mirror of https://github.com/raiots/TasksManager
156 lines
7.3 KiB
Python
156 lines
7.3 KiB
Python
from django.core import serializers
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from django.core.serializers.json import DjangoJSONEncoder
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from django.http import HttpResponse, JsonResponse
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from django.shortcuts import render
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from django.test import TestCase
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# Create your tests here.
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from django.db.models import Sum, F, FloatField, Count, Q
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from django.utils import timezone
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from django.views import View
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from apps.users.models import User
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from apps.tasks.models import Todo
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import pandas as pd
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from collections import defaultdict, Counter
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from copy import deepcopy
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class TestView(View):
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def get(self, request, year=2021, month=7):
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# sub_credit = User.objects.filter(department=request.user.department).annotate(
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# pre_credit=Sum(
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# (F('sub_executor__predict_work') * (1 - F('sub_executor__evaluate_factor')) / F(
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# 'sub_executor__sub_executor_count')
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# ),
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# filter=Q(sub_executor__deadline__year=year, sub_executor__deadline__month=month),
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# output_field=FloatField()
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# ),
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# real_credit=Sum(
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# (F('sub_executor__real_work') * (1 - F('sub_executor__evaluate_factor')) / F(
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# 'sub_executor__sub_executor_count')
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# ),
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# filter=Q(sub_executor__deadline__year=year, sub_executor__deadline__month=month),
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# output_field=FloatField()
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# )
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# ).values('id', 'real_name', 'pre_credit', 'real_credit')
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# sub_credit = [entry for entry in sub_credit]
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# 建立username和真实姓名的对应字典，并在工作量计算完成后插入结果集
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user_info = User.objects.filter(department=request.user.department)\
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.values_list('username', 'real_name')
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user_name = {}
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for user in user_info:
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user_name[user[0]] = user[1]
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# print(user_name)
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# 以用户表查询，按用户列出所参与承办、协办任务，并在之后按用户名分组合并。
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main_credit = User.objects.filter(department=request.user.department)\
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.annotate(main_count=Count('main_executor'))\
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.order_by('username')\
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.values('username', 'main_executor', 'main_executor__predict_work', 'main_executor__real_work',
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'main_executor__evaluate_factor', 'main_count') # 这里的annotate不知会不会有问题
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sub_count = Todo.objects.filter(sub_executor__department=request.user.department) \
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.annotate(sub_count=Count('sub_executor')).values('id', 'sub_count')
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sub_credit = User.objects.filter(department=request.user.department) \
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.order_by('username') \
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.values('username', 'real_name', 'sub_executor', 'sub_executor__predict_work', 'sub_executor__real_work',
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'sub_executor__evaluate_factor')
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# 构建工作包id对应协办人人数的字典
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sub_exe_count = {}
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for i in sub_count:
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key = i['id']
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value = i['sub_count']
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sub_exe_count[key] = value
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# print(sub_exe_count)
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# 计算每个承办任务的预计、实际工作量，并插入字典
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for i in main_credit:
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i['main_pre_cal'] = i['main_executor__predict_work'] * i['main_executor__evaluate_factor']
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i['main_real_cal'] = i['main_executor__real_work'] * i['main_executor__evaluate_factor']
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# print(i)
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# print(str(i['sub_executor']))
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# 将协办任务对应的人数插入，计算每个协办任务的预计、实际工作量，并插入字典
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for i in sub_credit:
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sub_todo_id = i['sub_executor']
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i['sub_exe_count'] = sub_exe_count[sub_todo_id]
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i['sub_pre_cal'] = i['sub_executor__predict_work'] * (1 - i['sub_executor__evaluate_factor']) / i['sub_exe_count']
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i['sub_real_cal'] = i['sub_executor__real_work'] * (1 - i['sub_executor__evaluate_factor']) / i['sub_exe_count']
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i['sub_count'] = 1 # 用于帮助累加程序计算每个用户的协办任务数量， sub_exe_count会返回此协办任务的协办人数，在累加时导致计算错误
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# print(i)
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# print(str(i['sub_executor']))
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# 用于按用户名合并任务，会对指定字段进行累加，类似GROUP BY(SUM)，但会丢失无需计算的部分，因此之前需要单独构建姓名字典
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def solve(dataset, group_by_key, sum_value_keys):
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dic = defaultdict(Counter)
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for item in dataset:
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key = item[group_by_key]
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vals = {k: item[k] for k in sum_value_keys}
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dic[key].update(vals)
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return dic
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main_credit = solve(main_credit, 'username', ['main_pre_cal', 'main_real_cal', 'main_count'])
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main_credit = dict(main_credit)
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sub_credit = solve(sub_credit, 'username', ['sub_pre_cal', 'sub_real_cal', 'sub_count'])
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sub_credit = dict(sub_credit)
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total_credit = deepcopy(main_credit)
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# 按用户名合并承办与协办任务字典
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for key in sub_credit.keys():
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if key in total_credit:
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total_credit[key].update(sub_credit[key])
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else:
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total_credit[key] = sub_credit[key]
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# print(total_credit['admin']['sub_pre_cal'])
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# 根据字典内容，计算总工作量
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for key, value in total_credit.items():
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# print(value)
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value['pre_cal'] = value['sub_pre_cal'] + value['main_pre_cal']
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value['real_cal'] = value['sub_real_cal'] + value['main_real_cal']
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value['real_name'] = user_name[key]
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# total_credit = dict(main_credit.items() + sub_credit.items())
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# for value in sub_credit.values():
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# dict(value)
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# print(sub_credit)
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#
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# new_pair = {}
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# for doc, tab in sub_credit.items():
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# new_pair[doc] = {}
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# for word, freq in tab.items():
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# new_pair[doc][word] = freq
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# print(new_pair)
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# return HttpResponse(str(main_credit)+str(sub_credit))
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current_user = total_credit[request.user.username]
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print(current_user)
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# 累加该部门各个用户的工作量，计算部门工作量
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department_cal = {}
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temp_pre = []
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depart_pre, depart_real, depart_count = 0, 0, 0
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for username, value in total_credit.items():
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print(username)
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print(value['pre_cal'])
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depart_pre = depart_pre + value['pre_cal']
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depart_real = depart_real + value['real_cal']
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depart_count = depart_count + value['main_count']
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temp_pre.append(value['pre_cal'])
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department_cal['pre_cal'] = depart_pre
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department_cal['real_cal'] = depart_real
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department_cal['depart_count'] = depart_count
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department_cal['pre_avg'] = department_cal['pre_cal'] / len(total_credit)
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department_cal['real_avg'] = department_cal['real_cal'] / len(total_credit)
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# 为页面提供日期信息
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date = str(year) + '年' + str(month) + '月'
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# return HttpResponse(str(total_credit) + '\n' + str(department_cal))
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context = {'date': date, 'users_data': total_credit, 'department_cal': department_cal,
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'current_user': current_user}
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return render(request, 'tasks/index.html', context)
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