Max
697 lines
43 KiB
Plaintext
697 lines
43 KiB
Plaintext
{
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"cells": [
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"# Wichtige Python-Bibliotheken\n",
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"\n",
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"## Ziel dieser Einheit\n",
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"\n",
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"In dieser Einheit lernst du:\n",
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"\n",
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"- welche Python-Bibliotheken für typische Aufgaben wichtig sind\n",
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"- wie Dateien und Verzeichnisse verarbeitet werden\n",
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"- wie Datenformate wie JSON und CSV genutzt werden\n",
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"- wie Datum, Zeit, Zufall und Mathematik unterstützt werden\n",
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"- wie reguläre Ausdrücke verwendet werden\n",
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"- welche externen Bibliotheken für Web, Datenanalyse und Visualisierung häufig genutzt werden\n",
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"\n",
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"\n",
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"## 1. Überblick\n",
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"\n",
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"Python bringt bereits viele Bibliotheken mit, die häufige Aufgaben erleichtern.\n",
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"\n",
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"Diese Bibliotheken nennt man Standardbibliothek.\n",
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"\n",
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"Sie helfen zum Beispiel bei:\n",
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"\n",
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"- Dateien und Verzeichnissen\n",
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"- Datenformaten\n",
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"- Datum und Zeit\n",
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"- Zufallszahlen\n",
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"- mathematischen Berechnungen\n",
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"- regulären Ausdrücken\n",
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"\n",
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"Zusätzlich gibt es externe Bibliotheken, die nicht automatisch installiert sind.\n",
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"\n",
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"Beispiele dafür sind:\n",
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"\n",
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"- requests\n",
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"- pandas\n",
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"- matplotlib\n",
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"\n",
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"Diese müssen bei Bedarf zusätzlich installiert werden.\n",
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"\n",
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"\n",
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"## 2. Dateien und Verzeichnisse mit os\n",
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"\n",
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"Die Bibliothek os enthält Funktionen für den Zugriff auf das Betriebssystem.\n",
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"\n",
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"Damit können zum Beispiel Informationen über Verzeichnisse abgefragt werden.\n"
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],
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"id": "d806e8d5775c1709"
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},
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{
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"import os\n",
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"print(os.getcwd())"
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],
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"id": "e77758f9a02f797f"
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"\n",
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"os.getcwd() gibt das aktuelle Arbeitsverzeichnis aus.\n",
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"\n",
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"Das ist hilfreich, wenn man wissen möchte, in welchem Ordner das Python-Programm gerade ausgeführt wird.\n",
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"\n",
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"\n",
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"## 3. Dateien prüfen mit pathlib\n",
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"\n",
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"pathlib ist eine moderne Bibliothek zum Arbeiten mit Dateipfaden.\n",
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"\n",
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" from pathlib import Path\n",
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" print(Path(\"datei.csv\").exists())\n",
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"\n",
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"Path(\"datei.csv\").exists() prüft, ob die Datei datei.csv existiert.\n",
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"\n",
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"Das Ergebnis ist ein Boolean-Wert:\n",
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"\n",
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"- True → Datei existiert\n",
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"- False → Datei existiert nicht\n",
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"\n",
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"pathlib ist oft lesbarer als ältere Lösungen mit os.\n",
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"\n",
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"\n",
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"## 4. JSON als Datenformat\n",
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"\n",
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"JSON ist ein häufig verwendetes Datenformat.\n",
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"\n",
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"Es wird oft genutzt, um Daten zwischen Programmen oder über APIs auszutauschen."
