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  | 2025-10-25 21:55:23 5731 0000007a_00001038.wal.lz4 | |
| 2025-10-25 21:55:23 1928 0000007b_00000000.wal.lz4 | |
| 2025-10-25 21:55:43 5768 0000007b_00001038.wal.lz4 | |
| 2025-10-25 21:55:53 11974 0000007b_000070c8.wal.lz4 | |
| 2025-10-25 21:56:23 1928 0000007c_00000000.wal.lz4 | |
| 2025-10-26 07:16:56 586 0000007c_00001038.wal.lz4 | |
| 2025-10-26 07:18:05 1928 0000007d_00000000.wal.lz4 | |
| 2025-10-26 07:34:45 5891 0000007d_00001038.wal.lz4 | |
| 2025-10-26 07:34:46 1928 0000007e_00000000.wal.lz4 | |
| 2025-10-26 07:34:55 7597 0000007e_00001038.wal.lz4 | 
  
    
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  | #![feature(time2)] | |
| use std::time::Instant; | |
| use std::thread; | |
| use std::sync::mpsc; | |
| use std::io; | |
| struct ScopedPerformanceBlock<'a> { | |
| sender: &'a mpsc::Sender<u32>, | |
| creation_time: Instant, | |
| } | 
  
    
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  | import json | |
| import argparse | |
| import numpy as np | |
| from sklearn.feature_extraction import DictVectorizer | |
| from sklearn.feature_extraction.text import CountVectorizer | |
| from sklearn.linear_model import LogisticRegression | |
| from sklearn.preprocessing import LabelEncoder | 
  
    
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  | import json | |
| from flask import Flask, url_for, redirect, session | |
| from flask_login import (UserMixin, login_required, login_user, logout_user, current_user) | |
| from flask_googlelogin import GoogleLogin | |
| users = {} | |
| app = Flask(__name__) | 
  
    
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  | @{ | |
| Layout = null; | |
| } | |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta http-equiv="X-UA-Compatible" content="IE=9"/> | |
| <title>Title</title> | |
| <link href="@Url.Content("~/Content/bootstrap.css")" rel="stylesheet" type="text/css" /> | 
  
    
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  | /// Minimal generic min heap and priority queue implementation in C#, in less than 100 lines of code | |
| using System; | |
| using System.Collections.Generic; | |
| class MinHeap<T> where T : IComparable<T> | |
| { | |
| private List<T> array = new List<T>(); | |
| public void Add(T element) | 
  
    
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  | from __future__ import print_function | |
| from scipy.sparse import * | |
| from sklearn.decomposition import TruncatedSVD | |
| import matplotlib.pyplot as plt | |
| from matplotlib import cm as CM | |
| import numpy as np | |
| import time | |
| class Timer(object): | 
  
    
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  | class node: | |
| def __init__(self): | |
| self.is_end = False | |
| self.table = {} | |
| def add(self, c): | |
| if c not in self.table: | |
| self.table[c] = node() | |
| return self.table[c] | 
  
    
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  | <html> | |
| <head> | |
| <title>Styling thing</title> | |
| <style type="text/css"> | |
| .riParent {border: 1px dotted gray} | |
| .riTitle {font-size:larger} | |
| .riText {font-size:smaller; font-style:italic; color: #AAAAAA; clear: both} | |
| .riReject {} | |
| .riAccept {} |