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import pandas as pd | |
import numpy as np | |
class InsertContext(): | |
def __init__(self, tf): | |
self._tf = tf | |
self.__write_mode_on = False | |
def __enter__(self): |
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// code generated from <org.scribe.extractors.TokenExtractorTest: void shouldExtractTokenFromOAuthStandardResponse()> | |
com.ser.assist.statecarver.xstreamcarver.StaticStateLoader.loadStaticState(760, "scribe-java_freqT") | |
def dbName_intg = "scribe-java_freqT_intg" | |
temp$0 = com.ser.assist.statecarver.xstreamcarver.XStreamStateCarver.loadState(760, 200, "scribe-java_freqT") | |
temp$0_clone = com.ser.assist.statecarver.xstreamcarver.XStreamStateCarver.loadState(760, 200, "scribe-java_freqT") | |
response = com.ser.assist.statecarver.xstreamcarver.XStreamStateCarver.loadState(760, 0, "scribe-java_freqT") | |
//Note that we are using a 'response' object which was tested as part of unit test elsewhere. |
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//Accepts a closure that takes one argument. The closure should return true/false. | |
//The closure is the predicate which will be checked to create new partitions | |
def partition(coll, Closure cond) { | |
def x = coll.drop(1).inject([[coll[0]]]) { acc, it -> | |
if ( cond(it) ) { | |
acc << [it] | |
} | |
else | |
{ |
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;; This gist roughly transribes the demo | |
;; by Jim Weirich during his talk on Y-Combinator | |
;; called Y-Not. | |
;; http://www.infoq.com/presentations/Y-Combinator | |
;; Jim does a phenomenal job of explaining in the demo. | |
;; Therefore, this gist only attempts to provide | |
;; the code example from the poor quality video | |
;; The examples are simplified at some places | |
;; based on how I tried to understand it |
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//Cartesian product of input (for Integers) | |
//similar to itertools.product in Python | |
def l = [ [1,2] , [3,4] , [5, 6]] | |
def product(l){ | |
def p = { l1, l2 -> | |
l1.inject([]) { acc, i -> | |
acc + l2.inject([]) { acc1, j -> | |
if ( i instanceof List) { acc1 << i + j} |
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// does a product on two lists | |
h = [ 1: "a", 2:"b", 3:"c"] | |
j = [ 1: ["x", "p"], 2: ["z"], 3:["y"]] | |
h.entrySet().inject([]) { acc, h1 -> | |
acc + j.get(h1.key).inject([]) { acc1, it-> acc1 << [h1.value, it]} } |
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;;visit all nodes using reduce | |
;;clojure | |
;;store nodes in visited order. | |
(defn visit [g] | |
(let [walk (fn walk [g seen n] | |
(reduce (fn [seen, m] | |
(cond | |
(seen m) seen | |
:else (walk g (conj seen m) m) )) seen (g n)) |
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;;Computes all possible paths through a graph (DAG) | |
;;assumes the graph is a DAG | |
;; Clojure | |
(defn all-paths [g] | |
(let [walk (fn walk [g seen n] | |
(cond | |
(empty? (g n)) seen | |
:else (mapcat (fn [m] | |
(walk g (conj seen m) m)) (g n))))] |
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;; Counting Coins | |
;; problem from "Coding for Interviews" news letter. | |
;; notes: switching to vector from raw list gave a tremendous performance boost | |
;; uses memoize as variant of Y-combinator. | |
(let | |
[coins (map read-string (clojure.string/split (read-line) #",")) | |
amt (read-string (read-line)) | |
change3 (fn [rec amt coins] | |
(cond |