324 lines
10 KiB
Python
324 lines
10 KiB
Python
import copy
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import json
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from collections import defaultdict
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from datetime import datetime, timedelta
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from io import BytesIO
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from pathlib import Path
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from typing import Any, Generator, List, TextIO, Tuple, Union
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import pandas as pd
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from flask import current_app
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from reportlab.lib import colors
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from reportlab.lib.enums import TA_CENTER
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from reportlab.lib.styles import getSampleStyleSheet
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from reportlab.lib.units import inch, mm
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from reportlab.pdfbase import pdfmetrics
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from reportlab.pdfbase.ttfonts import TTFont
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from reportlab.platypus import PageBreak, Paragraph, SimpleDocTemplate, Table
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from werkzeug.datastructures import FileStorage
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from ..base.mode import ModeGroups
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from ..examination_schedule.models import TermOfDefence
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from ..students.models import Group, ProjectGradeSheet, Student
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from .exceptions import InvalidNameOrTypeHeaderException
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def check_columns(df: pd.DataFrame) -> bool:
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headers = set(df.keys().values)
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column_names = ["NAZWISKO", "IMIE", "INDEKS", "EMAIL"]
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column_types = ["object", "object", "int", "object"]
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return all((column_name in headers for column_name in column_names)) and all(
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(
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str(df.dtypes[column_name]).startswith(column_type)
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for column_name, column_type in zip(column_names, column_types)
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)
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)
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def parse_csv(
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file: Union[FileStorage, TextIO], year_group_id: int
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) -> Generator[Student, Any, None]:
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df = pd.read_csv(file)
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if not check_columns(df):
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raise InvalidNameOrTypeHeaderException
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students = (
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Student(
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last_name=dict(item.items())["NAZWISKO"],
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first_name=dict(item.items())["IMIE"],
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index=dict(item.items())["INDEKS"],
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email=dict(item.items())["EMAIL"],
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year_group_id=year_group_id,
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)
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for _, item in df.iterrows()
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)
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return students
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def map_project_supervisors(groups: List[Group]) -> dict:
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i = 1
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mapped_project_supervisors = {}
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for group in groups:
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if group.project_supervisor_id not in mapped_project_supervisors.keys():
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mapped_project_supervisors[group.project_supervisor_id] = i
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i += 1
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return mapped_project_supervisors
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def generate_csv(students_and_groups: List[Tuple[Student, Group]]) -> str:
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headers = [
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"INDEKS",
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"IMIE",
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"NAZWISKO",
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"EMAIL",
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"CDYD_KOD",
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"PRZ_KOD",
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"TZAJ_KOD",
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"GR_NR",
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"PRG_KOD",
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]
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mapped_project_supervisors_id = map_project_supervisors(
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[group for _, group in students_and_groups]
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)
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data = [
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(
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student.index,
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student.first_name,
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student.last_name,
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student.email,
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group.cdyd_kod,
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group.prz_kod,
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group.tzaj_kod,
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mapped_project_supervisors_id[group.project_supervisor_id],
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None,
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)
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for student, group in students_and_groups
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]
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dataframe = defaultdict(list)
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for row in data:
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for idx, item in enumerate(row):
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dataframe[headers[idx]].append(item)
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df = pd.DataFrame(dataframe)
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return df.to_csv(index=False)
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def generate_range_dates(
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start_date: datetime, end_date: datetime, step_in_minutes: int
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) -> Generator[Union[datetime, timedelta], Any, None]:
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current_date = copy.copy(start_date)
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while True:
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next_date = current_date + timedelta(minutes=step_in_minutes)
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if next_date > end_date:
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break
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yield current_date
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current_date = copy.copy(next_date)
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def generate_examination_schedule_pdf_file(
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title: str, nested_term_of_defences: List[List[TermOfDefence]], base_dir: Path
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) -> bytes:
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pagesize = (297 * mm, 210 * mm)
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headers = [
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"lp.",
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"Godzina",
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"Nazwa projektu",
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"Opiekun",
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"Zespol",
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"Komisja",
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"Uwagi",
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]
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pdf_buffer = BytesIO()
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my_doc = SimpleDocTemplate(
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pdf_buffer,
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pagesize=pagesize,
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topMargin=1 * inch,
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leftMargin=1 * inch,
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rightMargin=1 * inch,
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bottomMargin=1 * inch,
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title=title,
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)
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pdfmetrics.registerFont(TTFont("Lato", base_dir / "fonts" / "Lato.ttf"))
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style = getSampleStyleSheet()
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bodyText = style["BodyText"]
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bodyText.fontName = "Lato"
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normal = style["Heading1"]
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normal.alignment = TA_CENTER
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flowables = []
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# print(nested_enrollments)
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for term_of_defences in nested_term_of_defences:
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if len(term_of_defences) == 0:
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continue
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date = datetime.strftime(term_of_defences[0].start_date.date(), "%d.%m.%Y")
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paragraph_1 = Paragraph(f"{title} ~ {date}", normal)
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flowables.append(paragraph_1)
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data = [headers]
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for idx, td in enumerate(term_of_defences, start=1):
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new_date = td.start_date + timedelta(hours=2)
