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データエンジニアé“ã®ä¿ºã®ãƒã‚¤ãƒ–ル
先人ã®çŸ¥æµã«å¦ã¶ データエンジニアé“ã§ã€æœ¬å½“ã«è‰¯ã‹ã£ãŸï¼èªã¿ç‰©ã‚’ã€ä¸å®šæœŸã«è¿½è¨˜ã—ã¦ã„ã。 A Beginner’s Guide to Data Engineering — Part I データエンジニアをã“ã‚Œã‹ã‚‰å§‹ã‚る人ã«ã€å¿…ãšè–¦ã‚る記事。データエンジニアã®åŸºæœ¬ã‚’å¦ã¹ã‚‹ã‹ã¤ã€ã©ã†ã„ã†ä¸–ç•Œã«åºƒãŒã£ã¦ã„ãã®ã‹ã¾ã§ã€ä¸€æ°—ã«å¦ã¹ã‚‹ã®ã§ã¨ã¦ã‚‚良ã„。 Functional Data Engineering — a modern paradigm for batch data processing 関数型パラダイムを使ã£ãŸãƒ‡ãƒ¼ã‚¿ãƒ‘イプラインã®æ§‹ç¯‰æ–¹æ³•ã€‚ã“れをåˆã‚ã¦èªã‚“ã 時ã®è¡æ’ƒã¯ä»Šã§ã‚‚忘れãªã„ã—ã€ãƒ•ãƒ«ã‚¹ã‚¯ãƒ©ãƒƒãƒã‹ã‚‰dbtを使ã£ãŸãƒ‡ãƒ¼ã‚¿ãƒ‘イプラインã«ãªã£ã¦ã‚‚å¥åœ¨ãªè¨è¨ˆæ‰‹æ³•ã€‚ Engineers Shouldn’t Write ETL: A Guide to Building a High Function
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Data Manipulation: Pandas vs Rust
Introduction Pandas is the main Data analysis package of Python. For many reasons, Native Python has very poor performance on data analysis without vectorizing with NumPy and the likes. And historically, Pandas has been created by Wes McKinney to package those optimisations in a nice API to facilitate data analysis in Python. This, however, is not necessary for Rust. Rust has great data performanc
iOS標準アプリ「ヘルスケアã€ã‹ã‚‰ãƒ‡ãƒ¼ã‚¿ã‚’書ã出ã—csvã«å¤‰æ› - u++ã®å‚™å¿˜éŒ²
ã¯ã˜ã‚㫠データã®æ¦‚è¦ ãƒ‡ãƒ¼ã‚¿ã®å–り出ã—æ–¹ ヘルスケアアプリã‹ã‚‰XMLファイルを書ã出㙠XMLファイルをcsvファイルã«å¤‰æ›ã™ã‚‹ 分æžä¾‹ ãŠã‚ã‚Šã« ã¯ã˜ã‚㫠本記事ã§ã¯ã€iOS標準アプリ「ヘルスケアã€ã‹ã‚‰ãƒ‡ãƒ¼ã‚¿ã‚’書ã出ã—ã€csvã«å¤‰æ›ã™ã‚‹æ–¹æ³•ã‚’ã¾ã¨ã‚ã¾ã™ã€‚ データã®æ¦‚è¦ ãƒ˜ãƒ«ã‚¹ã‚±ã‚¢ã‚¢ãƒ—ãƒªã¯iOSã«æ¨™æº–ã§æ載ã•ã‚Œã€æ—¥å¸¸ã®æ©æ•°ãªã©ãŒè¨˜éŒ²ã•ã‚Œã¦ã„ã¾ã™ã€‚自分ã«èº«è¿‘ãªãƒ‡ãƒ¼ã‚¿ãªã®ã§ã€åˆ†æžã®ä»®èª¬ã‚‚ç«‹ã¦ã‚„ã™ãã€ãƒ‡ãƒ¼ã‚¿åˆ†æžã®é¡Œæã¨ã—ã¦ä¾¿åˆ©ã‹ã¨æ€ã„ã¾ã™ã€‚ データã®å–り出ã—æ–¹ æ‰‹é †ã¯ä»¥ä¸‹ã®é€šã‚Šã§ã™ã€‚ ヘルスケアアプリã‹ã‚‰XMLファイルを書ã出㙠XMLファイルをcsvファイルã«å¤‰æ›ã™ã‚‹ ヘルスケアアプリã‹ã‚‰XMLファイルを書ã出㙠ã¾ãšã¯ãƒ˜ãƒ«ã‚¹ã‚±ã‚¢ã‚¢ãƒ—リã‹ã‚‰ãƒ‡ãƒ¼ã‚¿ã‚’書ã出ã—ã¾ã™ã€‚ã“ã®æ™‚点ã§csvå½¢å¼ã«ãªã£ã¦ã„ã‚‹Pythonãªã©ã§æ‰±ã„ã‚„ã™ã„ã®ã§ã™ãŒã€XMLファイルã§ã—ã‹æ›¸ã出ã™ã“ã¨ã¯ã§ãã¾ã›ã‚“。 ã¾ãšã¯ã€ã‚«ãƒ¬ãƒ³