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],
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"id": "dc1cc14ebcebf6d3"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:21:46.771084600Z",
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"start_time": "2026-07-23T06:21:46.734774200Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import json\n",
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"print(json.dumps({\"name\": \"Anna\"}))"
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],
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"id": "4fa664e155d8908e",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{\"name\": \"Anna\"}\n"
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]
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}
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],
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"execution_count": 6
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"json.dumps() wandelt Python-Daten in einen JSON-String um.\n",
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"\n",
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"In diesem Beispiel wird ein Dictionary verwendet:\n",
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"\n",
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" {\"name\": \"Anna\"}\n",
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"\n",
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"Das Ergebnis ist ein Text im JSON-Format.\n",
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"\n",
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"JSON ist besonders wichtig bei:\n",
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"\n",
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"- Web-APIs\n",
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"- Konfigurationsdateien\n",
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"- Datenaustausch zwischen Anwendungen\n",
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"\n",
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"\n",
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"## 5. CSV-Dateien\n",
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"\n",
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"CSV-Dateien sind Textdateien für tabellarische Daten.\n",
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"\n",
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"CSV steht für Comma-separated values.\n",
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"\n",
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"In der Praxis werden CSV-Dateien häufig für Exporte aus Tabellenprogrammen oder anderen Anwendungen verwendet.\n"
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],
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"id": "b2d53fd19c06cd65"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:21:38.576322300Z",
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"start_time": "2026-07-23T06:21:38.518128200Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import csv\n",
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"\n",
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"with open(\"datei.csv\") as f:\n",
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" reader = csv.reader(f)\n",
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" for line in reader:\n",
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" print(line)"
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],
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"id": "8d640100b34ccf09",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['Dies', ' ist', ' eine', ' CSV']\n",
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"['Dies', ' ist', ' eine', ' Zeile']\n"
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]
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}
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],
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"execution_count": 5
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"\n",
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"Ablauf:\n",
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"\n",
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"1. Die Datei datei.csv wird geöffnet\n",
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"2. csv.reader(f) liest die Datei zeilenweise\n",
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"3. Jede Zeile wird als Liste ausgegeben\n",
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"\n",
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"Die Schreibweise mit with sorgt dafür, dass die Datei automatisch wieder geschlossen wird.\n",
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"\n",
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"\n",
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"## 6. Datum und Zeit\n",
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"\n",
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"Für Datum und Uhrzeit wird häufig datetime verwendet.\n"
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],
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"id": "5b9e3d33e528f471"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:21:51.172465100Z",
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"start_time": "2026-07-23T06:21:51.134798300Z"
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}
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},
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"cell_type": "code",
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"source": [
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"from datetime import datetime\n",
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"print(datetime.now())"
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],
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"id": "65f933470ead2c90",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2026-07-23 08:21:51.142547\n"
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]
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}
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],
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"execution_count": 7
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"\n",
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"datetime.now() gibt das aktuelle Datum und die aktuelle Uhrzeit zurück.\n",
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"\n",
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"Das ist nützlich für:\n",
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"\n",
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"- Zeitstempel\n",
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"- Protokolle\n",
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"- Berechnungen mit Datum und Uhrzeit\n",
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"- Anzeige aktueller Zeitpunkte\n",
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"\n",
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"\n",
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"## 7. Zufallszahlen\n",
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"\n",
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"Für Zufallszahlen wird die Bibliothek random verwendet.\n"
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],
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"id": "e90d8636f98a3258"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:27:15.504068800Z",
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"start_time": "2026-07-23T06:27:15.461391300Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import random\n",
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"print(random.randint(1, 10))"
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],
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"id": "53dc9d63415c7d1b",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2\n"
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]
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}
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],
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"execution_count": 36
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"\n",
