pandas'to_html`是否会降低Django中页面的速度？

Question

我正在使用JSON和request库获取ExchangeRates API的JSON，使用Pandas读取SCV并转换表，在前端页面中呈现HTML，使用Forex转换速率

我注意到页面仅在45秒后加载，我认为问题在于CSV文件和to_html()的转换。我有6张巴西的桌子，5张新西兰的桌子和7张乌拉圭的桌子，总共18张桌子

有没有办法加快CSV和表格的速度

from django.shortcuts import get_object_or_404, render
from django.views import View
from forex_python.converter import CurrencyRates
from pathlib import Path

import json
import requests
from pandas.io.parsers import read_csv

class financial_planning(Mixin, View):
  def get(self, request, id = None, *args, **kwargs):
    template = "pages/financial-planning.html"
    context = {
      'title': "Planejamentos financeiros",
      'brazil_bills': self.brazil_bills(),
      'nz_bills': self.nz_bills(),
      'uy_bills': self.uy_bills(),
    }
    return render(request, template, context)

  def uruguayan_currency_conversion(self):
    url = 'https://v6.exchangerate-api.com/v6/YYYYEEESSS/latest/UYU'
    
    response = requests.get(url)
    data = response.json()
    
    return data

  def brazil_bills(self):
    cc = CurrencyRates()
    
    cad = cc.convert('BRL', 'CAD', 1)
    nzd = cc.convert('BRL', 'NZD', 1)
    usd = cc.convert('BRL', 'USD', 1)
    
    base_path = Path(__file__).parent
    file_path = (base_path / "static/data/brazil/bills.csv").resolve()
    c = pd.read_csv(file_path)
    c.loc["Total"] = c.sum()
    c["Item"].values[-1] = "Total"
    
    c["USD"] = (c['Price (BRL)'] * usd).round().astype(int)
    c["CAD"] = (c['Price (BRL)'] * cad).round().astype(int)
    c["NZD"] = (c['Price (BRL)'] * nzd).round().astype(int)
    
    html_table = c.to_html(classes = 'bills', index = False)
    
    return html_table

  def nz_bills(self):
    
    cc = CurrencyRates()
    
    brl = cc.convert('NZD', 'BRL', 1)
    cad = cc.convert('NZD', 'CAD', 1)
    usd = cc.convert('NZD', 'USD', 1)
    
    base_path = Path(__file__).parent
    file_path = (base_path / "static/data/nz/bills.csv").resolve()
    c = pd.read_csv(file_path)
    c.loc["Total"] = c.sum()
    c["Item"].values[-1] = "Total"
    
    c["BRL"] = (c['Price (NZD)'] * brl).round().astype(int)
    c["CAD"] = (c['Price (NZD)'] * cad).round().astype(int)
    c["USD"] = (c['Price (NZD)'] * usd).round().astype(int)
    
    html_table = c.to_html(classes = 'bills', index = False)
    
    return html_table

  def uy_bills(self):
    
    data = self.uruguayan_currency_conversion()
    
    base_path = Path(__file__).parent
    file_path = (base_path / "static/data/uruguay/bills.csv").resolve()
    c = pd.read_csv(file_path)
    c.loc["Total"] = c.sum()
    c["Item"].values[-1] = "Total"
    
    c["BRL"] = (data['conversion_rates']['BRL'] * c['Price (UYU)']).round().astype(int)
    c["CAD"] = (data['conversion_rates']['CAD'] * c['Price (UYU)']).round().astype(int)
    c["NZD"] = (data['conversion_rates']['NZD'] * c['Price (UYU)']).round().astype(int)
    c["USD"] = (data['conversion_rates']['USD'] * c['Price (UYU)']).round().astype(int)
    
    html_table = c.to_html(classes = 'bills', index = False)
    
    return html_table

如果要查看完整的views.py，可以选中here