Neko Null jerrylususu

## perform-transform.js
const ts = require("typescript");
const {readFileSync} = require("fs");

const filename = "source.ts";
// tsconfig
const options = {"target": "ESNext",
"module": "ESNext",
"moduleResolution": "node"}
const compilerHost = {
  ...ts.createCompilerHost(options),

## BENCHMARK.txt
## method
disable line no / file name logging: comment out line 10~13 in `index.js`
benchmark use `gocannon`: ./gocannon http://localhost:3000 -d 10s -c 50

## summary
without: 3495 req/s
with: 3204 req/s
perf cost: ~8.3%

## without line no / file name logging

## Metro_Cycles_README.txt
原帖：https://bgm.tv/group/topic/375970
TLDR：本 gist 试图找出深圳地铁图上的最长环

新算法运行说明
1. 把 `metroStationsList.js` 里的站点信息单独存储成一个 `all_lines.json`
2. 运行 `prepare_graph.py`
3. 运行 `find_graphillion.py`
4. 运行 `decode_result.py`


## PyItertoolPermutation.java
public class PyItertoolPermutation {
    public static void main(String[] args) {
        char[] arr = {'A', 'B', 'C', 'D'};
        int r = 2;
        dfs(0, arr, r);

    }

    public static void dfs(int changing_idx, char[] arr, int r) {
        if (changing_idx == r){

## cut.py

# WARNING: NOT QUITE WORKING...

import sys
import subprocess
import bisect
from pathlib import Path

def run_command(command_list):
    success = True

## bgm.ipynb

      
              4 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                jerrylususu
                / bgm.ipynb
            
            
              Last active
              January 19, 2022 20:36
            
              
                Bangumi x IMDB
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## generate_pdf_with_toc.py
import json
import toml
from pdftocgen.recipe import extract_toc, Recipe
from fitzutils import ToCEntry, dump_toc, open_pdf
from pdftocio.tocio import write_toc

# requiremnets
# ----------------------------
# ruquire `pdf.tocgen`
# https://github.com/Krasjet/pdf.tocgen

## demo.html
<!DOCTYPE html>
<html lang="cmn-Hans">
  <head>
    <meta charset="utf-8">
    <title>Hello!</title>
    <style id="dark-mode-theme" disabled>
    html {
        background-color: #ebebeb !important;
    }


## emoji-ranges.txt
# Note
# some codepoints you might want to remove:
# u+00a9: copyright
# u+00ae: registered

# Regex

(\u00a9|\u00ae|\u203c|\u2049|\u20e3|\u2122|\u2139|[\u2194-\u2199]|[\u21a9-\u21aa]|[\u231a-\u231b]|\u2328|\u23cf|[\u23e9-\u23f3]|[\u23f8-\u23fa]|\u24c2|[\u25aa-\u25ab]|\u25b6|\u25c0|[\u25fb-\u25fe]|[\u2600-\u2604]|\u260e|\u2611|[\u2614-\u2615]|\u2618|\u261d|\u2620|[\u2622-\u2623]|\u2626|\u262a|[\u262e-\u262f]|[\u2638-\u263a]|\u2640|\u2642|[\u2648-\u2653]|[\u265f-\u2660]|\u2663|[\u2665-\u2666]|\u2668|\u267b|[\u267e-\u267f]|[\u2692-\u2697]|\u2699|[\u269b-\u269c]|[\u26a0-\u26a1]|\u26a7|[\u26aa-\u26ab]|[\u26b0-\u26b1]|[\u26bd-\u26be]|[\u26c4-\u26c5]|\u26c8|[\u26ce-\u26cf]|\u26d1|[\u26d3-\u26d4]|[\u26e9-\u26ea]|[\u26f0-\u26f5]|[\u26f7-\u26fa]|\u26fd|\u2702|\u2705|[\u2708-\u270d]|\u270f|\u2712|\u2714|\u2716|\u271d|\u2721|\u2728|[\u2733-\u2734]|\u2744|\u2747|\u274c|\u274e|[\u2753-\u2755]|\u2757|[\u2763-\u2764]|[\u2795-\u2797]|\u27a1|\u27b0|\u27bf|[\u2934-\u2935]|[\u2b05-\u2b07]|[\u2b1b-\u2b1c]|\u2b50|\u2b55|\u3030|\u

## run.sh
# as of writing (2021/7/3), here is a list of the version of latest packages (arch=linux64):
# tensorflow-gpu: 2.4.0 (anaconda)
# cudnn: 8.2.1 (conda-forge)
# cudatoolkit: 11.0.221 (anaconda)

# step 1: create new conda environment, install python & cudatoolkit
conda create -n tf_25_new python=3.8 cudatoolkit=11.0.221
conda activate tf_25_new

