投稿時間:2021-09-13 10:19:28 RSSフィード2021-09-13 10:00 分まとめ(25件)

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ROBOT	ロボスタ	ガンダム×未来技術『ガンダムオープンイノベーション』とは? チーフガンダムオフィサーらのインタビュー動画公開中	https://robotstart.info/2021/09/13/guda-goi.html	現実	2021-09-13 00:04:00
デザイン	コリス	Adobe CCユーザーに朗報 🎉 フォントワークスの人気フォントがAdobe Fontsに大量追加されました！	https://coliss.com/articles/build-websites/operation/work/adobe-fonts-update-202109.html	続きを読む	2021-09-13 00:36:44
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Facebook広告が公開できない	https://teratail.com/questions/359181?rss=all	Facebook広告が公開できない前提・実現したいことFacebook広告でインスタグラムを中心に広告を流したいと考えており、流す広告を作成中です。	2021-09-13 09:58:43
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	unityがガイジ過ぎてfor文を入れただけで13個もエラーを出します	https://teratail.com/questions/359180?rss=all	unityがガイジ過ぎてfor文を入れただけで個もエラーを出します前提・実現したいことここに質問の内容を詳しく書いてください。	2021-09-13 09:48:09
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	HTMLとBootstrapのh1～h6について	https://teratail.com/questions/359179?rss=all	HTMLとBootstrapのhhについてHTMLのhhタグについて基本的にh→nbsph→h→h→h→hと使用していくのが基本で、bootstrapで文字の大きさを変更する際lthgtlthgtでも変更できると思います。	2021-09-13 09:44:30
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	YouTube Data APIを使って最新順で動画を取得したい	https://teratail.com/questions/359178?rss=all	YouTubeDataAPIを使って最新順で動画を取得したい前提・実現したいこと現在、GASを使用して指定チャンネルの動画一覧から、動画概要欄に指定文字が含まれている動画のみを取得してGoogleスプレッドシートに書き出す処理を作成しています。	2021-09-13 09:40:20
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ifの条件式がよくわかりません	https://teratail.com/questions/359177?rss=all	alert	2021-09-13 09:26:50
AWS	AWSタグが付けられた新着投稿 - Qiita	AWS IoT CoreをRaspberry Piで使ってみた その3	https://qiita.com/cami_oshimo/items/1f56cb4c3b2f22b6ae53	AWSIoTCoreをRaspberryPiで使ってみたその概要AWSにはIoT機器と接続、管理するためのAWSIoTCoreというサービスがある公式にもハンズオンがあるが、最小限の手順、構成で動作を確かめてみる前回に引き続き温湿度センサーDHTのデータを送信することを試みる前回の記事RaspberryPiの操作ライブラリseeedpythondhtをインストールするpipinstallseeedpythondhtまずセンサー、ライブラリの動作を確認するコードを書いてみるdhtpyimportRPiGPIOasGPIOimportseeeddhtGPIOsetupGPIOINsensorseeeddhtDHThumitempsensorreadhumidityfformathumitemperaturefformattempprinthumidityprinttemp動作を確認してみる温度、湿度が順番に表示されるpythondhtpy前回使用したサンプルプログラムに組み込んでみるbasicPubSubpyfromAWSIoTPythonSDKMQTTLibimportAWSIoTMQTTClientimportloggingimporttimeimportargparseimportjsonimportRPiGPIOasGPIO追加importseeeddht追加GPIOsetupGPIOIN追加sensorseeeddhtDHT追加AllowedActionsbothpublishsubscribebasicPubSubpywhileTrueifargsmodebothorargsmodepublishhumitempsensorread追加humidityfformathumi追加temperaturefformattemp追加messagemessagemessageargsmessagemessagesequenceloopCountmessagetemptemp追加messagehumihumi追加messageJsonjsondumpsmessagemyAWSIoTMQTTClientpublishtopicmessageJsonifargsmodepublishprintPublishedtopicssntopicmessageJsonloopCounttimesleep修正したサンプルプログラムのbasicPubSubpyを実行するpiraspberrypiawsiotdevicesdkpythonsamplesbasicPubSubpythonbasicPubSubpyendpointabcabcabcatsiotapnortheastamazonawscomrootCAcertsAmazonRootCApemcertcertsabcabcabcabcabcabcabcabcabcabcabccertificatepemcrtkeycertsabcabcabcabcabcabcabcabcabcabcabcprivatepemkeyトピックsdktestPythonにPublishされていることを確認するAWSIoTCoreの操作テスト→MQTTクライアントでJSON形式のデータが到着していることを確認する課題seeedpythondhtから読みだした値を小数点以下桁で送信したかったが、Pythonでfformattempとしても反映されない。	2021-09-13 09:20:40
