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import React, { useEffect, useState, useRef, useMemo, useCallback } from 'react'; | |
import { Text, Editor, createEditor, Node, Range, Point, Transforms } from 'slate'; | |
import { | |
Slate, | |
Editable, | |
withReact, | |
useSelected, | |
useFocused, | |
useSlate } from 'slate-react'; | |
import { withHistory } from 'slate-history'; |
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> db.web_hook_log.find({"created_at" : {"$gte": new Date("2019-04-19T03:00:00.000Z"), "$lte": new Date("2019-04-19T07:00:00.000Z")}}).sort({created_at: -1}).limit(10); | |
{ "_id" : ObjectId("5cb9718b3de6331b5b689400"), "is_sent" : 0, "thread_id" : 392511, "text" : "★購入完了のお知らせ★\r\n\r\nご購入いただき誠にありがとうございました。\r\n\r\n購入完了のメールが届いていなくても、このメッセージが届いた場合は、問題なくご注文が完了しています。\r\n\r\n会員のお客様は、MyLC(マイエルシー)からご注文履歴を確認することができるので、下記よりご確認ください。\r\n\r\nhttps://secure.lovecosmetic.net/lcmy/lcChum.php?apv1=\r\n\r\n商品お届けまで今しばらくお待ちください。何かご不明な点がございましたら、チャット・メールでお問合せください。", "updated_at" : ISODate("2019-04-19T06:58:19Z"), "created_at" : ISODate("2019-04-19T06:58:19Z") } | |
{ "_id" : ObjectId("5cb9718b3de6331b5b689401"), "is_sent" : 0, "thread_id" : 392511, "text" : "★購入完了のお知らせ★\r\n\r\nご購入いただき誠にありがとうございました。\r\n\r\n購入完了のメールが届いていなくても、このメッセージが届いた場合は、問題なくご注文が完了しています。\r\n\r\n会員のお客様は、MyLC(マイエルシー)からご注文履歴を確認することができるので、下記よりご確認ください。\r\n\r\nhttps://secure.lovecosmetic.net/lcmy/lcChum.php?apv1=\r\n\r\n商品お届けまで今しばらくお待ちください。何かご不明な点がございましたら、チャット・メールでお問合せください。", " |
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var fnInsertIframe = function(base_url, _args) { | |
var dfIframe = $.Deferred(); | |
_args.param = "top" | |
var url = base_url + "/web?" + $.param(_args) | |
if ($("#hidden-chatbot").length == 0) { | |
var iframe = document.createElement("iframe"); | |
iframe.style.display = "none"; | |
iframe.setAttribute("id", "hidden-chatbot"); | |
iframe.setAttribute('width', '0'); | |
iframe.setAttribute('height', '0'); |
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<script> | |
(function (c, s, p) { | |
if (typeof $ === "undefined") { | |
var e = document.createElement('script'); | |
e.async = 1;e.src = s + "/js/jquery.min.js"; | |
var t = document.getElementsByTagName('head')[0]; | |
t.parentNode.appendChild(e); | |
} | |
var fnAfterJquery = function () { |
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package main | |
import ( | |
"fmt" | |
) | |
// NewQueue returns a new queue with the given initial size. | |
func NewQueue(size int) *Queue { | |
return &Queue{ | |
nodes: make([]*Node, size), |
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package main | |
import ( | |
"fmt" | |
) | |
// MinMax comment | |
func MinMax(A []int) (int, int) { | |
min := A[0] | |
max := A[0] |
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package main | |
import ( | |
"fmt" | |
"strings" | |
) | |
func convert(s string, numRows int) string { | |
length := int(len(s)) |
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### Sơ lược: | |
![](https://images.viblo.asia/b3abf531-2cae-46f8-9ada-435a195c89ab.png) | |
![](https://images.viblo.asia/0d821119-6fcf-4580-8e1c-647047ae67b3.png) | |
- Kd-trees dùng để tìm kiếm các dữ liệu gần, liên quan nhất (neighbouring data points) trong miền không gian 2 chiều, hoặc nhiều chiều. | |
- Kd-trees thuộc họ **Nearest neighbor (NN) search**. | |
### Tóm tắt: | |
1) Cách build Kd-trees từ tranning data: | |
- chọn 1 chiều random, tìm toạ độ trung bình, chia data theo toạ độ đó, lặp lại. | |
2) Cách tìm các dữ liệu liên quan cho point (7,4) |
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{id: 847, targetable: "CuQnLGy7glkTRgCIuwlwJxyzpTUAbtO6U34xEkSO", targetable_type: 0, is_touch: 0,…} | |
1 | |
: | |
{id: 319, targetable: "46", targetable_type: 3, is_touch: 0, in_time: 1, note: "", operator_id: 1,…} | |
2 | |
: | |
{id: 1, targetable: "1", targetable_type: 1, is_touch: 0, in_time: 1, note: "", operator_id: 0,…} | |
3 | |
: | |
{id: 775, targetable: "41N8d2IDwu264m6QIL9B48LNrNWzYungJ5R9kT92", targetable_type: 0, is_touch: 0,…} |
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{ | |
"bool" : { | |
"must" : [ | |
{ | |
"bool" : { | |
"must" : [ | |
{ | |
"has_child" : { | |
"query" : { | |
"bool" : { |
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