投稿時間:2023-08-01 15:16:28 RSSフィード2023-08-01 15:00 分まとめ(19件)

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python Pythonタグが付けられた新着投稿 - Qiita 【深層学習】TabNetの使い方 https://qiita.com/Matsuda_Takumi/items/8a752534d671fb4e477a kaggle 2023-08-01 14:12:17
Ruby Rubyタグが付けられた新着投稿 - Qiita RSpecを実行するとWebdrivers::VersionErrorが発生する場合の対処方法 https://qiita.com/jnchito/items/f994dd3ac2cdc39bff8c etofindlatestpointrelease 2023-08-01 14:34:07
Ruby Railsタグが付けられた新着投稿 - Qiita RSpecを実行するとWebdrivers::VersionErrorが発生する場合の対処方法 https://qiita.com/jnchito/items/f994dd3ac2cdc39bff8c etofindlatestpointrelease 2023-08-01 14:34:07
技術ブログ Developers.IO Figmaにおけるバージョン管理というタイトルで発表しました #クラスメソッド勉強会 https://dev.classmethod.jp/articles/versioning-in-figma-at-cm-study-meeting-in-okayama/ githubfl 2023-08-01 05:15:30
海外TECH DEV Community Understanding Node.js Streams https://dev.to/amplication/understanding-nodejs-streams-534o Understanding Node js StreamsNode js is a powerful JavaScript runtime that allows developers to build scalable and efficient applications One key feature that sets Node js apart is its built in support for streams Streams are a fundamental concept in Node js that enable efficient data handling especially when dealing with large amounts of information or working with data in real time In this article we will explore the concept of streams in Node js understand the different types of streams available Readable Writable Duplex and Transform and discuss best practices for working with streams effectively What are Node js Streams Streams are a fundamental concept in Node js applications enabling efficient data handling by reading or writing input and output sequentially They are handy for file operations network communications and other forms of end to end data exchange The unique aspect of streams is that they process data in small sequential chunks instead of loading the entire dataset into memory at once This approach is highly beneficial when working with extensive data where the file size may exceed the available memory Streams make it possible to process data in smaller pieces making it feasible to work with larger files Source As depicted in the above image data is typically read in chunks or as a continuous flow when reading from a stream Data chunks read from the stream can be stored in buffers Buffers provide temporary storage space for holding the chunks of data until they can be processed further To further illustrate this concept consider the scenario of a live stock market data feed In financial applications real time updates of stock prices and market data are crucial for making informed decisions Instead of fetching and storing the entire data feed in memory which can be substantial and impractical streams enable the application to process the data in smaller continuous chunks The data flows through the stream allowing the application to perform real time analysis calculations and notifications as the updates arrive This streaming approach conserves memory resources and ensures that the application can respond promptly to market fluctuations and provide up to date information to traders and investors It eliminates the need to wait for the entire data feed to be available before taking action Why use streams Streams provide two key advantages over other data handling methods Memory efficiencyWith streams there s no need to load large amounts of data into memory before processing Instead data is processed in smaller manageable chunks reducing memory requirements and efficiently utilizing system resources Time efficiencyStreams enable immediate data processing as soon as it becomes available without waiting for the entire payload to be transmitted This results in faster response times and improved overall performance Understanding and effectively utilizing streams enable developers to achieve optimal memory usage faster data processing and enhanced code modularity making it a powerful feature in Node js applications However different types of Node js streams can be utilized for specific purposes and provide versatility in data handling To effectively use streams in your Node js application it is important to have a clear understanding of each stream type Therefore let s delve into the different stream types available in Node js Types of Node js StreamsNode js provides four primary types of streams each serving a specific purpose Readable StreamsReadable streams allow data to be read from a source such as a file or network socket They emit chunks of data sequentially and can be consumed by attaching listeners to the data event Readable streams can be in a flowing or paused state depending on how the data is consumed const fs require fs Create a Readable stream from a fileconst readStream fs createReadStream the princess bride input txt utf Readable stream data event handlerreadStream on data chunk gt console log Received chunk chunk Readable stream end event handlerreadStream on end gt console log Data reading complete Readable stream error event handlerreadStream on error err gt console error Error occurred err As depicted in the above code snippet we use the fs module to create a Readable stream using the createReadStream method We pass the file path the princess bride input txt and the encoding utf as arguments The Readable stream reads data from the file in small chunks We attach event handlers to the Readable stream to handle different events The data event is emitted when a chunk of data is available to be read The end event is emitted when the Readable stream has finished reading all the data from the file The error event is emitted if an error occurs during the reading process By using the Readable stream and listening to the corresponding events you can efficiently read data from a source such as a file and perform further operations on the received chunks Writable StreamsWritable streams handle