from io import BytesIO
from flask import Flask, render_template
# app = Flask("Project Numeri")
from flask import Flask, make_response, request
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
import base64

app = Flask(__name__)

def plot():
    # Generate the figure **without using pyplot**.
    fig = Figure()
    ax = fig.subplots()
    ax.plot([1, 2])
    # Save it to a temporary buffer.
    buf = BytesIO()
    fig.savefig(buf, format="png")
    # Embed the result in the html output.
    data = base64.b64encode(buf.getbuffer()).decode("ascii")
    return f"<img src='data:image/png;base64,{data}'/>"


# import pandas as pd
# import numpy as np

# GRADE_LIST = "Cijfers-HerrewijnenJonathan.csv"

# class Cijferlijst:
#     def __init__(self, grade_list=GRADE_LIST):
#         self.grade_list = grade_list
#         self.ps = pd.read_csv(GRADE_LIST, skiprows=2, sep=';')

#     '''
#     Get all data from a subject and a (yearly) period:
#     GetSubjectByYear("godsdienst", "2010/2011")
#     '''
#     def GetSubjectByYear(self, subject, year):
#         if(type(subject) == str and type(year) == str):
#             select_year = self.ps[self.ps['Schooljaar(Voortgangsdossier)'] == year] 
#             select_subject =  select_year[select_year["Vak(Voortgangsdossier)"] == subject]

#             #filter period and rapport
#             rapports =  select_subject[select_subject['Cijfertype(Voortgangsdossier)'] != "Periodegemiddelde"]
#             return rapports[rapports ['Cijfertype(Voortgangsdossier)'] != "Rapportcijfer"]
#         else:
#             return False

            
#     def iets(self):
#         print(self.grade_list)
    
#     def CalculateMedian(self, subject, year):
#         # Calculates average for all scores without weight!
#         Grades = self.ps['Cijfer(Voortgangsdossier)'].loc[:]