我有一個 Flask 應用程式，它當前連接到遠程服務器，然后連接到特定的資料庫。我有一個函式接受用戶的日期范圍輸入，然后根據給定的日期查詢資料。
from flask import make_response, redirect, render_template, session, url_for, Blueprint,request
import pandas as pd
import pymssql
from core.database import ConnectionFactory
from core.query import *
dat_a = Blueprint('dat_a', __name__)
ButtonPressed = 0
@dat_a.route('/download', methods=['POST','GET'])
def download():
if session.get('logged_in') != True:
return redirect(url_for('views.index'))
else:
if request.method == 'POST':
return render_template('data.html')
else:
Start = request.args.get('Start Date')
End = request.args.get('End Date')
connection = pymssql.connect(ConnectionFactory.SQL_HOST, ConnectionFactory.SQL_USER_xxx, ConnectionFactory.SQL_PW_xxx,ConnectionFactory.SQL_DB_xxx)
cur=connection.cursor()
query_1 = """
select some column from table
from xx
where date BETWEEN (%s) AND (%s)
"""
query_2 = """
select some column from table
"""
results = []
q_list = [query_1,query_2]
for query in q_list:
cur.execute(query,(Start,End))
results.append(cur)
print(results)
columns = [d[0] for d in cur.description]
data = pd.DataFrame(cur.fetchall(),columns=columns)
print(data)
resp = make_response(data.to_csv())
resp.headers["Content-Disposition"] = "attachment; filename=Data.csv"
resp.headers["Content-Type"] = "text/csv"
return resp
我遇到的問題是讓我的 for 回圈將 query_1 中的資料存盤到串列中，然后將其移動到我的資料框。目前來自 query_2 的資料將存盤到串列中，然后推送到資料幀，但這是不準確的，因為它只是在此時獲取隨機資料。
results = []
q_list = [query_1,query_2]
for query in q_list:
cur.execute(query,(Start,End))
results.append(cur)
print(results)
columns = [d[0] for d in cur.description]
data = pd.DataFrame(cur.fetchall(),columns=columns)
我嘗試了一個嵌套的 for 回圈，它分別呼叫每個查詢，有自己的連接和資料框，但這也沒有改變結果。有沒有更有效的方法來解決這個問題？
uj5u.com熱心網友回復：
你可能正在尋找這樣的東西......
cur = connection.cursor()
results = []
for query, args in [
("select some_column from xx where date BETWEEN (%s) AND (%s)", (Start, End)),
("select some_column from yy", ()),
]:
cur.execute(query, args)
results.extend(cur.fetchall())
# Will be overwritten on each iteration, but it's fine as long as the columns are the same for each query
columns = [d[0] for d in cur.description]
data = pd.DataFrame(results, columns=columns)
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