在 Python 的 MS Access 数据库中插入或更新行

Insert or update rows in MS Access database in Python

我有一个 MS Access table (SearchAdsAccountLevel),需要经常从 python 脚本更新。我已经设置了 pyodbc 连接,现在我想根据 Date_ 和 CampaignId 字段是否与 df 数据匹配,从 pandas df 到 MS Access table UPDATE/INSERT 行.

查看前面的示例,我构建了 UPDATE 语句,该语句使用 iterrows 遍历 df 中的所有行并执行 SQL 代码,如下所示:

    connection_string = (
            r"Driver={Microsoft Access Driver (*.mdb, *.accdb)};"
            r"c:\AccessDatabases\Database2.accdb;"
    )
    cnxn = pyodbc.connect(connection_string, autocommit=True)
    crsr = cnxn.cursor()

    for index, row in df.iterrows():
            crsr.execute("UPDATE SearchAdsAccountLevel SET [OrgId]=?, [CampaignName]=?, [CampaignStatus]=?, [Storefront]=?, [AppName]=?, [AppId]=?, [TotalBudgetAmount]=?, [TotalBudgetCurrency]=?, [DailyBudgetAmount]=?, [DailyBudgetCurrency]=?, [Impressions]=?, [Taps]=?, [Conversions]=?, [ConversionsNewDownloads]=?, [ConversionsRedownloads]=?, [Ttr]=?, [LocalSpendAmount]=?, [LocalSpendCurrency]=?, [ConversionRate]=?, [Week_]=?, [Month_]=?, [Year_]=?, [Quarter]=?, [FinancialYear]=?, [RowUpdatedTime]=? WHERE [Date_]=? AND [CampaignId]=?",
                        row['OrgId'],
                        row['CampaignName'],
                        row['CampaignStatus'],
                        row['Storefront'],
                        row['AppName'],
                        row['AppId'],
                        row['TotalBudgetAmount'],
                        row['TotalBudgetCurrency'],
                        row['DailyBudgetAmount'],
                        row['DailyBudgetCurrency'],
                        row['Impressions'],
                        row['Taps'],
                        row['Conversions'],
                        row['ConversionsNewDownloads'],
                        row['ConversionsRedownloads'],
                        row['Ttr'],
                        row['LocalSpendAmount'],
                        row['LocalSpendCurrency'],
                        row['ConversionRate'],
                        row['Week_'],
                        row['Month_'],
                        row['Year_'],
                        row['Quarter'],
                        row['FinancialYear'],
                        row['RowUpdatedTime'],
                        row['Date_'],
                        row['CampaignId'])
crsr.commit()

我想遍历我的 df 中的每一行(大约 3000),如果 ['Date_'] 和 ['CampaignId'] 匹配,我更新所有其他字段。否则我想在我的 Access Table 中插入整个 df 行(创建新行)。实现这一目标的最有效方法是什么?

考虑 DataFrame.values 并将列表传递给 executemany 调用,确保为 UPDATE 查询相应地对列进行排序:

cols = ['OrgId', 'CampaignName', 'CampaignStatus', 'Storefront',
        'AppName', 'AppId', 'TotalBudgetAmount', 'TotalBudgetCurrency',
        'DailyBudgetAmount', 'DailyBudgetCurrency', 'Impressions',
        'Taps', 'Conversions', 'ConversionsNewDownloads', 'ConversionsRedownloads',
        'Ttr', 'LocalSpendAmount', 'LocalSpendCurrency', 'ConversionRate',
        'Week_', 'Month_', 'Year_', 'Quarter', 'FinancialYear',
        'RowUpdatedTime', 'Date_', 'CampaignId']

sql = '''UPDATE SearchAdsAccountLevel 
            SET [OrgId]=?, [CampaignName]=?, [CampaignStatus]=?, [Storefront]=?, 
                [AppName]=?, [AppId]=?, [TotalBudgetAmount]=?, 
                [TotalBudgetCurrency]=?, [DailyBudgetAmount]=?, 
                [DailyBudgetCurrency]=?, [Impressions]=?, [Taps]=?, [Conversions]=?, 
                [ConversionsNewDownloads]=?, [ConversionsRedownloads]=?, [Ttr]=?, 
                [LocalSpendAmount]=?, [LocalSpendCurrency]=?, [ConversionRate]=?,
                [Week_]=?, [Month_]=?, [Year_]=?, [Quarter]=?, [FinancialYear]=?, 
                [RowUpdatedTime]=? 
          WHERE [Date_]=? AND [CampaignId]=?'''

crsr.executemany(sql, df[cols].values.tolist())   
cnxn.commit()

对于插入,使用具有与最终 table 完全相同的结构的临时暂存 table,您可以使用 make-table 查询创建它:SELECT TOP 1 * INTO temp FROM final。此临时 table 将定期清除并与所有数据框行一起插入。最终查询仅将新行从 temp 迁移到 final NOT EXISTS, NOT IN, or LEFT JOIN/NULL。您可以随时 运行 此查询,而不必担心每个 Date_CampaignId 列的重复项。

# CLEAN OUT TEMP
sql = '''DELETE FROM SearchAdsAccountLevel_Temp'''
crsr.executemany(sql)   
cnxn.commit()

# APPEND TO TEMP
sql = '''INSERT INTO SearchAdsAccountLevel_Temp (OrgId, CampaignName, CampaignStatus, Storefront,
                                AppName, AppId, TotalBudgetAmount, TotalBudgetCurrency,
                                DailyBudgetAmount, DailyBudgetCurrency, Impressions,
                                Taps, Conversions, ConversionsNewDownloads, ConversionsRedownloads,
                                Ttr, LocalSpendAmount, LocalSpendCurrency, ConversionRate,
                                Week_, Month_, Year_, Quarter, FinancialYear,
                                RowUpdatedTime, Date_, CampaignId)    
         VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, 
                 ?, ?, ?, ?, ?, ?, ?, ?, ?, 
                 ?, ?, ?, ?, ?, ?, ?, ?, ?);'''

crsr.executemany(sql, df[cols].values.tolist())   
cnxn.commit()

# MIGRATE TO FINAL
sql = '''INSERT INTO SearchAdsAccountLevel 
         SELECT t.* 
         FROM SearchAdsAccountLevel_Temp t
         LEFT JOIN SearchAdsAccountLevel f
            ON t.Date_ = f.Date_ AND t.CampaignId = f.CampaignId
         WHERE f.OrgId IS NULL'''
crsr.executemany(sql)   
cnxn.commit()