def local_fetch(r_dict, idlist, tableName, duration=10):
adict = {}
my = Entrez(tableName)
ctime = datetime.now()
bundle = 100
for i in range(len(idlist) / bundle + 1):
tmp = idlist[i * bundle:(i + 1) * bundle]
records = my.select("where fromid in (%s)", ','.join(tmp))
for record in records:
fromid, toid, date = record
#TODO: debug the date
if (ctime - date).days < duration:
adict[fromid] = toid.split(",")
remainingIDlist = []
for ID in idlist:
if ID not in adict:
remainingIDlist += [ID]
return adict, remainingIDlist
#!/bin/python3 # -*- coding: utf-8 -*- """ Created on Tue May 9 2017 @author: Claivaz & Ricci SCRIPT 5 From every parsed blast results of each reference_genome|protein_ID’s sequence (query) present in each Gene_family_*_parsed.out files in each folder of group of bees (data/parsed_blast/Bumble_bees_proteins/, data/parsed_blast/Honey_bees_proteins/, data/parsed_blast/Bumble_Honey_bees_proteins/), extract_taxonomy_hierarchy.py first creates a list of subject IDs (hit IDs, for example ‘WP_052726720’). Subsequently, thanks to Entrez (from Bio package), the function extracts the hierarchical taxonomy of each subject IDs (from protein database of NCBI, for example: 'Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus'). The example (‘WP_052726720’) is used as reference hierarchical taxonomy. Finally, the function looks for the most recent taxa which is shared between each hierarchical taxonomy of each subject IDs and the reference hierarchical taxonomy. Hierarchical taxonomy distance are subjective: Lactobacillus = 1 Lactobacillaceae = 2 Lactobacillales = 3 Bacilli = 4 Firmicutes = 5 Bacteria = 6 None = 7 (which either corresponds to Archae or Eukaryota - contaminations) The function creates a summary file (hierarchical_taxonomy.txt) which is located