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"random.randint(1, 10) erzeugt eine Zufallszahl zwischen 1 und 10.\n",
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"\n",
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"Beide Grenzen sind dabei eingeschlossen.\n",
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"\n",
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"Zufallszahlen werden häufig verwendet für:\n",
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"\n",
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"- Spiele\n",
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"- Simulationen\n",
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"- Tests\n",
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"- zufällige Auswahl von Werten\n",
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"\n",
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"\n",
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"## 8. Mathematische Funktionen\n",
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"\n",
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"Die Bibliothek math enthält mathematische Funktionen.\n"
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],
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"id": "4f5844bbf29fedd9"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:22:13.617188500Z",
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"start_time": "2026-07-23T06:22:13.557773800Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import math\n",
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"print(math.sqrt(16))"
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],
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"id": "a3345e045fe57ec1",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4.0\n"
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]
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}
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],
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"execution_count": 8
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"\n",
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"math.sqrt(16) berechnet die Quadratwurzel von 16.\n",
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"\n",
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"Das Ergebnis ist:\n",
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"\n",
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" 4.0\n",
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"\n",
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"math bietet viele weitere Funktionen, zum Beispiel für:\n",
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"\n",
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"- Potenzen\n",
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"- Rundungen\n",
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"- trigonometrische Funktionen\n",
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"- Konstanten wie pi\n",
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"\n",
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"\n",
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"## 9. Reguläre Ausdrücke\n",
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"\n",
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"Reguläre Ausdrücke werden mit der Bibliothek re verarbeitet.\n",
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"\n",
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"Sie dienen dazu, Muster in Texten zu finden.\n"
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],
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"id": "181d36505443c9d"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:32:11.783546600Z",
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"start_time": "2026-07-23T06:32:11.751408Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import re\n",
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"print(bool(re.match(r\"\\d+\", \"11\")))"
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],
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"id": "c40e185426ff334",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n"
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]
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}
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],
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"execution_count": 45
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"\n",
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"\n",
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"re.match(r\"\\d+\", \"123\") prüft, ob der String mit einer oder mehreren Ziffern beginnt.\n",
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"\n",
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"Erklärung:\n",
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"\n",
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"- \\d steht für eine Ziffer\n",
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"- + bedeutet: einmal oder mehrfach\n",
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"- \"123\" beginnt mit Ziffern\n",
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"\n",
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"bool(...) wandelt das Ergebnis in True oder False um.\n",
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"\n",
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"Reguläre Ausdrücke sind hilfreich für:\n",
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"\n",
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"- Textsuche\n",
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"- Validierung von Eingaben\n",
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"- Erkennen bestimmter Muster\n",
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"- einfache Textanalyse\n",
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"\n",
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"\n",
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"## 10. HTTP und Web mit requests\n",
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"\n",
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"Für HTTP-Anfragen wird häufig die externe Bibliothek requests verwendet.\n"
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],
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"id": "a99b5bcc0d9ba05a"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:13:02.238543200Z",
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"start_time": "2026-07-23T06:13:01.213093300Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import requests\n",
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"print(requests.get(\"https://api.github.com\").status_code)"
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],
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"id": "9a916a956765d052",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"200\n"
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]
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}
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],
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"execution_count": 1
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"requests ist nicht Teil der Standardbibliothek.\n",
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"\n",
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"Wenn requests verwendet werden soll, muss die Bibliothek vorher installiert werden.\n",
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"\n",
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"Beispiel:\n",
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"\n",
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" pip install requests\n",
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"\n",
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"Mit requests können Web-APIs abgefragt werden.\n",
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"\n",
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"Der Statuscode zeigt an, ob eine Anfrage erfolgreich war.\n",
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"\n",
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"Beispiele:\n",
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"\n",
