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Solved lab #636

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127 changes: 124 additions & 3 deletions lab-python-flow-control.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -37,13 +37,134 @@
"\n",
"3. Instead of updating the inventory by subtracting 1 from the quantity of each product, only do it for the products that were ordered (those in \"customer_orders\")."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "863664a2-71ce-4b17-819e-7a1812fd9120",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"quantity of t-shirt available in the inventory: 22\n",
"quantity of mug available in the inventory: 34\n",
"quantity of hat available in the inventory: 45\n",
"quantity of book available in the inventory: 65\n",
"quantity of keychain available in the inventory: 76\n"
]
}
],
"source": [
"products=[\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"inventory={}\n",
"inventory[\"t-shirt\"]=int(input(\"quantity of t-shirt available in the inventory: \"))\n",
"inventory[\"mug\"]=int(input(\"quantity of mug available in the inventory: \"))\n",
"inventory[\"hat\"]=int(input(\"quantity of hat available in the inventory: \"))\n",
"inventory[\"book\"]=int(input(\"quantity of book available in the inventory: \"))\n",
"inventory[\"keychain\"]=int(input(\"quantity of keychain available in the inventory: \"))\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "65848c54-3545-470f-ab1d-10a5e41641e8",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"input order : hat\n",
"if you want to add another product (yes/no): yes\n",
"input order : book\n",
"if you want to add another product (yes/no): no\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'book', 'hat'}\n",
"2\n"
]
}
],
"source": [
"\n",
"customer_orders=set() \n",
"add_another_product=\"yes\"\n",
"\n",
"while add_another_product== \"yes\" :\n",
" x=input(\"input order :\")\n",
" customer_orders.add(x)\n",
" add_another_product=input(\"if you want to add another product (yes/no):\")\n",
"\n",
"print(customer_orders)\n",
"\n",
"total_products_ordered=len(customer_orders)\n",
"print(total_products_ordered)\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f4e8f26a-03e9-41fc-bf62-224a7379b382",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 2\n",
"Percentage of Products Ordered: 40.0\n",
"{'t-shirt': 22, 'mug': 34, 'hat': 42, 'book': 62, 'keychain': 76}\n",
"('t-shirt', 22)\n",
"('mug', 34)\n",
"('hat', 42)\n",
"('book', 62)\n",
"('keychain', 76)\n",
"dict_items([('t-shirt', 22), ('mug', 34), ('hat', 42), ('book', 62), ('keychain', 76)])\n"
]
}
],
"source": [
"\n",
"\n",
"percentage_ordered=len(customer_orders)/len(products)*100\n",
"order_status=(total_products_ordered,percentage_ordered)\n",
"print(\"Order Statistics:\")\n",
"print(\"Total Products Ordered: \"+ str(total_products_ordered))\n",
"print(\"Percentage of Products Ordered: \"+ str(percentage_ordered))\n",
"\n",
"for item in customer_orders:\n",
" inventory[item]=inventory[item]-1\n",
" \n",
"print (inventory)\n",
"\n",
"for item in inventory.items() :\n",
" print(item)\n",
"\n",
"print(inventory.items())\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e5b646a5-82b3-4e02-bf21-4a56cd4cc9d9",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python [conda env:base] *",
"language": "python",
"name": "python3"
"name": "conda-base-py"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -55,7 +176,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.9"
}
},
"nbformat": 4,
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