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@tmbdev
Created April 18, 2018 18:43
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"%pylab inline"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"from dlinputs import tarrecords, utils\n",
"import hashlib"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'5d41402abc4b2a76b9719d911017c592'"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def md5hash(x):\n",
" return hashlib.md5(str(x)).hexdigest()\n",
"md5hash(\"hello\")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-rw-r--r-- tmb/tmb 1 1969-12-31 16:00 10.cls\n",
"-rw-r--r-- tmb/tmb 306 1969-12-31 16:00 10.png\n",
"-rw-r--r-- tmb/tmb 1 1969-12-31 16:00 11.cls\n",
"-rw-r--r-- tmb/tmb 345 1969-12-31 16:00 11.png\n",
"-rw-r--r-- tmb/tmb 1 1969-12-31 16:00 12.cls\n",
"tar: write error\n"
]
}
],
"source": [
"!tar -ztvf testdata/sample.tgz | sed 5q"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"__key__ '10'\n",
"__source__ <type 'NoneType'> None\n",
"cls 0\n",
"png float32 (28, 28)\n"
]
}
],
"source": [
"data = tarrecords.tariterator(open(\"testdata/sample.tgz\"))\n",
"data = list(data)\n",
"utils.print_sample(data[0])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on built-in function sorted in module __builtin__:\n",
"\n",
"sorted(...)\n",
" sorted(iterable, cmp=None, key=None, reverse=False) --> new sorted list\n",
"\n"
]
}
],
"source": [
"help(sorted)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"sorted_by_key = sorted(data, key=lambda x: x[\"__key__\"])"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"sorted_by_content = sorted(data, key=lambda x: x[\"cls\"])"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"sorted_by_keyhash = sorted(data, key=lambda x: md5hash(x[\"__key__\"]))"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"sorted_by_contenthash = sorted(data, key=lambda x: md5hash(x[\"png\"]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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