229 lines
9.7 KiB
Python
229 lines
9.7 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
薪资拆分明细表 + 考勤数据表 导入脚本
|
|
遵循现有 import_log + records 模式
|
|
"""
|
|
import openpyxl
|
|
import hashlib
|
|
import psycopg2
|
|
import os
|
|
import sys
|
|
from datetime import datetime
|
|
|
|
DB_CONFIG = {
|
|
'host': 'localhost',
|
|
'port': 5432,
|
|
'dbname': 'bill_query',
|
|
'user': 'freedak',
|
|
'password': '',
|
|
}
|
|
|
|
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
|
SALARY_FILE = os.path.join(BASE_DIR, '马兰拉面数据分析', '薪资拆分明细表_脱敏.xlsx')
|
|
ATTENDANCE_FILE = os.path.join(BASE_DIR, '马兰拉面数据分析', '考勤数据表-脱敏.xlsx')
|
|
|
|
def file_sha256(filepath):
|
|
h = hashlib.sha256()
|
|
with open(filepath, 'rb') as f:
|
|
for chunk in iter(lambda: f.read(8192), b''):
|
|
h.update(chunk)
|
|
return h.hexdigest()
|
|
|
|
def to_num(val):
|
|
if val is None or val == '':
|
|
return 0
|
|
try:
|
|
return float(val)
|
|
except (ValueError, TypeError):
|
|
return 0
|
|
|
|
def to_text(val):
|
|
if val is None:
|
|
return None
|
|
s = str(val).strip()
|
|
return s if s else None
|
|
|
|
def import_salary(conn, report_month='2026-04-01'):
|
|
print(f'导入薪资拆分明细表: {SALARY_FILE}')
|
|
sha = file_sha256(SALARY_FILE)
|
|
wb = openpyxl.load_workbook(SALARY_FILE, read_only=True, data_only=True)
|
|
ws = wb[wb.sheetnames[0]]
|
|
|
|
# Row 1: title, Row 2: merged title, Row 3: headers, Row 4+: data
|
|
rows = list(ws.iter_rows(min_row=4, values_only=True))
|
|
data_rows = [r for r in rows if r[0] is not None and r[9] is not None and str(r[9]).strip()]
|
|
print(f' 数据行数: {len(data_rows)}')
|
|
|
|
report_month = report_month
|
|
source_file = os.path.basename(SALARY_FILE)
|
|
|
|
cur = conn.cursor()
|
|
# Check if already imported
|
|
cur.execute(
|
|
'SELECT import_id FROM public.salary_import_log WHERE report_month = %s AND source_file = %s AND file_sha256 = %s',
|
|
(report_month, source_file, sha)
|
|
)
|
|
existing = cur.fetchone()
|
|
if existing:
|
|
print(f' 已导入过, import_id={existing[0]}, 跳过')
|
|
wb.close()
|
|
return
|
|
|
|
# Insert import log
|
|
cur.execute(
|
|
'''INSERT INTO public.salary_import_log (report_month, source_file, file_sha256, workbook_rows, imported_rows)
|
|
VALUES (%s, %s, %s, %s, %s) RETURNING import_id''',
|
|
(report_month, source_file, sha, len(data_rows), len(data_rows))
|
|
)
|
|
import_id = cur.fetchone()[0]
|
|
print(f' import_id={import_id}')
|
|
|
|
# Batch insert
|
|
insert_sql = '''INSERT INTO public.salary_detail_records (
|
|
import_id, source_row,
|
|
org_level1, org_level2, org_level3, org_level4, org_level5, org_level6, org_level7, org_level8,
|
|
employee_code, salary_period, position, work_type, employment_type, hire_date, leave_date,
|
|
salary_standard, base_wage, overtime_subsidy, social_subsidy, position_wage, tenure_wage,
|
|
hourly_rate, total_wage, brand_wage, rent_subsidy,
|
|
month_days, expected_attend, calc_attend, actual_attend, actual_hours,
|
|
expected_rest, actual_rest, expected_legal_holiday, actual_legal_holiday,
