| from typing import Optional, Hashable, TypeVar | |
| class CallableDict(dict): | |
| V = TypeVar('V') | |
| """ A callable dictionary useful for functional programming """ | |
| def __call__(self, key: Hashable, default: Optional[V]=None) -> Optional[V]: | |
| return self.get(key, default) |
Hey guys! I'm @soaxelbrooke, and I am here to show you ladies and guys how to create a basic text analytics engine with Elasticsearch.
Let's get the data first! These are product reviews from Amazon, which can be found here.
$ curl http://times.cs.uiuc.edu/~wang296/Data/LARA/Amazon/AmazonReviews.zip -o reviews.zip
| import scala.sys.process._ | |
| object BetaDistributionFit { | |
| val distName: String = "beta" | |
| def fitCommand(samples: Seq[Double]): Seq[String] = | |
| Seq("python", "-c", | |
| s""" | |
| |from scipy import stats |
| from gensim.models import Phrases | |
| import sys | |
| assert len(sys.argv) > 2, "Need gensim model path and output filename!" | |
| in_path, out_path = sys.argv[:2] | |
| class PrefixTree(object): | |
| def __init__(self, words, impl=dict, suffix_impl=list): | |
| self.word = words[0] |
| #!/usr/bin/env bash | |
| # Usage: $ ec2ssh cassandra-i-3 | |
| ssh $(aws ec2 describe-instances --query 'Reservations[].Instances[].[Tags[?Key==`Name`].Value | [0], PrivateIpAddress]' --output text | grep $1 | head -n 1 | python -c 'import sys; print(sys.stdin.read().split("\t")[1].strip())') |
| object implicits { | |
| implicit class ESFuture[Response <: ActionResponse](future: ListenableActionFuture[Response]) | |
| extends Future[Response] { | |
| override def onComplete[U](f: (Try[Response]) => U)(implicit executor: ExecutionContext): Unit = { | |
| future.addListener(new ActionListener[Response] { | |
| override def onFailure(e: Throwable): Unit = throw e | |
| override def onResponse(response: Response): Unit = f(Try(response)) | |
| }) |
I hereby claim:
To claim this, I am signing this object:
| """ Caches expensive function calls in pickled bytes on disk. """ | |
| import os | |
| import shutil | |
| import subprocess | |
| import dill | |
| from functools import wraps | |
| import hashlib | |
| import base64 |
| # It's not pretty, but it get's the job done. JSON is valid Python, so you can eval it, | |
| # provided that you have the proper names in scope, like ObjectId and ISODate | |
| from dateutil import parser | |
| NumberLong = int | |
| ObjectId = str | |
| false = False |
| class GzipBuffer(object): | |
| def __init__(self): | |
| self.len = 0 | |
| self.buffer = io.BytesIO() | |
| self.writer = gzip.GzipFile(fileobj=self.buffer, mode='wb') | |
| def append(self, thing): | |
| self.len += 1 | |
| self.writer.write(thing) |