交通センサスã®è§£æžã¨å¯è¦–化 - ponkotuyã®ãƒ–ãƒã‚°
æ¦‚è¦ ä»Šå›žã¯äº¤é€šã‚»ãƒ³ã‚µã‚¹ã®è§£æžã—ã¦å¸‚区町æ‘é–“ã®äº¤é€šæµå‹•ã‚’解æžã—ã¦æ—¥æœ¬ã®å¸‚区町æ‘をグルーピングã—ã€GISã®ä»•çµ„ã¿ã‚’使ã£ã¦å¯è¦–化ã™ã‚‹ã¨ã“ã‚ã¾ã§ã‚„ã£ãŸã®ã§ã€ãã®è©±ã‚’ã—ã¾ã™ã€‚ モãƒãƒ™ãƒ¼ã‚·ãƒ§ãƒ³ ãã‚‚ãã‚‚ãªã‚“ã§ãã‚“ãªã“ã¨ã‚’始ã‚ãŸã‹ã¨ã„ã†ã¨ã€ç‰¹ã«ç¦å³¶çœŒãªã‚“ã§ã™ãŒã€ŒçœŒå¢ƒã®è¨å®šãŒé›‘ã˜ã‚ƒã?ã€ã¿ãŸã„ãªç´ 朴ãªç–‘å•ãŒã‚ã£ãŸã‹ã‚‰ã§ã™ã€‚ ã“ã‚Œã¯æ´å²çš„事実ã¨ã—ã¦ã€å®Ÿéš›ã«å»ƒè—©ç½®çœŒã®æ”¿æ²»çš„ãªã‚´ã‚¿ã‚´ã‚¿ã®ä¸ã§æ±ºã¾ã£ãŸçœŒå¢ƒãŒå¤‰æ›´ã•ã‚Œãšã«ä»Šã«è‡³ã£ã¦ã„ã‚‹ã®ã§å½“然ãã†ãªã‚“ã§ã™ãŒã€ ã¨ãªã‚‹ã¨ã€Œã˜ã‚ƒã‚ãã“らã¸ã‚“åˆç†çš„ã«çœŒå¢ƒã‚’決ã‚ãŸã‚‰ã©ã†ãªã‚‹ã‚“?ã€ã¨ã„ã†ç–‘å•ãŒã‚ã„ã¦ãã‚‹ã‚ã‘ã§ã™ã€‚ 多ãã®åœ°å…ƒæ°‘ãŒç´å¾—ã™ã‚‹çœŒå¢ƒã‚’考ãˆã‚‹ã¨ã€ 「大ããªè²·ã„物をã™ã‚‹ã¨ãã«è¡Œãè¡—ã‚„ã€é ãã«è¡Œãã¨ãã«ã„ãã¨ãã«çµŒç”±ã™ã‚‹è¡—ãŒåŒã˜éƒ½é“府県ã«ãªã‚‹ã¨ã€ã¾ã‚ã¾ã‚ã†ã¾ãã„ãã ã‚ã†ã€ ã¨ã„ã†ä»®èª¬ã‚’ã¾ãšç«‹ã¦ã¾ã™ã€‚ ãã®ä¸Šã§ã€ãã®åœ°åŸŸã®ã‚°ãƒ«ãƒ¼ãƒ—を作るã®ã§ã‚ã‚Œã°ã€æœ€ã‚‚交通æµå‹•ã®å¤šã„地域を繋
Perlã®printデãƒãƒƒã‚°ã‚’シュッã¨è¦‹ã‚„ã™ãã™ã‚‹ 〜Data::Printer編〜 - Masteries
Perl Advent Calendar 2014ã®7日目ã®è¨˜äº‹ã§ã™. 宜ã—ããŠé¡˜ã„ã—ã¾ã™. ã•ã¦, 昨日ã®è¨˜äº‹ã¯@FromAtomã•ã‚“ã®ï½¢Perlã®printデãƒãƒƒã‚°ã‚’シュッã¨è¦‹ã‚„ã™ãã™ã‚‹ï½£ã§ã—ãŸ. printデãƒãƒƒã‚°ã¯ãƒ‡ãƒãƒƒã‚°ã®ä¸ã§ã‚‚基礎ä¸ã®åŸºç¤Ž, ã¨ã‚Šã‚ãˆãšè©°ã¾ã£ãŸã‚‰printデãƒãƒƒã‚°ã§è©¦ã—ã¦ã¿ã‚‹... ã¨ã„ã†æ–¹ã¯çµæ§‹å¤šã„ã®ã§ã¯ãªã„ã§ã—ょã†ã‹. 昨日ã®è¨˜äº‹ã§ã¯Data::Dumperを紹介ã•ã‚Œã¦ã„ã¾ã—ãŸãŒ, デãƒãƒƒã‚°ã«å½¹ç«‹ã¤ãƒ€ãƒ³ãƒ—用ã®ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã¯ä»–ã«ã‚‚ã‚ã‚Šã¾ã™. 今日ã¯ãã®ä¸ã®1ã¤, Data::Printerを紹介ã—ãŸã„ã¨æ€ã„ã¾ã™. Data::Printerã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ« cpanmコマンドãŒä½¿ãˆã‚Œã°ç°¡å˜ã§ã™. $ cpanm Data::Printer ã“ã“ãŒData::Dumperã¨æ¯”ã¹ãŸæ™‚ã®Data::Printerã®å¼±ç‚¹ã§ã™. ã¤ã¾ã‚Šï½¢ä¾¿åˆ©ã ã‘ã©, コアモジュールã˜ã‚ƒãªã„
