ordered set.ipynb

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     "text": [
      "435 µs ± 4.32 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
      "64.5 µs ± 1.53 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
      "35.8 µs ± 159 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
      "44.4 µs ± 303 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
      "564 µs ± 1.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
      "940 µs ± 1.67 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
      "26.4 ms ± 275 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "# only tested on python 3.6\n",
    "from functools import reduce\n",
    "\n",
    "with open(\"ordered set.ipynb\") as f:\n",
    "    s = f.read()\n",
    "\n",
    "def naive(s):\n",
    "    d = []\n",
    "    for c in s:\n",
    "        if c not in d:\n",
    "            d.append(c)\n",
    "    return d\n",
    "\n",
    "%timeit naive(s)\n",
    "%timeit list(dict(zip(s, s)))\n",
    "%timeit list(dict.fromkeys(s))\n",
    "%timeit sorted(set(s), key=s.index)\n",
    "%timeit reduce(lambda x, y: x if y in x else x + [y], s, [])\n",
    "%timeit reduce(lambda x, y: x + [y] * (y not in x), s, [])\n",
    "%timeit [c[1] for c in enumerate(s) if list(s).index(c[1]) == c[0]]"
   ]
  }
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