def read_file(path):
ged = open(path)
ged_lines = ged.readlines()
person_date_tags = ["BIRT", "DEAT"]
fam_date_tags = ["MARR","DIV"]
fam_flag=False
date_type=''
individuals={}
ind_id = ""
families={}
#Makes individual and family dicts
for ged_line in ged_lines:
status, tag, args = check(strip(ged_line))
if(status == True):
if (tag == "FAMC"):
individuals[ind_id]["FAMC"] = args
if (tag == "FAMS"):
if tag not in individuals[ind_id].keys():
individuals[ind_id]["FAMS"] = [args]
else:
individuals[ind_id]['FAMS'].append(args)
if(tag == "INDI"):
ind_id = args
individuals[ind_id] = {}
individuals[ind_id]["ID"] = args
fam_flag = False
#Gets name and sex
if(tag == "NAME" or tag == "SEX"):
individuals[ind_id][tag] = args
#gets date
if(tag in person_date_tags):
date_type = tag
if(tag == "DATE"):
if(fam_flag == False):
individuals[ind_id][date_type] = args
else:
families[ind_id][date_type] = args
#Indetifies family
if(tag == "FAM"):
ind_id = args
fam_flag = True
families[ind_id] = {}
families[ind_id]["ID"] = args
#gets husband wife and child IDS
if(tag in fam_date_tags):
date_type = tag
if(tag == "HUSB" or tag == "WIFE"):
families[ind_id][tag]=args
if(tag == "CHIL"):
if( tag not in families[ind_id].keys() ):
families[ind_id][tag] = [args]
else:
families[ind_id][tag].append(args)
ged.close
individuals = UsefulFunctions.age_bank(families, individuals)
return(individuals, families)
ind_id = args
fam_flag = True
families[ind_id] = {}
families[ind_id]["ID"] = args
#gets husband wife and child IDS
if (tag in fam_date_tags):
date_type = tag
if (tag == "HUSB" or tag == "WIFE"):
families[ind_id][tag] = args
if (tag == "CHIL"):
if (tag not in families[ind_id].keys()):
families[ind_id][tag] = [args]
else:
families[ind_id][tag].append(args)
ged.close
return (individuals, families)
#reads information from file
individuals, families = read_file('./test.ged')
#calculates and stores useful data, mostly ages
individuals = UsefulFunctions.age_bank(families, individuals)
#printing in table format
ind_table = pd.DataFrame(individuals).transpose()
print(tabulate(ind_table, headers='keys', tablefmt='psql'))
fam_table = pd.DataFrame(families).transpose()
print(tabulate(fam_table, headers='keys', tablefmt='psql'))