基于 Python Django 的电影市场预测分析系统数据可视化

（6）用户数据管理

左侧设含首页、电影分析等入口的导航栏，页面主体有搜索框可查询用户，以列表展示用户的 ID、姓名等信息，同时支持新增用户，以及对现有用户进行修改、删除操作，还配备分页功能，实现用户信息的管理、查询与操作处理。

（7）首页

左侧设包含电影分析、票房预测等功能入口的导航栏，页面主体展示欢迎提示与可视化背景，作为系统的入口页面，可引导用户通过左侧导航栏进入各功能模块，实现系统功能的快速访问与跳转。

（8）注册登录

页面展示用户登录表单，包含用户名、密码输入框与登录按钮，支持用户输入账号信息并提交登录操作，实现系统的身份验证与权限准入功能，是进入系统各模块的前置验证入口。

3、核心代码

import datetime
from django.http import HttpResponseRedirect, HttpResponse, HttpResponseForbidden, JsonResponse
from django.shortcuts import render
from user.models import User
import os
import csv

work_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))

def login(req):
    """ 跳转登录 :param req: :return: """
    return render(req, 'login.html')

def register(req):
    """ 跳转注册 :param req: :return: """
    return render(req, 'register.html')

def index(req):
    """ 跳转首页 :param req: :return: """
    username = req.session['username']
    total_user = len(User.objects.all())
    date = datetime.datetime.today()
    month = date.month
    year = date.year
    return render(req, 'index.html', locals())

def index2(req):
    """ 跳转首页 :param req: :return: """
    username = req.session['username']
    total_user = len(User.objects.all())
    date = datetime.datetime.today()
    month = date.month
    year = date.year
    return render(req, 'welcome_index.html', locals())

def login_out(req):
    """ 注销登录 :param req: :return: """
    del req.session['username']
    return HttpResponseRedirect('http://127.0.0.1:8000/')

def personal(req):
    username = req.session['username']
    role_id = req.session['role']
    user = User.objects.filter(name=username).first()
    return render(req, 'personal.html', locals())

def zydy(request):
    username = request.session['username']
    return render(request, 'zydyfx.html', locals())

def pffx(request):
    username = request.session['username']
    return render(request, 'pffx.html', locals())

def dysj(request):
    username = request.session['username']
    return render(request, 'dysj.html', locals())

def get_data(request):
    keyword = request.GET.get('name')
    page = int(request.GET.get("page", ''))
    limit = request.GET.get("limit", '')
    response_data = {}
    response_data['code'] = 0
    response_data['msg'] = ''
    data = []
    with open(os.path.join(work_dir, 'movie/data/recentlyMovies.csv'), 'r') as csv_file:
        csv_reader = csv.reader(csv_file)
        for arrTxt in csv_reader:
            dict_values = {
                'id': arrTxt[0], 'name': arrTxt[1], 'pf': arrTxt[2], 'sj': arrTxt[3],
                'dqcc': arrTxt[4], 'dqrc': arrTxt[5], 'pfzb': arrTxt[7], 'ljsyts': arrTxt[8],
                'tpp': arrTxt[10], 'my': arrTxt[11], 'db': arrTxt[12]
            }
            data.append(dict_values)
    if page == 1:
        results = data[1:11]
    elif page == 2:
        results = data[11:21]
    elif page == 3:
        results = data[21:31]
    elif page == 4:
        results = data[31:41]
    elif page == 5:
        results = data[41:51]
    elif page == 6:
        results = data[51:61]
    elif page == 7:
        results = data[61:71]
    response_data['count'] = len(data)
    response_data['data'] = results
    return JsonResponse(response_data)

def update_data(request):
    from movie.getData import recently
    recently()
    return JsonResponse({'msg': 'ok'})

def pfyc(request):
    data = []
    value = []
    with open(os.path.join(work_dir, 'movie/data/predict_result.csv'), 'r') as csv_file:
        csv_reader = csv.reader(csv_file)
        for arrTxt in csv_reader:
            data.append(arrTxt[0])
            value.append(arrTxt[1])
    data = data[1:]
    value = value[1:]
    print(data)
    print(value)
    return render(request, 'pfyc.html', locals())