Init

debian/changelog

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+klette (0.1) UNRELEASED; urgency=low
+
+  * Initial release.
+
+ -- Adrian Heine <debian@adrianheine.de>  Mon, 08 Apr 2024 11:29:30 +0200

debian/control

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+Source: klette
+Section: education
+Priority: optional
+Maintainer: Adrian Heine <debian@adrianheine.de>
+Build-Depends: debhelper-compat (= 13), dh-python, python3-all, dh-exec
+Standards-Version: 4.6.2
+Homepage: https://git.adrianheine.de/adrian/klette
+Rules-Requires-Root: no
+Vcs-Git: https://git.adrianheine.de/adrian/klette.git
+Vcs-Browser: https://git.adrianheine.de/adrian/klette
+X-Python3-Version: >= 3.10
+
+Package: klette
+Architecture: all
+Multi-Arch: foreign
+Depends: ${misc:Depends}, ${python3:Depends}, python3-pyamf
+Description: Replacement for klett's flash-based vocabulary trainer

debian/copyright

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+Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
+Upstream-Name: klette
+
+Files:     *
+Copyright: 2024 Adrian Heine
+License:   AGPL-3.0+

debian/klette.install

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+#!/usr/bin/dh-exec
+main.py => /usr/bin/klette

debian/rules

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+#!/usr/bin/make -f
+
+%:
+	dh $@ --with python3

debian/source/format

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+3.0 (native)

