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@hiromis
Created March 9, 2018 19:39
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## My understanding\n",
"In Python, you can concatinate lists by using `+`"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1, 2, 3, 4, 5]"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[1, 2] + [3, 4, 5]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['a', 'b', ['c', 'd'], 'e', 'f']"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"['a', 'b', ['c', 'd']] + ['e', 'f']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"When I saw `sum(texts, [])` I automatically imagined `texts + []` "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[['a'], ['b']]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"texts = [['a'], ['b']]\n",
"texts + []"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"which would not change dimentionality in anyway. Then I looked at:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"?? sum"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
"Signature: sum(iterable, start=0, /)\n",
"Docstring:\n",
"Return the sum of a 'start' value (default: 0) plus an iterable of numbers\n",
"\n",
"When the iterable is empty, return the start value.\n",
"This function is intended specifically for use with numeric values and may\n",
"reject non-numeric types.\n",
"Type: builtin_function_or_method\n",
"```\n",
"\n",
"\n",
"And experimented with `sum`"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum([1, 2], 3)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "sum() can't sum strings [use ''.join(seq) instead]",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0mTraceback (most recent call last)",
"\u001b[0;32m<ipython-input-6-558d097dd53c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'a'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'b'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m: sum() can't sum strings [use ''.join(seq) instead]"
]
}
],
"source": [
"sum(['a', 'b'], 'c')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### I believe `sum` does the following:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iterable = [1, 2]\n",
"start = 3\n",
"\n",
"for i in iterable: start += i\n",
" \n",
"start"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So when you do:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['a', 'b', ['c']]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum([['a'], ['b'], [['c']]], [])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It is equivalent to:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['a', 'b', ['c']]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[] + ['a'] + ['b'] + [['c']]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"and dimentionality is reduced by 1"
]
}
],
"metadata": {
"gist": {
"data": {
"description": "",
"public": true
},
"id": ""
},
"kernelspec": {
"display_name": "fastai",
"language": "python",
"name": "fastai"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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