"] += val
with open("./docs/taxon_distribution_frontend.json", "w+") as outfile:
json.dump(final_obj, outfile)
def setUpClass(cls):
cls.src_basic = config.Config()
cls.src_prod = config.ProductionConfig()
cls.src_test = config.TestConfig()
cls.src_ftx = config.FtxConfig()
