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meow_base/benchmarking/sequential.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"INPUT_FILE = 'file_0.txt'\n",
"MAX_COUNT = 100"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"with open(INPUT_FILE, 'r') as f:\n",
" data = int(f.read())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"read in: \"+ str(data))\n",
"print(\"writing out: \"+ str(data+1))"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"if data+1 < MAX_COUNT:\n",
" with open(INPUT_FILE.replace(str(data), str(data+1)), 'w') as f:\n",
" f.write(str(data+1))"
]
}
],
"metadata": {
"interpreter": {
"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
},
"kernelspec": {
"display_name": "Python 3",
"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": "3.9.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}