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Fábián Varga
2025-02-19 22:11:03 +01:00
commit e9217e9001
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7
.gitignore vendored Normal file
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bin/
include/
lib/
share/
lib64
pyvenv.cfg

4
README.md Normal file
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# UI Cviko 1
- Úvod do/Opakovanie Pythonu
- Jednoduchý chatbot

359
notebook/cviko1_1.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"text = \"Some not interesting text input\""
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"words = text.split(\" \")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Some', 'not', 'interesting', 'text', 'input']"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"words"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Some\n",
"not\n",
"interesting\n",
"text\n",
"input\n"
]
}
],
"source": [
"for word in words:\n",
" print(word)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['The lazy fox jumps over ', ' lazy dog']"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"The lazy fox jumps over the lazy dog\".split(\"the\")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(\"Hello\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(words)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(words[0])"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"text\" in words"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"text.count(\"text\")"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"long_words = [word for word in words if len(word) > 4]"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['interesting', 'input']"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"long_words"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Hello'"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"Hello\".title()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"capitals = [word for word in words if word.istitle()]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Some']"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"capitals"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'ADAM'"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"Adam\".upper()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'adam'"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\"Adam\".lower()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"text = \"Lorem Ipsum has been the industry's standard dummy text ever since the 1500s , when an unknown printer took a galley of type and scrambled it to make a type specimen book .\""
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"30"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(set(text.split(\" \")))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "ui-cviko1",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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notebook/cviko1_2-chatbot.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"< My name is AI-CHATBOT.\n",
"< I can't do that.\n",
"< Nope.\n",
"< The sky is blue.\n",
"< Bye\n"
]
}
],
"source": [
"import random\n",
"\n",
"no_responses = [\n",
" \"I can't answer that.\",\n",
" \"I don't know, sorry.\",\n",
" \"I can't understand you.\",\n",
" \"Can you elaborate, please?\"\n",
"]\n",
"\n",
"responses = {\n",
" \"What's the weather like today?\": [\n",
" \"It's sunny!\",\n",
" \"It seems sunny today.\",\n",
" \"Sunny.\"\n",
" ],\n",
" \"What is your name?\": [\n",
" \"My name is AI-CHATBOT.\",\n",
" \"It's AI-CHATBOT.\",\n",
" ],\n",
" \"What's your favorite color?\": [\n",
" \"It's yellow.\",\n",
" \"Yellow.\"\n",
" ],\n",
" \"What color is the sky?\": [\n",
" \"The sky is blue.\",\n",
" \"It's blue.\"\n",
" ],\n",
" \"Can you talk?\": [\n",
" \"No.\",\n",
" \"Nope.\",\n",
" \"I can't do that.\"\n",
" ]\n",
"}\n",
"\n",
"while True:\n",
" message = input(\"> \")\n",
"\n",
" if message == \"bye\":\n",
" print(\"< Bye\")\n",
" break\n",
" \n",
" if message in responses.keys():\n",
" print(\"<\", random.choice(responses[message]))\n",
" else:\n",
" print(\"<\", random.choice(no_responses))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "ui-cviko1",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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requirements.txt Normal file
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asttokens==3.0.0
comm==0.2.2
debugpy==1.8.12
decorator==5.1.1
executing==2.2.0
ipykernel==6.29.5
ipython==8.32.0
jedi==0.19.2
jupyter_client==8.6.3
jupyter_core==5.7.2
matplotlib-inline==0.1.7
nest-asyncio==1.6.0
packaging==24.2
parso==0.8.4
pexpect==4.9.0
platformdirs==4.3.6
prompt_toolkit==3.0.50
psutil==7.0.0
ptyprocess==0.7.0
pure_eval==0.2.3
Pygments==2.19.1
python-dateutil==2.9.0.post0
pyzmq==26.2.1
six==1.17.0
stack-data==0.6.3
tornado==6.4.2
traitlets==5.14.3
wcwidth==0.2.13