Python/Django 下载Excel2007

Posted julygift

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一、前提

  上一篇,我写了下载Excel2003的博文,这里写下载Excel2007的博文的原因有三:

    第一、Excel2003基本已经淘汰了

    第二、Excel2003下载文件太大,不利于网络传输

    第三、xlwt这个库有个Bug,就是它不支持单元格字符串长度超过32767【这里,有兴趣的同学可以查看下源码】

  好了,废话不多说了,我们进入正题。

二、安装

  本文使用的是pandas,引入库的方式:pip install pandas

三、使用

  首先、引入该库,例如:import pandas

  其次、

    创建Excel文档:

      out = BytesIO()  创建的输出流

      excel = pandas.ExcelWriter(out, engine = ‘xlsxwriter‘)  这里使用xlsxwriter引擎创建, 创建的文件直接关联到输出流out,安装xlsxwriter也很简单,如: pip install xlsxwriter

    创建Sheet:

      summary_df = pandas.DataFrame({})  这里使用空对象创建,下面代码生成的sheet会是一个空sheet

      summary_df.to_excel(excel, sheet_name = "Summary", index = False, header = False)  这里会在excel中创建一个sheet名称为Summary的文档,index=False,使得Excel不会咋第一列创建序号列,xlsxwriter默认会在第一列创建序号列。这里的参数具体用法请参考相关文档。

    获取sheet:worksheet = excel.sheets["Summary"]  获取sheet名称为summary的sheet名

    设置列宽:worksheet.set_column(‘D:D‘, 18, long_text_format)  设置第四列宽度为18,使用样式long_text_format【这个样式需要自己提前定义】

    保存Excel:excel.save()

      Excel文件会直接输出上面创建的输出流out。

第四、输出

   

response = HttpResponse(out.getvalue(), content_type = application/vnd.ms-excel)
    dt = datetime.datetime.now()
    response[Content-Disposition] = attachment;filename={} {}.xlsx.format(urlquote(domain_name), dt.strftime(%Y-%m-%d %H-%M-%S))
    print("End downloading...")
    return response

 

贴下源码:

def download_report(request, task_id, domain_name = 全部):
    print("start downloading xlsx...", task_id)
    print("start downloading...", domain_name)

    domains = [{domain_name: domain_name}]
    ai_task = AITask.objects.get(id = task_id)
    if domain_name == 全部:
        if 1 == ai_task.type:
            domains = Classification.objects.values(domain_name).distinct().filter(type = 1).order_by("domain_name")
        elif 2 == ai_task.type:
            domains = Classification.objects.values(domain_name).distinct().filter(type = 2).order_by("domain_name")

    out = BytesIO()
    excel = pandas.ExcelWriter(out, engine = xlsxwriter)

    summary_title = [Domain, Pass, Fail]
    summary_dict = {title: [] for title in summary_title}
    domain_title = [Domain, One level, Two level, Semantic, Priority, Intent group, Intent, Result,
                    Handle time, Response time, Server Domain, Detail]

    summary_df = pandas.DataFrame({})
    summary_df.to_excel(excel, sheet_name = "Summary", index = False, header = False)

    workbook = excel.book
    body_format = workbook.add_format(style.body_style)
    header_format = workbook.add_format(style.head_style)
    long_text_format = workbook.add_format(style.long_text_style)
    large_text_format = workbook.add_format(style.large_text_style)

    sheet_data = {}
    for domain in domains:
        dmain_name = domain["domain_name"]
        sheet_data[dmain_name] = {column_name: [] for column_name in domain_title}
        reports = ai_task.report.filter(semantic__classification__domain_name__exact = dmain_name)

        if len(reports):
            pass_no = fail_no = 0
            for report in reports:
                semantic = report.semantic
                classification = semantic.classification

                sheet_data[dmain_name][domain_title[0]].append(classification.domain_name)
                sheet_data[dmain_name][domain_title[1]].append(classification.first_classification)
                sheet_data[dmain_name][domain_title[2]].append(classification.second_classification)
                sheet_data[dmain_name][domain_title[3]].append(semantic.name)
                sheet_data[dmain_name][domain_title[4]].append(classification.semantic_property)
                sheet_data[dmain_name][domain_title[5]].append(classification.intent_group)
                sheet_data[dmain_name][domain_title[6]].append(classification.intent)
                sheet_data[dmain_name][domain_title[7]].append(report.result)
                sheet_data[dmain_name][domain_title[8]].append(report.in_handle_time)
                sheet_data[dmain_name][domain_title[9]].append(report.ex_handle_time)
                sheet_data[dmain_name][domain_title[10]].append(report.server_domain)
                sheet_data[dmain_name][domain_title[11]].append(report.description)

                if "pass" == report.result:
                    pass_no += 1
                elif "fail" == report.result:
                    fail_no += 1
            sheet_df = pandas.DataFrame(sheet_data[dmain_name])
            sheet_df.to_excel(excel, sheet_name = dmain_name, index = False, header = False, startrow = 1)

            worksheet = excel.sheets[dmain_name]
            worksheet.set_column(A:C, None, body_format)
            worksheet.set_column(D:D, 18, long_text_format)
            worksheet.set_column(E:E, None, body_format)
            worksheet.set_column(F:G, 30, long_text_format)
            worksheet.set_column(H:H, None, body_format)
            worksheet.set_column(I:K, None, body_format)
            worksheet.set_column(L:L, 50, large_text_format)

            for col, title in enumerate(sheet_df.columns.values):
                worksheet.write(0, col, title, header_format)

            sheet_data.clear()  #回收内存

            summary_dict[summary_title[0]].append(dmain_name)
            summary_dict[summary_title[1]].append(pass_no)
            summary_dict[summary_title[2]].append(fail_no)

    summary_df = pandas.DataFrame(summary_dict)
    summary_df.to_excel(excel, sheet_name = Summary, index = False, header = False, startrow = 1)
    worksheet = excel.sheets[Summary]
    for col, title in enumerate(summary_df.columns.values):
        worksheet.write(0, col, title, header_format)
        for row in range(len(summary_dict[title])):
            worksheet.write(row + 1, col, summary_dict[title][row], body_format)
    excel.save()

    response = HttpResponse(out.getvalue(), content_type = application/vnd.ms-excel)
    dt = datetime.datetime.now()
    response[Content-Disposition] = attachment;filename={} {}.xlsx.format(urlquote(domain_name), dt.strftime(%Y-%m-%d %H-%M-%S))
    print("End downloading...")
    return response

 

 

 

 

 

  

     

    

 

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