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f05ee8709f
7 changed files with 234 additions and 0 deletions
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5debian/changelog
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17debian/control
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6debian/copyright
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2debian/klette.install
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4debian/rules
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1debian/source/format
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199main.py
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klette (0.1) UNRELEASED; urgency=low |
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* Initial release. |
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-- Adrian Heine <debian@adrianheine.de> Mon, 08 Apr 2024 11:29:30 +0200 |
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Source: klette |
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Section: education |
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Priority: optional |
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Maintainer: Adrian Heine <debian@adrianheine.de> |
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Build-Depends: debhelper-compat (= 13), dh-python, python3-all, dh-exec |
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Standards-Version: 4.6.2 |
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Homepage: https://git.adrianheine.de/adrian/klette |
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Rules-Requires-Root: no |
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Vcs-Git: https://git.adrianheine.de/adrian/klette.git |
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Vcs-Browser: https://git.adrianheine.de/adrian/klette |
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X-Python3-Version: >= 3.10 |
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Package: klette |
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Architecture: all |
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Multi-Arch: foreign |
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Depends: ${misc:Depends}, ${python3:Depends}, python3-pyamf |
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Description: Replacement for klett's flash-based vocabulary trainer |
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Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/ |
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Upstream-Name: klette |
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Files: * |
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Copyright: 2024 Adrian Heine |
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License: AGPL-3.0+ |
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#!/usr/bin/dh-exec |
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main.py => /usr/bin/klette |
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#!/usr/bin/make -f |
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%: |
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dh $@ --with python3 |
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3.0 (native) |
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#!/usr/bin/python3 |
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import pyamf |
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import shutil |
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import json |
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import os |
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import argparse |
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import unicodedata |
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import random |
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import re |
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import sys |
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import readline |
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|
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DATA_DIR = os.environ['XDG_DATA_HOME'] + '/klette' |
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VOKABELN_FILE = DATA_DIR + '/vokabeln.json' |
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STATUS_FILE = DATA_DIR + '/status.json' |
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AUDIO_BASE = DATA_DIR + '/audio/' |
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|
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class bcolors: |
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HEADER = '\033[95m' |
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OKBLUE = '\033[94m' |
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OKCYAN = '\033[96m' |
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OKGREEN = '\033[92m' |
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WARNING = '\033[93m' |
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FAIL = '\033[91m' |
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ENDC = '\033[0m' |
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BOLD = '\033[1m' |
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UNDERLINE = '\033[4m' |
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LINK_START = '\033]8;;' |
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LINK_MIDDLE = '\033\\' |
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LINK_END = '\033]8;;\033\\' |
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|
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def import_vokabeln(file_name, audio_base): |
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os.makedirs(AUDIO_BASE, exist_ok=True) |
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palabras = [] |
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with open(file_name, 'rb') as reader: |
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obj = pyamf.decode(reader.read()) |
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for unidad_data in obj.readElement()['lektionList']: |
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unidad = unidad_data['name'] |
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for paso_data in unidad_data['lektionsTeilList']: |
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paso = paso_data['name'] |
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for palabra in paso_data['entryList']: |
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audio = palabra['vorderSeite']['swTonAbgleichwort'] |
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palabras.append({ |
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'id': palabra['matId'], |
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'de': palabra['rueckSeite']['text'], |
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'es': palabra['vorderSeite']['text'], |
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'audio': audio, |
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'unidad': unidad, |
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'paso': paso |
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}) |
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shutil.copy2(audio_base + audio + '.bin', |
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AUDIO_BASE + audio + '.aac') |
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with open(VOKABELN_FILE, 'x') as writer: |
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writer.write(json.dumps(palabras)) |
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def import_status(file_name): |
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os.makedirs(DATA_DIR, exist_ok=True) |
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statuses = {} |
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with open(file_name, 'rb') as reader: |
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obj = pyamf.decode(reader.read()).readElement()[0] |
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for idx in obj: |
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item = obj[idx] |
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statuses[item['matId']] = item['statusWortschatz'] |
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with open(STATUS_FILE, 'x') as writer: |
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writer.write(json.dumps(statuses)) |
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def vergleiche(respuesta, expecta): |
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if respuesta == "": return 4 |
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if respuesta[0] == '!' and expecta[0] == '¡': |
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respuesta = '¡' + respuesta[1:] |
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if respuesta[0] == '?' and expecta[0] == '¿': |
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respuesta = '¿' + respuesta[1:] |
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respuesta = unicodedata.normalize('NFD', respuesta) |
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expecta = unicodedata.normalize('NFD', expecta) |
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if respuesta == expecta: return 0 |
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respuesta = respuesta.encode('ASCII', 'ignore').decode('ASCII') |
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expecta = expecta.encode('ASCII', 'ignore').decode('ASCII') |
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if respuesta == expecta: return 1 |
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respuesta = respuesta.casefold() |
