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| import re | |
| from datetime import datetime | |
| import psycopg2 | |
| import pandas as pd | |
| from DbConnection import DbConnection | |
| class SkillExtractorDetailsV1: | |
| def GetSkillData(skill_extractor, inputData): | |
| getdbskills = SkillExtractorDetailsV1.GetSkillDatafromDB() | |
| skills_list = [] | |
| annotations = skill_extractor.annotate(inputData) | |
| matches = annotations['results']['full_matches']+annotations['results']['ngram_scored'] | |
| skill_Typelst = [] | |
| skill_Scorelst = [] | |
| reuiredSkilllst = [] | |
| softskillslst = [] | |
| goodtohavelst = [] | |
| for result in matches: | |
| skill_id = result['skill_id'] | |
| skill_name1 = skill_extractor.skills_db[skill_id]['skill_name'] | |
| skill_name = skill_name1.split("(")[0].strip() | |
| skill_type = skill_extractor.skills_db[skill_id]['skill_type'] | |
| skill_score = round(result['score'],2) * 100 | |
| result = getdbskills[getdbskills['skill'] == skill_name.upper()] | |
| if(result.empty and skill_name not in skills_list): | |
| skills_list.append(skill_name) | |
| if(skill_score > 99 and skill_type != 'Soft Skill'): | |
| reuiredSkilllst.append(skill_name) | |
| elif(skill_score > 50 and skill_type == 'Soft Skill'): | |
| softskillslst.append(skill_name) | |
| elif(skill_score <= 50 and skill_type == 'Soft Skill'): | |
| goodtohavelst.append(skill_name) | |
| elif(skill_score <= 99 and skill_type != 'Soft Skill'): | |
| goodtohavelst.append(skill_name) | |
| # skills_list.append(skill_name) | |
| # skill_Typelst.append(skill_type) | |
| # skill_Scorelst.append(skill_score) | |
| else: | |
| print('Weightage zero skill-'+ skill_name) | |
| # list_of_tuples = list(zip(skills_list, skill_Typelst,skill_Scorelst)) | |
| # df = pd.DataFrame(list_of_tuples, | |
| # columns=['Skill_Name', 'Skill_Type','Skill_Score']) | |
| newSkilllst = SkillExtractorDetailsV1.extractWords(inputData) | |
| reqSkill = '' | |
| if(len(newSkilllst)>0): | |
| reqSkill = ','.join(reuiredSkilllst) + ',' + ','.join(newSkilllst) | |
| else: | |
| reqSkill = ','.join(reuiredSkilllst) | |
| data = {'Data':['Required Skills', 'Soft Skills', 'Good to have Skills'], 'Values':[reqSkill, ','.join(softskillslst), ','.join(goodtohavelst)]} | |
| df = pd.DataFrame(data) | |
| return df | |
| def GetSkillDatafromDB(): | |
| conn = DbConnection.GetMySQLDbConnection() | |
| query = "select upper(skilldetails) skill from skillmaster where weightage = 0" | |
| df = pd.read_sql_query(query, conn) | |
| return df | |
| def extractWords(job_description): | |
| job_roles = [] | |
| job_description = job_description.replace(')',' ') | |
| delimiters = ",", " ", " , ", ";","\n","/","\\" | |
| regex_pattern = '|'.join(map(re.escape, delimiters)) | |
| df = SkillExtractorDetailsV1.getNewSkills() | |
| data = re.split(regex_pattern, job_description) | |
| #data = job_description.split(',') | |
| for ds in data: | |
| #print(ds) | |
| try: | |
| if(SkillExtractorDetailsV1.skill_Validate(df,ds.strip())): | |
| job_roles.append(ds) | |
| #SkillExtractorDetails.GetSkillId(ds.strip(),JdMasterid,db_params) | |
| print("Additional Skills : " + ds) | |
| except Exception as error: | |
| test = 1 | |
| return job_roles | |
| def getNewSkills(): | |
| query = "select skillid,skilldetails,skilltype,skill_score from skillmaster where weightage = -2" | |
| conn = DbConnection.GetMySQLDbConnection() | |
| cursor = conn.cursor() | |
| df_skill_master = pd.read_sql_query(query, conn) | |
| df_skill_master['skilldetails'] = df_skill_master['skilldetails'].str.upper() | |
| cursor.close() | |
| # Close the connection | |
| conn.close() | |
| #print(df_skill_master) | |
| return df_skill_master | |
| def skill_Validate(df, skill): | |
| skill = skill.upper() | |
| if (len(skill.split()) < 2 and len(skill) < 3) or len(skill.split())==1: | |
| df['skill_present'] = df['skilldetails'].apply(lambda x: re.match(rf'^{skill}$', x)) | |
| if any(df['skill_present']): | |
| #print("Valid Skill") | |
| return 1 | |
| else: | |
| #print("Not a Skill") | |
| return 0 | |
| elif df['skilldetails'].str.contains(skill.upper()).any(): | |
| #print("Valid Skill") | |
| return 1 | |
| else: | |
| # print("Not a Skill") | |
| return 0 |