main.py

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+#!/usr/bin/python3
+
+import pyamf
+import shutil
+import json
+import os
+import argparse
+import unicodedata
+import random
+import re
+import sys
+import readline
+
+DATA_DIR = os.environ['XDG_DATA_HOME'] + '/klette'
+VOKABELN_FILE = DATA_DIR + '/vokabeln.json'
+STATUS_FILE = DATA_DIR + '/status.json'
+AUDIO_BASE = DATA_DIR + '/audio/'
+
+class bcolors:
+    HEADER = '\033[95m'
+    OKBLUE = '\033[94m'
+    OKCYAN = '\033[96m'
+    OKGREEN = '\033[92m'
+    WARNING = '\033[93m'
+    FAIL = '\033[91m'
+    ENDC = '\033[0m'
+    BOLD = '\033[1m'
+    UNDERLINE = '\033[4m'
+    LINK_START = '\033]8;;'
+    LINK_MIDDLE = '\033\\'
+    LINK_END = '\033]8;;\033\\'
+
+def import_vokabeln(file_name, audio_base):
+    os.makedirs(AUDIO_BASE, exist_ok=True)
+    palabras = []
+    with open(file_name, 'rb') as reader:
+        obj = pyamf.decode(reader.read())
+        for unidad_data in obj.readElement()['lektionList']:
+            unidad = unidad_data['name']
+            for paso_data in unidad_data['lektionsTeilList']:
+                paso = paso_data['name']
+                for palabra in paso_data['entryList']:
+                    audio = palabra['vorderSeite']['swTonAbgleichwort']
+                    palabras.append({
+                            'id': palabra['matId'],
+                            'de': palabra['rueckSeite']['text'],
+                            'es': palabra['vorderSeite']['text'],
+                            'audio': audio,
+                            'unidad': unidad,
+                            'paso': paso
+                    })
+                    shutil.copy2(audio_base + audio + '.bin',
+                                 AUDIO_BASE + audio + '.aac')
+    with open(VOKABELN_FILE, 'x') as writer:
+        writer.write(json.dumps(palabras))
+
+def import_status(file_name):
+    os.makedirs(DATA_DIR, exist_ok=True)
+    statuses = {}
+    with open(file_name, 'rb') as reader:
+        obj = pyamf.decode(reader.read()).readElement()[0]
+        for idx in obj:
+            item = obj[idx]
+            statuses[item['matId']] = item['statusWortschatz']
+    with open(STATUS_FILE, 'x') as writer:
+        writer.write(json.dumps(statuses))
+
+def vergleiche(respuesta, expecta):
+    if respuesta == "": return 4
+    if respuesta[0] == '!' and expecta[0] == '¡':
+        respuesta = '¡' + respuesta[1:]
+    if respuesta[0] == '?' and expecta[0] == '¿':
+        respuesta = '¿' + respuesta[1:]
+    respuesta = unicodedata.normalize('NFD', respuesta)
+    expecta = unicodedata.normalize('NFD', expecta)
+    if respuesta == expecta: return 0
+    respuesta = respuesta.encode('ASCII', 'ignore').decode('ASCII')
+    expecta = expecta.encode('ASCII', 'ignore').decode('ASCII')
+    if respuesta == expecta: return 1
+    respuesta = respuesta.casefold()
+    expecta = expecta.casefold()
+    if respuesta == expecta: return 2
+    respuesta = re.sub('\W', '', respuesta)
+    expecta = re.sub('\W', '', expecta)
+    if respuesta == expecta: return 3
+    return 4
+
+assert vergleiche("e", "e") == 0
+assert vergleiche("é", "e") == 1
+assert vergleiche("Bien", "bien") == 2
+assert vergleiche("quétal", "Qué tal") == 3
+assert vergleiche("Buenas Noches", "¡Buenas noches!") == 3
+
+class Resultado:
+    BIEN = 1
+    MAL = 2
+    ADIOS = 3
+
+def einzelne_abfrage(palabra, status):
+    status_text = f"({status})" if status > 0 else f"{bcolors.OKGREEN}neu{bcolors.ENDC}"
+    try:
+        respuesta = input(f"{status_text} {bcolors.BOLD}{palabra['de']}{bcolors.ENDC} {bcolors.OKCYAN}")
+    except EOFError:
+        print()
+        return Resultado.ADIOS
+    finally:
+        print(bcolors.ENDC, end="")
+    print('\033[{}C\033[1A'.format(4 + len(palabra['de']) + 1 + len(respuesta)), end="")
+    resultado = vergleiche(respuesta, palabra['es'])
+    match status:
+        case 0: bien = resultado < 4
+        case 1: bien = resultado < 3
+        case 2: bien = resultado < 3
+        case 3: bien = resultado < 2
+        case 4: bien = resultado < 1
+    print(f" {bcolors.LINK_START}file://{AUDIO_BASE}{palabra['audio']}.aac{bcolors.LINK_MIDDLE}",end="")
+    if bien and resultado == 0:
+        print(f"{bcolors.OKGREEN}✓{bcolors.ENDC}",end="")
+    elif bien:
+        print(f"{bcolors.WARNING}{palabra['es']}{bcolors.ENDC}",end="")
+    else:
+        print(f"{bcolors.FAIL}{palabra['es']}{bcolors.ENDC}",end="")
+    print(bcolors.LINK_END,end="")
+    try:
+        input(" ")
+    except EOFError:
+        print()
+        return Resultado.ADIOS
+    return Resultado.BIEN if bien else Resultado.MAL
+
+def abfrage(parser):
+    random.seed()
+    try:
+        with open(VOKABELN_FILE, 'r') as f:
+            palabras = json.load(f)
+        with open(STATUS_FILE, 'r') as f:
+            status = json.load(f)
+    except FileNotFoundError:
+        print(f"{bcolors.FAIL}Daten können nicht geladen werden, hast du sie schon importiert?{bcolors.ENDC}")
+        print()
+        parser.print_help()
+        return
+
+    unidad = False
+    paso = False
+    cur_palabras = False
+    bien = 0
+    mal = 0
+    for palabra in palabras:
+        if paso != palabra['paso']:
+            if cur_palabras != False:
+                c = [len(cur_palabras[x]) for x in cur_palabras]
+                print(f"{bcolors.BOLD}{unidad}{bcolors.ENDC}: {paso} (",end="")
+                print(*c, sep="/", end=")")
+                print()
+                for n in range(5): # 1..4, no 5
+                    random.shuffle(cur_palabras[n])
+                    for palabra in cur_palabras[n]:
+                        s = status.get(palabra['id'], 0)
+                        match einzelne_abfrage(palabra, s):
+                            case Resultado.BIEN:
+                                status[palabra['id']] = s + 1
+                                bien+=1
+                            case Resultado.MAL:
+                                if s > 0:
+                                    status[palabra['id']] = s - 1
+                                    mal+=1
+                                    continue
+                            case Resultado.ADIOS:
+                                print(f'{bcolors.OKGREEN}+{bien}{bcolors.ENDC} / {bcolors.FAIL}-{mal}{bcolors.ENDC}')
+                                return
+                        with open(STATUS_FILE + '.new', 'w') as f:
+                            json.dump(status, f)
+                            f.flush()
+                            os.fsync(f.fileno())
+                        with open(STATUS_FILE + '.new', 'r') as f:
+                            status = json.load(f)
+                        os.replace(STATUS_FILE + '.new', STATUS_FILE)
+
+            cur_palabras = {0: [], 1: [], 2: [], 3: [], 4: [], 5: []}
+            unidad = palabra['unidad']
+            paso = palabra['paso']
+
+        cur_palabras[status.get(palabra['id'], 0)].append(palabra)
+
+parser = argparse.ArgumentParser()
+default_data_file = os.environ['PWD'] + '/assets/amf/vokabelTrainer147.amf'
+parser.add_argument('--import-data', type=str, help="Path to assets", metavar="DIR")
+default_status_file = os.environ['HOME'] + '/klett/1266/vokabeltrainerData147'
+parser.add_argument('--import-status', type=str, help="Path to AMF File, defaults to " + default_status_file, metavar="FILE", nargs='?', const=default_status_file)
+args = parser.parse_args()
+
+if args.import_data:
+    import_vokabeln(args.import_data + '/amf/vokabelTrainer147.amf',
+                    args.import_data + '/amf/medium/')
+elif args.import_status:
+    import_status(args.import_status)
+else:
+    abfrage(parser)