the writing of data to a destination such as a file or network socket They provide methods like write and end to send data to the stream Writable streams can be used to write large amounts of data in a chunked manner preventing memory overflow const fs require fs Create a Writable stream to a fileconst writeStream fs createWriteStream the princess bride output txt Writable stream finish event handlerwriteStream on finish gt console log Data writing complete Writable stream error event handlerwriteStream on error err gt console error Error occurred err Write a quote from The to the Writable streamwriteStream write As writeStream write You writeStream write Wish writeStream end In the above code sample we use the fs module to create a Writable stream using the createWriteStream method We specify the file path the princess bride output txt where the data will be written We attach event handlers to the Writable stream to handle different events The finish event is emitted when the Writable stream has finished writing all the data The error event is emitted if an error occurs during the writing process The write method is used to write individual chunks of data to the Writable stream In this example we write the strings As You and Wish to the stream Finally we call end to signal the end of data writing By using the Writable stream and listening to the corresponding events you can efficiently write data to a destination and perform any necessary cleanup or follow up actions once the writing process is complete Duplex StreamsDuplex streams represent a combination of both readable and writable streams They allow data to be both read from and written to a source simultaneously Duplex streams are bidirectional and offer flexibility in scenarios where reading and writing happen concurrently const Duplex require stream class MyDuplex extends Duplex constructor super this data this index this len read size Readable side push data to the stream const lastIndexToRead Math min this index size this len this push this data slice this index lastIndexToRead this index lastIndexToRead if size Signal the end of reading this push null write chunk encoding next const stringVal chunk toString console log Writing chunk stringVal this data stringVal this len stringVal length next const duplexStream new MyDuplex Readable stream data event handlerduplexStream on data chunk gt console log Received data n chunk Write data to the Duplex stream Make sure to use a quote from The Princess Bride for better performance duplexStream write Hello n duplexStream write My name is Inigo Montoya n duplexStream write You killed my father n duplexStream write Prepare to die n Signal writing endedduplexStream end In the above example we extend the Duplex class from the stream module to create a Duplex stream The Duplex stream represents both a readable and writable stream which can be independent of each other We define the read and write methods of the Duplex stream to handle the respective operations In this case we are tying the write stream and the read stream together but this is just for the sake of this example Duplex stream supports independent read and write streams In the read method we implement the readable side of the Duplex stream We push data to the stream usingthis push and when the size becomes we signal the end of the reading by pushing null to the stream In the write method we implement the writable side of the Duplex stream We process the received chunk of data and add it to the internal buffer The next method is called to indicate the completion of the write operation Event handlers are attached to the Duplex stream s data event to handle the readable side of the stream To write data to the Duplex stream we can use the write method Finally we call end to signal the end of writing A duplex stream allows you to create a bidirectional stream that allows both reading and writing operations enabling flexible data processing scenarios Transform StreamsTransform streams are a special type of duplex stream that modify or transform the data while it passes through the stream They are commonly used for data manipulation tasks such as compression encryption or parsing Transform streams receive input process it and emit modified output const Transform require stream Create a Transform streamconst uppercaseTransformStream new Transform transform chunk encoding callback Transform the received data const transformedData chunk toString toUpperCase Push the transformed data to the stream this push transformedData Signal the completion of processing the chunk callback Readable stream data event handleruppercaseTransformStream on data chunk gt console log Received transformed data chunk Write a classic Princess Bride quote to the Transform streamuppercaseTransformStream write Have fun storming the castle uppercaseTransformStream end As depicted in the above code snippet we use the Transform class from the stream module to create a Transform stream We define the transform method within the transform stream options object to handle the transformation operation In the transform method we implement the transformation logic In this case we convert the received chunk of data to uppercase using chunk toString toUpperCase We use this push to push the transformed data to the stream And finally we call callback to indicate the completion of processing the chunk We attach an event handler to the Transform stream s data event to handle the readable side of the stream To write data to the Transform stream we use the write method And we call end to signal the end of writing A transform stream allows you to perform data transformations on the fly as data flows through the stream allowing for flexible and customizable processing of data Understanding these different types of streams allows developers to choose the appropriate stream type based on their