Python/Django 批量下载Excel

一、前提

　　项目上需求的变更总是时时发生的，应对需求的我们，也只能变更我们代码，所以、继前两篇之后，我们的批量下载诞生了

二、安装

　　本文使用zipstream库进行压缩，安装方式：pip install zipstream

　　生成Excel方式与前一篇博文一致，这里只是为了讲解下批量下载，需要将多个Excel文件保存，并压缩至一个ZIP文件中即可，所以、关于如何生成Excel文件，本文不再额外介绍，请参考下面的的源码，自行学习。

三、使用

　　zipstream使用比较简单，这里直接贴出代码：

　　

# coding: UTF-8
import os
import zipstream

from web.settings import DOWNLOAD_URL

class ZipFile:

    def __init__(self):
        self.folder = DOWNLOAD_URL
        for filename in os.listdir(self.folder):
            file = self.folder + os.sep + filename
            if os.path.exists(file):
                os.remove(file)
                print('Remove such file:%s' % file)
            else:
                print('No such file:%s' % file)
        self.zipfile = zipstream.ZipFile(mode = 'w', compression = zipstream.ZIP_DEFLATED)

    def zip_file(self, file, name):
        if os.path.isfile(file):
            arcname = os.path.basename(file)
            self.zipfile.write(file, arcname = arcname)
        else:
            self.zip_folder(file, name)

    def zip_folder(self, folder, name = 'downloads'):
        for file in os.listdir(folder):
            full_path = os.path.join(folder, file)
            if os.path.isfile(full_path):
                self.zipfile.write(full_path, arcname = os.path.join(name, os.path.basename(full_path)))
            elif os.path.isdir(full_path):
                self.zip_folder(full_path, os.path.join(name, os.path.basename(full_path)))

    def close(self):
        if self.zipfile:
            self.zipfile.close()

四、保存下载

　　

    excel.save()

    dt = datetime.datetime.now()
    ecarxzip.zip_folder(DOWNLOAD_URL)
    response = StreamingHttpResponse(ecarxzip.zipfile, content_type = 'application/zip')
    response['Content-Disposition'] = 'attachment;filename={} {}.zip'.format("Batch report", dt.strftime(' %Y-%m-%d %H-%M-%S'))
    print("end batch downloading...")
    return response

贴下源码：

def batch_download(request, task_id):
    print("batch start downloading...", task_id)

    ai_task = AITask.objects.get(id = task_id)
    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")
    else:
        domains = {}

    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']

    sheet_data = {}
    ecarxzip = ZipFile()  #保存Excel文档前，清空downloads文件夹
    for domain in domains:
        domain_name = domain["domain_name"]
        reports = ai_task.report.filter(semantic__classification__domain_name__exact = domain_name)

        if len(reports):
            pass_no = fail_no = 0
            for report in reports:
                semantic = report.semantic
                classification = semantic.classification
                sheet_name = classification.third_classification_Number if classification.third_classification_Number else domain_name
                if sheet_name not in sheet_data:
                    sheet_data[sheet_name] = {title: [] for title in domain_title}

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

                if "pass" == report.result:
                    pass_no += 1
                elif "fail" == report.result:
                    fail_no += 1

            excel = pandas.ExcelWriter('{}/{}.xlsx'.format(DOWNLOAD_URL, domain_name), engine = 'xlsxwriter')
            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)

            summary_data = [domain_name, pass_no, fail_no]
            summary_df = pandas.DataFrame({})
            summary_df.to_excel(excel, sheet_name = "Summary", index = False, header = False)
            worksheet = excel.sheets['Summary']
            for index in range(len(summary_title)):
                worksheet.write(0, index, summary_title[index], header_format)
                worksheet.write(1, index, summary_data[index], body_format)

            order_sheet = []
            for sheet in sheet_data:
                order_sheet.append(sheet)

            order_sheet.sort(key = lambda param: ''.join([no.rjust(2, '') for no in param.split('.')]))
            for sheet in order_sheet:
                sheet_df = pandas.DataFrame(sheet_data[sheet])
                sheet_df.to_excel(excel, sheet_name = sheet, index = False, header = False, startrow = 1)

                worksheet = excel.sheets[sheet]
                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)

            excel.save()
            sheet_data.clear()  #回收内存

            summary_dict['Domain'].append(domain_name)
            summary_dict['Pass'].append(pass_no)
            summary_dict['Fail'].append(fail_no)

    excel = pandas.ExcelWriter('{}/Summary.xlsx'.format(DOWNLOAD_URL), engine = 'xlsxwriter')

    summary_df = pandas.DataFrame({})
    summary_df.to_excel(excel, sheet_name = 'Summary', index = False, startrow = 1)

    workbook = excel.book
    body_format = workbook.add_format(style.body_style)
    header_format = workbook.add_format(style.head_style)

    worksheet = excel.sheets['Summary']
    for col in range(len(summary_title)):
        title = summary_title[col]
        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()

    dt = datetime.datetime.now()
    ecarxzip.zip_folder(DOWNLOAD_URL)
    response = StreamingHttpResponse(ecarxzip.zipfile, content_type = 'application/zip')
    response['Content-Disposition'] = 'attachment;filename={} {}.zip'.format("Batch report", dt.strftime(' %Y-%m-%d %H-%M-%S'))
    print("end batch downloading...")
    return response