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group_name = td.group.name if td.group is not None else ""
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if group_name != "":
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ps = td.group.project_supervisor
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project_supervisor_fullname = f"{ps.first_name[0]}. {ps.last_name}"
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students = td.group.students
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team = ", ".join([f"{s.first_name} {s.last_name}" for s in students])
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else:
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project_supervisor_fullname = ""
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team = ""
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members = td.members_of_committee
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if len(members) == 0:
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committee = ""
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else:
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members_iter = (f"{m.first_name[0]}. {m.last_name}" for m in members)
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committee = ", ".join(members_iter)
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data.append(
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[
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str(idx),
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new_date.strftime("%H:%M"),
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Paragraph(group_name, bodyText),
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Paragraph(project_supervisor_fullname, bodyText),
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Paragraph(team, bodyText),
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Paragraph(committee, bodyText),
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]
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)
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# print(data)
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table = Table(
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data=data,
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style=[
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("GRID", (0, 0), (-1, -1), 0.5, colors.black),
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("BACKGROUND", (0, 0), (-1, 0), colors.HexColor("#A6F1A6")),
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("BACKGROUND", (0, 0), (1, -1), colors.HexColor("#A6F1A6")),
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],
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colWidths=[
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0.25 * inch,
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0.7 * inch,
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1.6 * inch,
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1.5 * inch,
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2.5 * inch,
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2.2 * inch,
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2 * inch,
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],
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)
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flowables.append(table)
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flowables.append(PageBreak())
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my_doc.build(flowables)
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pdf_value = pdf_buffer.getvalue()
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pdf_buffer.close()
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return pdf_value
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def get_duration_time(mode: str) -> int:
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duration_time = None
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if mode == ModeGroups.NON_STATIONARY.value:
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duration_time = 20
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elif mode in [
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ModeGroups.STATIONARY.value,
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ModeGroups.ENGLISH_SPEAKING_STATIONARY.value,
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]:
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duration_time = 30
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return duration_time
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def load_weight_for_project_grade_sheet() -> Union[dict, None]:
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base_dir = current_app.config.get("BASE_DIR")
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config_dir = base_dir / "config"
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with open(config_dir / "weights_project_grade_sheet.json") as f:
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data = json.load(f)
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return data
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def get_criterion_by_weight_key(weight_key: str) -> str:
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if weight_key.startswith("presentation"):
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return "presentation"
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if weight_key.startswith("documentation"):
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return "documentation"
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if weight_key.startswith("group_work"):
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return "group_work"
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return "product_project"
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def grade_in_percentage(term_key: str, term_points: dict) -> str:
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try:
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criterions = {
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"presentation": current_app.config.get(f"PRESENTATION_WEIGHT_{term_key}"),
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"group_work": current_app.config.get(f"GROUP_WORK_WEIGHT_{term_key}"),
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"documentation": current_app.config.get(f"DOCUMENTATION_WEIGHT_{term_key}"),
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"product_project": current_app.config.get(
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f"PRODUCT_PROJECT_WEIGHT_{term_key}"
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),
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}
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result = 0
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for criterion_key, criterion_weight in criterions.items():
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result += (
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term_points[criterion_key]["gained_points"]
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/ term_points[criterion_key]["all_points"]
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* criterion_weight
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)
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result /= sum(criterions.values())
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except ZeroDivisionError:
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result = 0
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return result
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def calculate_points_for_both_terms(
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weights: dict, project_grade_sheets: List[ProjectGradeSheet]
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) -> list:
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terms = []
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for pgs in project_grade_sheets:
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if pgs is None:
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terms.append((0, 0))
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continue
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first_term_points = {
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"presentation": {"gained_points": 0, "all_points": 0},
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"documentation": {"gained_points": 0, "all_points": 0},
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"group_work": {"gained_points": 0, "all_points": 0},
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"product_project": {"gained_points": 0, "all_points": 0},
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}
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second_term_points = copy.deepcopy(first_term_points)
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for weight_key, weight_value in weights.items():
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points = (
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first_term_points if weight_key.endswith("1") else second_term_points
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)
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criterion = get_criterion_by_weight_key(weight_key)
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try:
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attribute_value = getattr(pgs, weight_key)
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except AttributeError:
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attribute_value = 0
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points[criterion]["gained_points"] += attribute_value / 4 * weight_value
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points[criterion]["all_points"] += weight_value
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points_1 = round(grade_in_percentage("FIRST_TERM", first_term_points) * 100, 1)
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points_2 = round(
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grade_in_percentage("SECOND_TERM", second_term_points) * 100, 1
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)
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terms.append((points_1, points_2))
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return terms
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def attach_points_for_first_and_second_term_to_group_models(items: List[Group]) -> None:
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weights = load_weight_for_project_grade_sheet()
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pgs = []
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for g in items:
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if len(g.project_grade_sheet) == 0:
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pgs.append(None)
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else:
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pgs.append(g.project_grade_sheet[0])
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calculated_points = calculate_points_for_both_terms(weights, pgs)
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for group, points in zip(items, calculated_points):
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group.points_for_first_term = points[0]
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group.points_for_second_term = points[1]
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