# step 2: install cudann from conda forge
	const ts = require("typescript");
	const {readFileSync} = require("fs");

	const filename = "source.ts";
	// tsconfig
	const options = {"target": "ESNext",
	"module": "ESNext",
	"moduleResolution": "node"}
	const compilerHost = {
	...ts.createCompilerHost(options),
	## method
	disable line no / file name logging: comment out line 10~13 in `index.js`
	benchmark use `gocannon`: ./gocannon http://localhost:3000 -d 10s -c 50

	## summary
	without: 3495 req/s
	with: 3204 req/s
	perf cost: ~8.3%

	## without line no / file name logging
	原帖：https://bgm.tv/group/topic/375970
	TLDR：本 gist 试图找出深圳地铁图上的最长环

	新算法运行说明
	1. 把 `metroStationsList.js` 里的站点信息单独存储成一个 `all_lines.json`
	2. 运行 `prepare_graph.py`
	3. 运行 `find_graphillion.py`
	4. 运行 `decode_result.py`
	public class PyItertoolPermutation {
	public static void main(String[] args) {
	char[] arr = {'A', 'B', 'C', 'D'};
	int r = 2;
	dfs(0, arr, r);

	}

	public static void dfs(int changing_idx, char[] arr, int r) {
	if (changing_idx == r){

	# WARNING: NOT QUITE WORKING...

	import sys
	import subprocess
	import bisect
	from pathlib import Path

	def run_command(command_list):
	success = True
	import json
	import toml
	from pdftocgen.recipe import extract_toc, Recipe
	from fitzutils import ToCEntry, dump_toc, open_pdf
	from pdftocio.tocio import write_toc

	# requiremnets
	# ----------------------------
	# ruquire `pdf.tocgen`
	# https://github.com/Krasjet/pdf.tocgen
	<!DOCTYPE html>
	<html lang="cmn-Hans">
	<head>
	<meta charset="utf-8">
	<title>Hello!</title>
	<style id="dark-mode-theme" disabled>
	html {
	background-color: #ebebeb !important;
	}
	# Note
	# some codepoints you might want to remove:
	# u+00a9: copyright
	# u+00ae: registered

	# Regex

	(\u00a9\|\u00ae\|\u203c\|\u2049\|\u20e3\|\u2122\|\u2139\|[\u2194-\u2199]\|[\u21a9-\u21aa]\|[\u231a-\u231b]\|\u2328\|\u23cf\|[\u23e9-\u23f3]\|[\u23f8-\u23fa]\|\u24c2\|[\u25aa-\u25ab]\|\u25b6\|\u25c0\|[\u25fb-\u25fe]\|[\u2600-\u2604]\|\u260e\|\u2611\|[\u2614-\u2615]\|\u2618\|\u261d\|\u2620\|[\u2622-\u2623]\|\u2626\|\u262a\|[\u262e-\u262f]\|[\u2638-\u263a]\|\u2640\|\u2642\|[\u2648-\u2653]\|[\u265f-\u2660]\|\u2663\|[\u2665-\u2666]\|\u2668\|\u267b\|[\u267e-\u267f]\|[\u2692-\u2697]\|\u2699\|[\u269b-\u269c]\|[\u26a0-\u26a1]\|\u26a7\|[\u26aa-\u26ab]\|[\u26b0-\u26b1]\|[\u26bd-\u26be]\|[\u26c4-\u26c5]\|\u26c8\|[\u26ce-\u26cf]\|\u26d1\|[\u26d3-\u26d4]\|[\u26e9-\u26ea]\|[\u26f0-\u26f5]\|[\u26f7-\u26fa]\|\u26fd\|\u2702\|\u2705\|[\u2708-\u270d]\|\u270f\|\u2712\|\u2714\|\u2716\|\u271d\|\u2721\|\u2728\|[\u2733-\u2734]\|\u2744\|\u2747\|\u274c\|\u274e\|[\u2753-\u2755]\|\u2757\|[\u2763-\u2764]\|[\u2795-\u2797]\|\u27a1\|\u27b0\|\u27bf\|[\u2934-\u2935]\|[\u2b05-\u2b07]\|[\u2b1b-\u2b1c]\|\u2b50\|\u2b55\|\u3030\|\u
	# as of writing (2021/7/3), here is a list of the version of latest packages (arch=linux64):
	# tensorflow-gpu: 2.4.0 (anaconda)
	# cudnn: 8.2.1 (conda-forge)
	# cudatoolkit: 11.0.221 (anaconda)

	# step 1: create new conda environment, install python & cudatoolkit
	conda create -n tf_25_new python=3.8 cudatoolkit=11.0.221
	conda activate tf_25_new

	# step 2: install cudann from conda forge