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"- 200 → erfolgreich\n",
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"- 404 → nicht gefunden\n",
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"- 500 → Serverfehler\n",
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"\n",
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"\n",
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"## 11. Alternative zu requests: urllib\n",
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"\n",
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"Wenn keine externe Bibliothek installiert werden soll, kann urllib verwendet werden.\n",
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"\n",
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"urllib gehört zur Standardbibliothek.\n",
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"\n",
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"Der Vorteil:\n",
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"\n",
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"- keine zusätzliche Installation nötig\n",
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"\n",
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"Der Nachteil:\n",
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"\n",
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"- weniger komfortabel als requests\n",
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"\n",
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"\n",
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"## 12. Datenanalyse mit pandas\n",
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"\n",
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"pandas ist eine externe Bibliothek für Datenanalyse.\n"
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],
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"id": "562f7b5c490ca65d"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-07-23T06:16:45.001465600Z",
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"start_time": "2026-07-23T06:16:43.101256500Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import pandas as pd\n",
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"df = pd.DataFrame({\"a\": [1, 2, 3]})"
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],
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"id": "c5891b3e345a01ec",
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"outputs": [],
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"execution_count": 2
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
|
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"pandas wird häufig verwendet, um tabellarische Daten zu verarbeiten.\n",
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"\n",
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"Zum Beispiel:\n",
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"\n",
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"- CSV-Dateien einlesen\n",
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"- Daten filtern\n",
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"- Daten gruppieren\n",
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"- Daten auswerten\n",
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"- Tabellen ähnlich wie in Excel bearbeiten\n",
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"\n",
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"pandas ist nicht Teil der Standardbibliothek und muss bei Bedarf installiert werden.\n",
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"\n",
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"Beispiel:\n",
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"\n",
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" pip install pandas\n",
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"\n",
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"\n",
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"## 13. Visualisierung mit matplotlib\n",
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"\n",
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"matplotlib ist eine externe Bibliothek zum Erstellen von Diagrammen.\n"
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],
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"id": "cbb0beecbe743112"
|
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},
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{
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"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2026-07-23T06:35:07.696130800Z",
|
|
"start_time": "2026-07-23T06:35:07.555373200Z"
|
|
}
|
|
},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"plt.plot([1, 2, 3], [4, 5, 6])\n",
|
|
"plt.show()"
|
|
],
|
|
"id": "3940fcd1a8543718",
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
],
|
|
"image/png": 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"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data",
|
|
"jetTransient": {
|
|
"display_id": null
|
|
}
|
|
}
|
|
],
|
|
"execution_count": 46
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"\n",
|
|
"\n",
|
|
"Mit matplotlib können Daten grafisch dargestellt werden.\n",
|
|
"\n",
|
|
"Zum Beispiel:\n",
|
|
"\n",
|
|
"- Liniendiagramme\n",
|
|
"- Balkendiagramme\n",
|
|
"- Punktdiagramme\n",
|
|
"- einfache Auswertungen\n",
|
|
"\n",
|
|
"matplotlib ist besonders hilfreich, wenn Daten nicht nur berechnet, sondern auch sichtbar gemacht werden sollen.\n",
|
|
"\n",
|
|
"Auch matplotlib muss bei Bedarf installiert werden.\n",
|
|
"\n",
|
|
"Beispiel:\n",
|
|
"\n",
|
|
" pip install matplotlib\n",
|
|
"\n",
|
|
"\n",
|
|
"## 14. Wichtige Konzepte im Überblick\n",
|
|
"\n",
|
|
"### Standardbibliothek\n",
|
|
"\n",
|
|
"Die Standardbibliothek ist direkt in Python enthalten.\n",
|
|
"\n",
|
|
"Beispiele:\n",
|
|
"\n",
|
|
"- os\n",
|
|
"- pathlib\n",
|
|
"- json\n",
|
|
"- csv\n",
|
|
"- datetime\n",
|
|
"- random\n",
|
|
"- math\n",
|
|
"- re\n",
|
|
"\n",
|
|
"\n",
|
|
"### Externe Bibliotheken\n",
|
|
"\n",
|
|
"Externe Bibliotheken müssen zusätzlich installiert werden.\n",
|
|
"\n",
|
|
"Beispiele:\n",
|
|
"\n",
|
|
"- requests\n",
|
|
"- pandas\n",
|
|
"- matplotlib\n",
|
|
"\n",
|
|
"\n",
|
|
"### Import\n",
|
|
"\n",
|
|
"Mit import werden Bibliotheken eingebunden.\n",
|
|
"\n",
|
|
"Beispiel:\n"
|
|
],
|
|
"id": "866a163292f47048"
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"outputs": [],
|
|
"execution_count": null,
|
|
"source": "import random",
|
|
"id": "7b1b02fa0328a838"
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"\n",
|
|
"\n",
|
|
"Danach können Funktionen aus dieser Bibliothek verwendet werden.\n",
|
|
"\n",
|
|
"\n",
|
|
"### from import\n",
|
|
"\n",
|
|
"Mit from import kann gezielt ein Teil einer Bibliothek importiert werden.\n",
|
|
"\n",
|
|
"Beispiel:\n"
|
|
],
|
|
"id": "3aeb90a1b507c8c1"
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"outputs": [],
|
|
"execution_count": null,
|
|
"source": "from datetime import datetime",
|
|
"id": "8f9012dff21be2af"
|
|
},
|
|
{
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"\n",
|
|
"Dadurch kann datetime direkt verwendet werden.\n",
|
|
"\n",
|
|
"\n",
|
|
"## Zusammenfassung\n",
|
|
"\n",
|
|
"- Python bietet viele Bibliotheken für typische Aufgaben\n",
|
|
"- os und pathlib helfen beim Arbeiten mit Dateien und Verzeichnissen\n",
|
|
"- json und csv werden für Datenformate verwendet\n",
|
|
"- datetime verarbeitet Datum und Uhrzeit\n",
|
|
"- random erzeugt Zufallszahlen\n",
|
|
"- math stellt mathematische Funktionen bereit\n",
|
|
"- re verarbeitet reguläre Ausdrücke\n",
|
|
"- requests, pandas und matplotlib sind externe Bibliotheken für Web, Datenanalyse und Visualisierung\n",
|
|
"\n",
|
|
"\n",
|
|
"## Verständnisfragen\n",
|
|
"\n",
|
|
"- Wofür wird os.getcwd() verwendet?\n",
|
|
"- Was prüft Path(\"datei.csv\").exists()?\n",
|
|
"- Wozu dient json.dumps()?\n",
|
|
"- Warum wird beim Lesen einer Datei häufig with verwendet?\n",
|
|
"- Was ist der Unterschied zwischen Standardbibliotheken und externen Bibliotheken?"
|
|
],
|
|
"id": "2771261011b94e9c"
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 2
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython2",
|
|
"version": "2.7.6"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|