海外TECH	DEV Community	Using Generators in Python: The Why, The What, and The When	https://dev.to/jerrynsh/using-generators-in-python-the-why-the-what-and-the-when-55l	Using Generators in Python The Why The What and The WhenToday “what are Generators in Python and “what are Generators used for in Python are some of the most popular Python interview questions Often Generator is considered as one of the more intermediate concepts in Python If you are new to learning Python you may not have come across Generator before Here s a tip it has something to do with the use of yield statements inside a function In this post I am going to highlight some of the use cases reasons and advantages of using Generators in Python In short you should consider using Generators when dealing with large datasets with memory constraints Let s dive a little bit deeper shall we TL DR Consider using Generator when dealing with a huge dataset Consider using Generator in scenarios where we do not need to reiterate it more than once Generators give us lazy evaluation They are a great way to generate sequences in a memory efficient manner Why Should I Care About Using Generators Memory constraintsTo understand why you should use Generators we have to first understand that computers have a finite amount of memory RAM Whenever we are storing or manipulating variables lists etc all that is being stored inside our memory You might ask why do computer programs store them in memory Because it s the fastest way for us to write and retrieve data ScenariosHave you ever had to work with a list so large that you run into MemoryError Perhaps you have tried reading rows from a super large Excel or csv file All I remember was that performing these tasks is painfully slow or impossible What Is a Generator FunctionTo put it simply a Generator function is a special kind of function that returns many items The point here is that the items are returned one by one rather than all at once The main difference between a regular function and a Generator function lies in the use of return and yield statements in Python Generators give you lazy evaluationYou may have come across this statement But what does it really mean If you are familiar with Iterator a Generator function is essentially a function that behaves just like that Behind the scene Generators don t compute the value of each item when being instantiated Rather they compute it when we ask for it This is what people mean by Generators give you lazy evaluation As a result Generators allow us to process and deal with one value at a time without having to load everything in memory first When and Where Should I Use GeneratorsGenerators are great when you encounter problems that require you to read from a large dataset Reading from a large dataset means our computer or server would have to allocate memory for it The only condition to remember is that a Generator can only be iterated once In other words as long as we do not need the previous value from our dataset we can always use Generator Reading sizable CSVAnother common use case of using Generators is when we are working with large files such as Excel or CSV documents Without using a Generator function here s how we can write it Example of using a regular functionimport csvdef read csv from regular fn with open large dataset csv r as f reader csv reader f return row for row in reader result read csv from regular fn Output a b c x y z Upon running the example above we may experience some slowness or even MemoryError depending on our computers Looking at the code example above to generate the result the read csv from regular fn would open our CSV file and loads everything in memory in an instance This is not a good solution when working with larger files than our available memory Alternatively we could do this Example of using a Generator functionimport csvdef read csv from generator fn with open large dataset csv r as f reader csv reader f for row in reader yield row To get the same output as result We generate a list using our newly created Generator function result row for row in read csv from generator fn Output same as result a b c x y z In this scenario