|
|
comp_leave_days, annual_leave, marriage_leave, paid_leave, bereavement_leave,
|
|
personal_leave_days, personal_leave_deduction, furlough_days, furlough_deduction,
|
|
injury_leave_days, injury_leave_deduction, absent_days, absent_deduction, join_leave_absent,
|
|
attendance_wage, rest_subsidy, overtime_pay, shift_subsidy, comp_leave_wage,
|
|
cashier_amount, bonus, subsidy, subsidy_remark, rush_wage, total_supplement,
|
|
late_deduction, no_punch_deduction, internal_social_total, internal_social_remark,
|
|
loan, loan_remark, fine, compensation, total_deduction, injury_wage, singapore_subsidy,
|
|
perf_standard, perf_score, perf_amount, phone_allowance, dorm_fee,
|
|
net_salary, gross_pay, income_tax, net_pay,
|
|
external_base_standard, external_overtime, external_absence, external_bonus,
|
|
external_subsidy, external_other_deduction, external_gross,
|
|
pension_deduction, medical_deduction, unemployment_deduction,
|
|
external_social_total, external_tax, external_net, internal_tax, internal_net,
|
|
external_unit, attendance_remark, employment_type_orig, salary_category
|
|
) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)'''
|
|
|
|
batch = []
|
|
batch_size = 500
|
|
for idx, r in enumerate(data_rows):
|
|
source_row = idx + 4 # Excel row number
|
|
vals = [
|
|
import_id, source_row,
|
|
to_text(r[1]), to_text(r[2]), to_text(r[3]), to_text(r[4]), to_text(r[5]), to_text(r[6]), to_text(r[7]), to_text(r[8]),
|
|
to_text(r[9]), to_text(r[10]), to_text(r[11]), to_text(r[12]), to_text(r[13]), to_text(r[14]), to_text(r[15]),
|
|
to_num(r[16]), to_num(r[17]), to_num(r[18]), to_num(r[19]), to_num(r[20]), to_num(r[21]),
|
|
to_num(r[22]), to_num(r[23]), to_num(r[24]), to_num(r[25]),
|
|
to_num(r[26]), to_num(r[27]), to_num(r[28]), to_num(r[29]), to_num(r[30]),
|
|
to_num(r[31]), to_num(r[32]), to_num(r[33]), to_num(r[34]),
|
|
to_num(r[35]), to_num(r[36]), to_num(r[37]), to_num(r[38]), to_num(r[39]),
|
|
to_num(r[40]), to_num(r[41]), to_num(r[42]), to_num(r[43]),
|
|
to_num(r[44]), to_num(r[45]), to_num(r[46]), to_num(r[47]), to_num(r[48]),
|
|
to_num(r[49]), to_num(r[50]), to_num(r[51]), to_num(r[52]), to_num(r[53]),
|
|
to_num(r[54]), to_num(r[55]), to_num(r[56]), to_text(r[57]), to_num(r[58]), to_num(r[59]),
|
|
to_num(r[60]), to_num(r[61]), to_num(r[62]), to_text(r[63]),
|
|
to_num(r[64]), to_text(r[65]), to_num(r[66]), to_num(r[67]), to_num(r[68]), to_num(r[69]), to_num(r[70]),
|
|
to_num(r[71]), to_num(r[72]), to_num(r[73]), to_num(r[74]), to_num(r[75]),
|
|
to_num(r[76]), to_num(r[77]), to_num(r[78]), to_num(r[79]),
|
|
to_num(r[80]), to_num(r[81]), to_num(r[82]), to_num(r[83]),
|
|
to_num(r[84]), to_num(r[85]), to_num(r[86]),
|
|
to_num(r[87]), to_num(r[88]), to_num(r[89]),
|
|
to_num(r[90]), to_num(r[91]), to_num(r[92]), to_num(r[93]), to_num(r[94]),
|
|
to_text(r[95]), to_text(r[96]), to_text(r[97]), to_text(r[98]),
|
|
]
|
|
batch.append(vals)
|
|
if len(batch) >= batch_size:
|
|
cur.executemany(insert_sql, batch)
|
|