テスト用マイナンãƒãƒ¼ã®ãƒ€ãƒŸãƒ¼ãƒ‡ãƒ¼ã‚¿ - Qiita
require 'set' class MyNumber def self.generate_valid_individual_number(n = 1) generator = ValidMyNumberGenerator.new generate(n, generator) end def self.generate_invalid_individual_number(n = 1) generator = InvalidMyNumberGenerator.new generate(n, generator) end def self.generate(n, generator) numbers = Set.new numbers << generator.individual_number while numbers.length < n numbers.map(&:join) end
Separation of business logic and data access in django
I am writing a project in Django and I see that 80% of the code is in the file models.py. This code is confusing and, after a certain time, I cease to understand what is really happening. Here is what bothers me: I find it ugly that my model level (which was supposed to be responsible only for the work with data from a database) is also sending email, walking on API to other services, etc. Also, I
Ruby ã® Object Data Dumper - 俺ãŸã¡ã®ãƒ–ãƒã‚°
プリントデãƒãƒƒã‚°ãŒå¤§å¥½ãã ï¼ï¼ï¼ä½•ã¯ãªãã¨ã‚‚ã¨ã‚Šã‚ãˆãšæ¨™æº–出力ã«åã„ã¦ãƒ‡ãƒã‚°ï¼ï¼ï¼ï¼ï¼ï¼ï¼ï¼ï¼ã£ã¦ã„ã†ã‚ˆã†ãªã“ã¨ã¯ã¿ãªã•ã‚“ã«ãŠã‹ã‚Œã¾ã—ã¦ã‚‚å°‘ãªã‹ã‚‰ãšã‚ã‚‹ã®ã§ã¯ãªã„ã§ã—ょã†ã‹ã€‚ プリントデãƒãƒƒã‚°ã‚’è¡Œã†å ´åˆã€å˜ç´”ã«å¤‰æ•°ã«ä½•ãŒå…¥ã£ã¦ã„ã‚‹ã‹ã¨ã„ã†ã‚ˆã‚Šã‚‚ã€ã‚ªãƒ–ジェクトã®çŠ¶æ…‹ã¨ã‹ã‚’見ãŸã„ã“ã¨ãŒå¤šã„ã‹ã¨æ€ã†ã€‚ ãã†ã„ã†ã¨ãã®ãŸã‚ã®ãƒ©ã‚¤ãƒ–ラリã¨ã—ã¦ã€Ruby ã ã¨ã€p, pp ã¯çµ„ã¿è¾¼ã¿ã€ap ã¯ã‚‚ã†å®šç•ªåŒ–ã—ã¦ã¦ã¿ã‚“ãªä½¿ã£ã¦ã‚‹ã¨æ€ã†ã€‚ ã§ã€ddp ã£ã¦ã®ã‚‚ã‚る。http://hisaichi5518.hatenablog.jp/entry/2014/11/05/154949 é©å½“ãªã‚¯ãƒ©ã‚¹ã‚’ã§ã£ã¡ä¸Šã’ã¦ãã‚Œãžã‚Œã«é£Ÿã‚ã›ã¦ã¿ã‚‹ ã“ã‚“ãªã‚¯ãƒ©ã‚¹ãŒã‚ã£ãŸã¨ã™ã‚‹ã€‚ インスタンスを作ã£ã¦ã€ã‚¤ãƒ³ã‚¹ã‚¿ãƒ³ã‚¹è‡ªä½“ã€ã‚¤ãƒ³ã‚¹ã‚¿ãƒ³ã‚¹å¤‰æ•°ã€ã‚¤ãƒ³ã‚¹ã‚¿ãƒ³ã‚¹ãƒ¡ã‚½ãƒƒãƒ‰ã‚’ãã‚Œãžã‚Œã®ãƒ©ã‚¤ãƒ–ラリã«é£Ÿã‚ã›ã¦ã¿ã¦ã€ã©ã‚“ãªæ„Ÿã˜ã«è¡¨ç¤ºã•ã‚Œã‚‹ã‹è¦‹ã¦ã¿ã¾ã›ã†ã€‚
