def main():
print("GO")
start_time = time.time()
document_map = {}
try:
cand_table = db["candidate"]
#characteristic_id_list = list(ideal_table.find({}, {"global_job_category_id": 1, "Skills": 1}).distinct("global_job_category_id"))
characteristic_list = getCharacteristicMap()
#print("%s" % characteristic_list)
print("%s" % len(characteristic_list))
print("---query Time: %s seconds ---" % (time.time() - start_time))
print("done")
skip_amount = 0
cand_count = 0
total_cand = cand_table.count()
print("%s" % total_cand)
start_delta = 200000
total_cand = 300000
while (start_delta + skip_amount) < total_cand:
candidate_list = list(cand_table.find({}, {"candidate_id":1,"job_skill_names": 1}).skip(start_delta + skip_amount).limit(2500))
for candidate in candidate_list:
cand_count += 1
cand_cat_count = 0
print("Running candidate - %s" % cand_count)
classification_array = []
for key, record in characteristic_list.items():
if matchSkills(candidate["job_skill_names"], record["Skills"], .75):
cand_cat_count += 1
if document_map.get(key) is None:
document_map[key] = []
if candidate["candidate_id"] not in document_map[key]:
document_map[key].append(candidate["candidate_id"])
print("Added to %s categories" % cand_cat_count)
#print("%s" % json.dumps(document_map, default=obj_dict))
skip_amount += 2500
count = 0
text_file.write("[")
for key, val in document_map.items():
record = ClassifierObject(key, val)
recordJson = record.toJson()
text_file.write("%s" % recordJson)
count += 1
if count < len(document_map):
text_file.write(",")
text_file.write("]")
text_file.close()
print("---Parse Time: %s seconds ---" % (time.time() - start_time))
except Exception as e:
DebugException(e)
print("---Run Time: %s seconds ---" % (time.time() - start_time))
def main():
print("GO")
start_time = time.time()
document_map = {}
try:
cand_table = db["candidate_skills_from_parsed_resumes"]
#characteristic_id_list = list(ideal_table.find({}, {"global_job_category_id": 1, "Skills": 1}).distinct("global_job_category_id"))
characteristic_list = getCharacteristicMap()
#print("%s" % characteristic_list)
print("Total Number of Job Categories - %s" % len(characteristic_list))
print("---Job Categories Retrieval Time: %s seconds ---" % (time.time() - start_time))
#print("done")
skip_amount = 0
cand_count = 0
total_cand = cand_table.count()
#print("%s" % total_cand)
start_delta = 0
category_map = db["category_candidate_map"]
total_cand = total_cand/2
while (start_delta + skip_amount) < total_cand:
candidate_list = list(cand_table.find({}, {"candidate_id":1,"parsedWords": 1}).skip(start_delta + skip_amount).limit(5000))
for candidate in candidate_list:
cand_count += 1
cand_cat_count = 0
parsedWords = candidate["parsedWords"]
candidate_skill_list = []
for words in parsedWords:
candidate_skill_list.append(words["word"].lower())
printPerThousand = cand_count%1000
if(printPerThousand == 0):
print("Running candidate - %s - Time Taken So Far - %s" % (cand_count,(time.time() - start_time)))
printPerThousand = 1
#print("Running candidate - %s - Time Taken So Far - %s" % (cand_count,(time.time() - start_time)))
#print("Running candidate - %s - Time Taken So Far - %s" % (cand_count,(time.time() - start_time)))
classification_array = []
for key, record in characteristic_list.items():
if matchSkills(candidate_skill_list, record["Skills"], Threshold):
cand_cat_count += 1
if document_map.get(key) is None:
document_map[key] = []
if candidate["candidate_id"] not in document_map[key]:
document_map[key].append(candidate["candidate_id"])
#category_map.update({"global_job_category_id":key},{"$addToSet":{"candidates":candidate["candidate_id"]}},True)
#print("Added to %s categories" % cand_cat_count)
#print("%s" % json.dumps(document_map, default=obj_dict))
skip_amount += 5000
count = 0
text_file.write("[")
for key, val in document_map.items():
record = ClassifierObject(key, val)
recordJson = record.toJson()
text_file.write("%s" % recordJson)
count += 1
if count < len(document_map):
text_file.write(",")
text_file.write("]")
text_file.close()
print("---Parse Time: %s seconds ---" % (time.time() - start_time))
except Exception as e:
DebugException(e)
print("---Run Time: %s seconds ---" % (time.time() - start_time))
