使用pymssql导出CSV格式文件

这里是官方例子http://www.pymssql.org/pymssql_examples.html

下面实例程序使用python 2.7运行

# -*- coding: utf-8 -*-
import csv
import pymssql

if __name__ == '__main__':
    sql_st = '''
     SQL语句
    '''

    conn = pymssql.connect(host = '数据服务器地址', user = '用户名', password = '密码', 
    database = '数据库名称')
    cur = conn.cursor()

    cur.execute(sql_st)
    rows = cur.fetchall()
    #如果使用中文则'test.csv'替换成'测试.csv'.decode('utf-8')
    with open('test.csv', 'wb') as f:
        csv_writer = csv.writer(f)
        description = map(lambda x: x[0].encode('gb18030'), cur.description)
        #写入列名        
        csv_writer.writerow(description)
        for row in rows:
            #csv_writer.writerow(row)
            csv_writer.writerow([(x+'\t').encode('gb18030') if isinstance(x, unicode)        else x  for x in row])

    cur.close()
    conn.close()

    print('ok')

 

 

``` import numpy as np import pymssql import pandas as pd import math def calculate_workday(): server = '100.00.00.00' database = 'D' username = 'x' password = '@' port = '1433' # 如果使用默认端口号(1433),则可以省略此步骤 # 连接数据库并执行查询 conn = pymssql.connect(server, user=username, password=password, database=database, port=port) query ="SELECT * FROM DLCH.dbo.CH_MainDt WHERE ((YWNRId >= 1 AND YWNRId <= 41) OR (YWNRId >= 85 AND YWNRId <= 97)) ORDER BY CreateTime" # 获取查询结果,将结果写入df csv_data = pd.read_sql_query(query, conn) conn.close() # 保证需要参与计算工期的列为数值 columns_to_convert = ['paraInt1', 'paraInt2', 'paraInt3', 'paraFloat1', 'paraFloat2', 'paraFloat5'] for column in columns_to_convert: csv_data[column] = pd.to_numeric(csv_data[column], errors='coerce') # 判断工期和工作量并将结果存入新的列中 def cal_workday(csv_data): csv_data['工期'] = '协商' csv_data['工作量'] = '' csv_data['工作量'] = csv_data['工作量'].astype(str) # 转化成字符串形式 # YWNRId=7 csv_data.loc[csv_data['YWNRId'] == '7', '工期'] = csv_data.loc[ csv_data['YWNRId'] == '7', 'paraFloat1'].apply( lambda x: 7 if x <= 50000 else min(7 + 2 * math.ceil((x - 50000) / 50000), 25) ) # YWNRId=16 csv_data.loc[csv_data['YWNRId'] == '16', '工期'] = csv_data.loc[ csv_data['YWNRId'] == '16', 'paraFloat1'].apply( lambda x: 10 if x <= 50000 else ( 12 if x <= 100000 else ( 15 if x <= 200000 else 15 + 3 * math.ceil((x - 200000) / 50000) ) ) ) return csv_data 应用计算结果 csv_data = cal_workday(csv_data) # 关键步骤:将计算结果合并回原DataFrame # 输出到CSV csv_data.to_csv('计算结果.csv', index=False, encoding='utf_8_sig') # 支持中文路径 print("文件已成功导出为 计算结果.csv")```name 'cal_workday' is not defined
最新发布
03-15
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