Ruby 㨠tumugi ã«ã‚ˆã‚‹ãƒ‡ãƒ¼ã‚¿ãƒ‘イプライン構築 - Qiita
データを扱ã†ä»•äº‹ã‚’ã—ã¦ã„ã‚‹ã¨ã€ä½•ã‚‰ã‹ã®å½¢ã§ãƒ‡ãƒ¼ã‚¿ã‚’ã‚ã‚‹é †åºã«æ²¿ã£ã¦å‡¦ç†ã™ã‚‹ Workflow = データパイプラインを構築ã™ã‚‹å¿…è¦ã«ãªã‚‹å ´é¢ã«å‡ºãã‚ã™ã“ã¨ãŒå¤šã„ã¨æ€ã„ã¾ã™ã€‚ ã“ã†ã—ãŸå‡¦ç†ã«é©ç”¨ã§ãるソフトウェアã¯æ—¢ã«ã„ãã¤ã‹å˜åœ¨ã™ã‚‹ã®ã§ã™ãŒã€è‡ªåˆ†ãŒä»•äº‹ã§ä½¿ã†ä¸Šã§ãƒžãƒƒãƒã™ã‚‹ã‚‚ã®ãŒãªã‹ã£ãŸã®ã§ã€tumugi ã‚’ Ruby ã®ãƒ©ã‚¤ãƒ–ラリを作æˆã—〠gem ã¨ã—ã¦å…¬é–‹ã—ã¾ã—ãŸã€‚ãƒã‚´ã¯ã“ã‚“ãªæ„Ÿã˜ã€‚ Workflow Engine ã‚’ã¤ãã‚ã†ï¼ シリーズ連載ã¯ã€å…ƒã€…ã“ã®ãƒ©ã‚¤ãƒ–ラリã®è¨è¨ˆã‚’æ•´ç†ã™ã‚‹ãŸã‚ã«æ›¸ã„ã¦ã„ãŸè¨˜äº‹ã§ã—ãŸã€‚ã¾ã ã€æœªå®Œã§ã™ãŒèˆˆå‘³ã®ã‚ã‚‹æ–¹ã¯ãã¡ã‚‰ã‚‚ãŠèªã¿ãã ã•ã„。 注釈 ã“ã®è¨˜äº‹ã¯ tumugi ㌠Python ã§æ›¸ã‹ã‚ŒãŸãƒ¯ãƒ¼ã‚¯ãƒ•ãƒãƒ¼ã‚¨ãƒ³ã‚¸ãƒ³ã§ã‚ã‚‹ Luigi ã«å¼·ã影響ã•ã‚Œã¦æ›¸ã„ãŸã“ã¨ã‹ã‚‰ã€å¯¾æ¯”ã¨ã—ã¦åˆ†ã‹ã‚Šã‚„ã™ã„ãŸã‚ Building Data Pilelines with Pytho
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YouTube Data Tools
GitHub - djblue/portal: A clojure tool to navigate through your data.
Registry of Open Data on AWS
GitHub - xakepnz/BLUELAY: Searches online paste sites for certain search terms which can indicate a possible data breach.
GitHub - ponkotuy/traffic: Read traffic on city boundaries from census.
This bookmarklet gives you a code editor in your browser with a single click.
GitHub - arkadiyt/bounty-targets-data: This repo contains hourly-updated data dumps of bug bounty platform scopes (like Hackerone/Bugcrowd/Intigriti/etc) that are eligible for reports
O'Reilly Media - Technology and Business Training
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