we use read csv from generator fn as our Generator function This new Generator opens our large CSV file loops through every row and yields each row at a time rather than all at once Here we would not run into any MemoryError or even any slowness due to memory constraints when reading data from our large dataset csv To check the memory usage in bytes we could do the following import sysprint sys getsizeof read csv from generator fn bytesprint sys getsizeof read csv from regular fn bytes Iterating through a large list array Another example where Generators are often used is where we intend to process values from a large list Example nums list comprehension i i for i in range sum nums list comprehension Depending on your computer you may encounter MemoryError or at least a couple of seconds of slowness when evaluating the expression above Like list comprehensions the Generator expression allows us to quickly create a Generator object without having to use the yield statement To cope with our memory constraint we could turn the code example above into a Generator expression This line of code below evaluates almost immediately Example nums generator i i for i in range lt generator object lt genexpr gt at xecc gt sum nums generator In Example i i for the entire range of is being evaluated and stored in memory beforehand It returns a full list In Example i i is only evaluated when being iterated one at a time It returns a Generator expression Remember Generators don t compute the value of each item when being instantiated The differences in memory usage are below import sysprint sys getsizeof nums generator bytesprint sys getsizeof nums list comprehension bytes When NOT To Use Generators We need the previous valuesA Generator can only be iterated once The example below shows that the Generator expression from nums generator can only be iterated once Using sum on it for the second time resulted in zero as the Generator was exhausted Continuing from Example sum nums generator sum nums generator because it can only be iterated once Dealing with relatively small filesWhen dealing with relatively small files or lists we may not want to use Generator as it might actually slow us down We can use our previous examples cProfile to profile the performance differences between list comprehension and Generator expression when summing the values up cProfile of summing using List Comprehension vs Generator Expression List Comprehension cProfile run sum i i for i in range function calls in seconds Ordered by standard name ncalls tottime percall cumtime percall filename lineno function lt string gt lt listcomp gt lt string gt lt module gt built in method builtins exec built in method builtins sum method disable of lsprof Profiler objects Generator Expression cProfile run sum i i for i in range function calls in seconds Ordered by standard name ncalls tottime percall cumtime percall filename lineno function lt string gt lt genexpr gt lt string gt lt module gt built in method builtins exec built in method builtins sum method disable of lsprof Profiler objects From our cProfile result above we can tell that using list comprehension is a lot faster provided we don t run into memory constraints Evidently if memory is not an issue we should stick with using regular functions or list comprehensions ConclusionIn summary Generator is an amazing tool in Python given the scenario where we do not need to reiterate it more than once As Generators give us lazy evaluation they are a great way to generate sequences in a memory efficient manner We should definitely consider using Generator when dealing with huge datasets to optimize our program Thank you for reading	2021-09-13 00:43:52