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expecta = expecta.casefold() |
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if respuesta == expecta: return 2 |
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respuesta = re.sub('\W', '', respuesta) |
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expecta = re.sub('\W', '', expecta) |
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if respuesta == expecta: return 3 |
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return 4 |
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assert vergleiche("e", "e") == 0 |
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assert vergleiche("é", "e") == 1 |
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assert vergleiche("Bien", "bien") == 2 |
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assert vergleiche("quétal", "Qué tal") == 3 |
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assert vergleiche("Buenas Noches", "¡Buenas noches!") == 3 |
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class Resultado: |
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BIEN = 1 |
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MAL = 2 |
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ADIOS = 3 |
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def einzelne_abfrage(palabra, status): |
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status_text = f"({status})" if status > 0 else f"{bcolors.OKGREEN}neu{bcolors.ENDC}" |
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try: |
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respuesta = input(f"{status_text} {bcolors.BOLD}{palabra['de']}{bcolors.ENDC} {bcolors.OKCYAN}") |
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except EOFError: |
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print() |
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return Resultado.ADIOS |
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finally: |
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print(bcolors.ENDC, end="") |
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print('\033[{}C\033[1A'.format(4 + len(palabra['de']) + 1 + len(respuesta)), end="") |
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resultado = vergleiche(respuesta, palabra['es']) |
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match status: |
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case 0: bien = resultado < 4 |
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case 1: bien = resultado < 3 |
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case 2: bien = resultado < 3 |
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case 3: bien = resultado < 2 |
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case 4: bien = resultado < 1 |
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print(f" {bcolors.LINK_START}file://{AUDIO_BASE}{palabra['audio']}.aac{bcolors.LINK_MIDDLE}",end="") |
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if bien and resultado == 0: |
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print(f"{bcolors.OKGREEN}✓{bcolors.ENDC}",end="") |
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elif bien: |
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print(f"{bcolors.WARNING}{palabra['es']}{bcolors.ENDC}",end="") |
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else: |
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print(f"{bcolors.FAIL}{palabra['es']}{bcolors.ENDC}",end="") |
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print(bcolors.LINK_END,end="") |
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try: |
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input(" ") |
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except EOFError: |
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print() |
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return Resultado.ADIOS |
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return Resultado.BIEN if bien else Resultado.MAL |
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def abfrage(parser): |
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random.seed() |
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try: |
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with open(VOKABELN_FILE, 'r') as f: |
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palabras = json.load(f) |
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with open(STATUS_FILE, 'r') as f: |
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status = json.load(f) |
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except FileNotFoundError: |
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print(f"{bcolors.FAIL}Daten können nicht geladen werden, hast du sie schon importiert?{bcolors.ENDC}") |
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print() |
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parser.print_help() |
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return |
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unidad = False |
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paso = False |
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cur_palabras = False |
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bien = 0 |
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mal = 0 |
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for palabra in palabras: |
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if paso != palabra['paso']: |
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if cur_palabras != False: |
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c = [len(cur_palabras[x]) for x in cur_palabras] |
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print(f"{bcolors.BOLD}{unidad}{bcolors.ENDC}: {paso} (",end="") |
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print(*c, sep="/", end=")") |
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print() |
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for n in range(5): # 1..4, no 5 |
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random.shuffle(cur_palabras[n]) |
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for palabra in cur_palabras[n]: |
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s = status.get(palabra['id'], 0) |
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match einzelne_abfrage(palabra, s): |
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case Resultado.BIEN: |
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status[palabra['id']] = s + 1 |
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bien+=1 |
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case Resultado.MAL: |
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if s > 0: |
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status[palabra['id']] = s - 1 |
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mal+=1 |
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continue |
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case Resultado.ADIOS: |
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print(f'{bcolors.OKGREEN}+{bien}{bcolors.ENDC} / {bcolors.FAIL}-{mal}{bcolors.ENDC}') |
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return |
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with open(STATUS_FILE + '.new', 'w') as f: |
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json.dump(status, f) |
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f.flush() |
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os.fsync(f.fileno()) |
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with open(STATUS_FILE + '.new', 'r') as f: |
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status = json.load(f) |
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os.replace(STATUS_FILE + '.new', STATUS_FILE) |
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cur_palabras = {0: [], 1: [], 2: [], 3: [], 4: [], 5: []} |
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unidad = palabra['unidad'] |
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paso = palabra['paso'] |
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cur_palabras[status.get(palabra['id'], 0)].append(palabra) |
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parser = argparse.ArgumentParser() |
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default_data_file = os.environ['PWD'] + '/assets/amf/vokabelTrainer147.amf' |
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parser.add_argument('--import-data', type=str, help="Path to assets", metavar="DIR") |
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default_status_file = os.environ['HOME'] + '/klett/1266/vokabeltrainerData147' |
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parser.add_argument('--import-status', type=str, help="Path to AMF File, defaults to " + default_status_file, metavar="FILE", nargs='?', const=default_status_file) |
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args = parser.parse_args() |
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if args.import_data: |
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import_vokabeln(args.import_data + '/amf/vokabelTrainer147.amf', |
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args.import_data + '/amf/medium/') |
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elif args.import_status: |
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import_status(args.import_status) |
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else: |
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abfrage(parser) |
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