conn.commit()
|
|
print(f' 已导入 {idx + 1}/{len(data_rows)} 行')
|
|
batch = []
|
|
|
|
if batch:
|
|
cur.executemany(insert_sql, batch)
|
|
conn.commit()
|
|
print(f' 已导入 {len(data_rows)}/{len(data_rows)} 行')
|
|
|
|
wb.close()
|
|
print(f' 薪资明细导入完成: {len(data_rows)} 行')
|
|
|
|
def import_attendance(conn, report_month='2026-04-01'):
|
|
print(f'\n导入考勤数据表: {ATTENDANCE_FILE}')
|
|
sha = file_sha256(ATTENDANCE_FILE)
|
|
wb = openpyxl.load_workbook(ATTENDANCE_FILE, read_only=True, data_only=True)
|
|
ws = wb[wb.sheetnames[0]]
|
|
|
|
# Row 1: headers, Row 2+: data
|
|
rows = list(ws.iter_rows(min_row=2, values_only=True))
|
|
data_rows = [r for r in rows if r[0] is not None]
|
|
print(f' 数据行数: {len(data_rows)}')
|
|
|
|
report_month = report_month
|
|
source_file = os.path.basename(ATTENDANCE_FILE)
|
|
|
|
cur = conn.cursor()
|
|
cur.execute(
|
|
'SELECT import_id FROM public.attendance_import_log WHERE report_month = %s AND source_file = %s AND file_sha256 = %s',
|
|
(report_month, source_file, sha)
|
|
)
|
|
existing = cur.fetchone()
|
|
if existing:
|
|
print(f' 已导入过, import_id={existing[0]}, 跳过')
|
|
wb.close()
|
|
return
|
|
|
|
cur.execute(
|
|
'''INSERT INTO public.attendance_import_log (report_month, source_file, file_sha256, workbook_rows, imported_rows)
|
|
VALUES (%s, %s, %s, %s, %s) RETURNING import_id''',
|
|
(report_month, source_file, sha, len(data_rows), len(data_rows))
|
|
)
|
|
import_id = cur.fetchone()[0]
|
|
print(f' import_id={import_id}')
|
|
|
|
# 33 columns: 工号, 岗位, 所在部门, day_01..day_30
|
|
cols = ['import_id', 'source_row', 'employee_code', 'position', 'department']
|
|
cols += [f'day_{str(i).zfill(2)}' for i in range(1, 31)]
|
|
placeholders = ', '.join(['%s'] * len(cols))
|
|
col_names = ', '.join(cols)
|
|
insert_sql = f'INSERT INTO public.attendance_records ({col_names}) VALUES ({placeholders})'
|
|
|
|
batch = []
|
|
batch_size = 500
|
|
for idx, r in enumerate(data_rows):
|
|
source_row = idx + 2
|
|
vals = [import_id, source_row, to_text(r[0]), to_text(r[1]), to_text(r[2])]
|
|
# Days 1-30 (columns 3-32)
|
|
for d in range(30):
|
|
vals.append(to_text(r[3 + d]) if 3 + d < len(r) else None)
|
|
batch.append(vals)
|
|
if len(batch) >= batch_size:
|
|
cur.executemany(insert_sql, batch)
|
|
conn.commit()
|
|
print(f' 已导入 {idx + 1}/{len(data_rows)} 行')
|
|
batch = []
|
|
|
|
if batch:
|
|
cur.executemany(insert_sql, batch)
|
|
conn.commit()
|
|
print(f' 已导入 {len(data_rows)}/{len(data_rows)} 行')
|
|
|
|
wb.close()
|
|
print(f' 考勤数据导入完成: {len(data_rows)} 行')
|
|
|
|
def main():
|
|
report_month = sys.argv[1] if len(sys.argv) > 1 else '2026-04-01'
|
|
print(f'导入月份: {report_month}')
|
|
conn = psycopg2.connect(**DB_CONFIG)
|
|
conn.autocommit = False
|
|
try:
|
|
import_salary(conn, report_month)
|
|
import_attendance(conn, report_month)
|
|
print('\n=== 导入完成 ===')
|
|
except Exception as e:
|
|
conn.rollback()
|
|
print(f'错误: {e}', file=sys.stderr)
|
|
raise
|
|
finally:
|
|
conn.close()
|
|
|
|
if __name__ == '__main__':
|
|
main()
|