海外科学	BBC News - Science & Environment	Record number of environmental activists murdered	https://www.bbc.co.uk/news/science-environment-58508001?at_medium=RSS&at_campaign=KARANGA	rights	2021-09-13 00:02:30
金融	ニッセイ基礎研究所	「男女減少格差、最高エリアは10.5倍」新型コロナ禍２年目上半期、人口の社会減はどこで起こったのか（下）―新型コロナ人口動態解説(11)	https://www.nli-research.co.jp/topics_detail1/id=68715?site=nli	コロナ禍において男性が女性よりも社会減となったエリアも発生している。	2021-09-13 09:56:21
金融	ニッセイ基礎研究所	成約事例で見る東京都心部のオフィス市場動向（2021年上期）－「オフィス拡張移転DI」の動向	https://www.nli-research.co.jp/topics_detail1/id=68712?site=nli	そのなかで、オフィス拡張移転DIは、企業の拡張・縮小意欲が拮抗する水準で横ばいとなり、昨年来の低下に歯止めがかかる一方で、オフィス床解約の影響が大きく、空室率の上昇が続いていること業績悪化を理由とした縮小移転の動きは昨年で一巡し、コロナ禍を起点とした企業のオフィス再構築の動きが顕在化し始めた可能性があることAクラスビルのオフィス拡張移転DIが大幅に低下するなか、定借期限を迎える大口テナントの動向や企業のオフィス戦略の動きによっては、空室率が想定以上に上振れする可能性があることを確認した。	2021-09-13 09:48:11
金融	ニュース - 保険市場TIMES	ソニー生命、「シニアの生活意識調査2021」の結果を発表	https://www.hokende.com/news/blog/entry/2021/09/13/100000	ソニー生命、「シニアの生活意識調査」の結果を発表現在の楽しみ、位は「旅行」ソニー生命保険株式会社以下、ソニー生命は年月日、「シニアの生活意識調査」の結果を発表した。	2021-09-13 10:00:00
海外ニュース	Japan Times latest articles	North Korea tests new long-range cruise missiles that could hit Japan	https://www.japantimes.co.jp/news/2021/09/13/asia-pacific/north-korea-cruise-missiles-test/	defense	2021-09-13 09:37:09
海外ニュース	Japan Times latest articles	What will the next six months of the pandemic bring?	https://www.japantimes.co.jp/news/2021/09/13/world/pandemic-next-six-months/	Detail Nothing	2021-09-13 09:10:43
ニュース	BBC News - Home	Record number of environmental activists murdered	https://www.bbc.co.uk/news/science-environment-58508001?at_medium=RSS&at_campaign=KARANGA	rights	2021-09-13 00:02:30
ニュース	BBC News - Home	US Open: Novak Djokovic loses to Daniil Medvedev in New York	https://www.bbc.co.uk/sport/tennis/58540110?at_medium=RSS&at_campaign=KARANGA	US Open Novak Djokovic loses to Daniil Medvedev in New YorkRussia s Daniil Medvedev wins his first Grand Slam title by shattering Novak Djokovic s hopes of completing a calendar sweep of the majors in a one sided US Open final	2021-09-13 00:08:01
ニュース	BBC News - Home	Britney Spears announces engagement to Sam Asghari	https://www.bbc.co.uk/news/entertainment-arts-58540571?at_medium=RSS&at_campaign=KARANGA	asghari	2021-09-13 00:15:49
ニュース	BBC News - Home	Jesse Lingard takes control of a Rainbow Six Siege esports team	https://www.bbc.co.uk/news/newsbeat-58507739?at_medium=RSS&at_campaign=KARANGA	online	2021-09-13 00:04:14
LifeHuck	ライフハッカー［日本版］	Macでスクリーンショットの保存先を変更する方法	https://www.lifehacker.jp/2021/09/241795how-to-change-your-macs-default-save-location-for-scree.html	方法	2021-09-13 10:00:00
GCP	Google Cloud Platform Japan 公式ブログ	BungkusIT が Google Maps Platform を使用し、マレーシアの 100 万人以上の顧客に代わり買い物を済ませ、荷物を配達したその方法とは	https://cloud.google.com/blog/ja/products/maps-platform/how-bungkusit-uses-google-maps-platform-run-errands-and-deliver-packages-over-one-million-customers-across-malaysia/	オンデマンド配達サービスを提供することで、お客様の生活をもっと楽にしたいと当社は考えています。	2021-09-13 01:00:00
北海道	北海道新聞	メドベージェフ、四大大会初優勝　男子単、ジョコビッチは年間全制覇逃す	https://www.hokkaido-np.co.jp/article/588494/	全米オープン	2021-09-13 09:19:09
北海道	北海道新聞	香川真司、開幕戦に先発出場　ギリシャ１部のＰＡＯＫ	https://www.hokkaido-np.co.jp/article/588506/	先発出場	2021-09-13 09:15:00
北海道	北海道新聞	士別市長選、渡辺英次氏が初当選　新人同士の一騎打ち制す	https://www.hokkaido-np.co.jp/article/588502/	一騎打ち	2021-09-13 09:04:00
GCP	Cloud Blog JA	BungkusIT が Google Maps Platform を使用し、マレーシアの 100 万人以上の顧客に代わり買い物を済ませ、荷物を配達したその方法とは	https://cloud.google.com/blog/ja/products/maps-platform/how-bungkusit-uses-google-maps-platform-run-errands-and-deliver-packages-over-one-million-customers-across-malaysia/	オンデマンド配達サービスを提供することで、お客様の生活をもっと楽にしたいと当社は考えています。	2021-09-13 01:00:00