初级
统计批处理作业成功率
未完成
初级参考
完整示例代码供参考,建议自己理解后重新输入
def solve():
from pyodide.http import open_url
offices_csv = open_url("https://data.zuihe.com/dbd/core/state_09/offices.csv").read()
staff_csv = open_url("https://data.zuihe.com/dbd/core/state_09/staff.csv").read()
savings_products_csv = open_url("https://data.zuihe.com/dbd/core/state_09/savings_products.csv").read()
clients_csv = open_url("https://data.zuihe.com/dbd/core/state_09/clients.csv").read()
savings_accounts_csv = open_url("https://data.zuihe.com/dbd/core/state_09/savings_accounts.csv").read()
savings_account_transactions_csv = open_url("https://data.zuihe.com/dbd/core/state_09/savings_account_transactions.csv").read()
gl_accounts_csv = open_url("https://data.zuihe.com/dbd/core/state_09/gl_accounts.csv").read()
journal_entries_csv = open_url("https://data.zuihe.com/dbd/core/state_09/journal_entries.csv").read()
cob_job_logs_csv = open_url("https://data.zuihe.com/dbd/core/state_09/cob_job_logs.csv").read()
account_balance_snapshots_csv = open_url("https://data.zuihe.com/dbd/core/state_09/account_balance_snapshots.csv").read()
import sqlite3, pandas as pd
from io import StringIO
conn = sqlite3.connect(':memory:')
pd.read_csv(StringIO(cob_job_logs_csv)).to_sql('cob_job_logs', conn, index=False, if_exists='replace')
df = pd.read_sql_query("""
SELECT job_name, COUNT(*) AS run_count,
SUM(CASE WHEN status='COMPLETED' THEN 1 ELSE 0 END) AS success_count
FROM cob_job_logs GROUP BY job_name ORDER BY run_count DESC
""", conn)
df['success_rate'] = (df['success_count']/df['run_count']*100).round(1).astype(str)+'%'
print(df.to_string(index=False))
conn.close()
示例
输入
solve()
期望输出
job_name run_count success_count success_rate
BALANCE_SNAPSHOT 3 2 66.7%
INTEREST_ACCRUAL 2 2 100.0%
REPORT_GENERATION 1 1 100.0%
MATURITY_CHECK 1 1 100.0%
GL_BALANCE_CHECK 1 1 100.0%
DORMANT_ACCOUNT_SCAN 1 1 100.0%
CHARGE_DUE_UPDATE 1 1 100.0%
👑
升级 VIP
解锁全部题目,畅通无阻地学习
- ✓ 解锁全部训练包所有题目
- ✓ 查看完整参考代码和提示
- ✓ 浏览器内直接运行 Python 代码
- ✓ 自动批改 + 进度追踪
30天
¥18
1年
¥99
2年
¥158
3年
¥199