specific requirements Using Node js StreamsTo better grasp the practical implementation of Node js Streams let s consider an example of reading data from a file and writing it to another file using streams after transforming and compressing const fs require fs const zlib require zlib const Readable Transform require stream Readable stream Read data from a fileconst readableStream fs createReadStream classic tale of true love and high adventure txt utf Transform stream Modify the data if neededconst transformStream new Transform transform chunk encoding callback Perform any necessary transformations const modifiedData chunk toString toUpperCase Placeholder for transformation logic this push modifiedData callback Compress stream Compress the transformed dataconst compressStream zlib createGzip Writable stream Write compressed data to a fileconst writableStream fs createWriteStream compressed tale gz Pipe streams togetherreadableStream pipe transformStream pipe compressStream pipe writableStream Event handlers for completion and errorwritableStream on finish gt console log Compression complete writableStream on error err gt console error An error occurred during compression err In this code snippet we read a file using a readable stream transform the data to uppercase and compress it using two transform streams one is ours one is the built in zlib transform stream and finally write the data to a file using a writable stream We create a readable stream using fs createReadStream to read data from the input file A transform stream is created using the Transform class Here you can implement any necessary transformations on the data for this example we used toUpperCase again Then we create another transform stream using zlib createGzip to compress the transformed data using the Gzip compression algorithm And finally a writable stream is created using fs createWriteStream to write the compressed data to the compressed tale gz file The pipe method is used to connect the streams together in a sequential manner We start with the readable stream and pipe it to the transform stream which is then piped to the compress stream and finally the compress stream is piped to the writable stream It allows you to establish a streamlined data flow from the readable stream through the transform and compress streams to the writable stream Lastly event handlers are attached to the writable stream to handle the finish and error events Using pipe simplifies the process of connecting streams automatically handling the data flow and ensuring efficient and error free transfer from a readable stream to a writable stream It takes care of managing the underlying stream events and error propagation On the other hand using events directly gives developers more fine grained control over the data flow By attaching event listeners to the readable stream you can perform custom operations or transformations on the received data before writing it to the destination When deciding whether to use pipe or events the following are some factors you should consider Simplicity If you need a straightforward data transfer without any additional processing or transformation pipe provides a simple and concise solution Flexibility If you require more control over the data flow such as modifying the data before writing or performing specific actions during the process using events directly gives you the flexibility to customize the behavior Error handling Both pipe and event listeners allow for error handling However when using events you have more control over how errors are handled and can implement custom error handling logic It s important to choose the approach that best suits your specific use case For simple data transfers pipe is often the preferred choice due to its simplicity and automatic error handling However if you need more control or additional processing during the data flow using events directly provides the necessary flexibility Best Practices for Working with Node js StreamsWhen working with Node js Streams it s important to follow best practices to ensure optimal performance and maintainable code Error handling Streams can encounter errors during reading writing or transformation It s important to handle these errors by listening to the error event and taking appropriate action such as logging the error or gracefully terminating the process Use appropriate high water marks The high water mark is a buffer size limit that determines when a readable stream should pause or resume its data flow It s essential to choose an appropriate high water mark based on the available memory and the nature of the data being processed This prevents memory overflow or unnecessary pauses in the data flow Optimise memory usage Since streams process data in chunks it s important to avoid unnecessary memory consumption Always release resources when they are no longer needed such as closing file handles or network connections after the data transfer is complete Leverage stream utilities Node js provides several utility modules such as stream pipeline and stream finished which simplifies stream handling and ensures proper cleanup These utilities handle error propagation promise integration and automatic stream destruction reducing manual boilerplate code we at Amplication are all for minimizing boilerplate code Implement flow control mechanisms When a writable stream cannot keep up with the rate of data being read from a readable stream by the time the readable stream finish reading there can be a lot of data left in the buffer In some scenarios this might even exceed the amount of available memory  This is called backpressure To handle backpressure effectively consider implementing flow control mechanisms such as using thepause and resume methods or leveraging third party modules like pump or through By adhering to these best practices developers can ensure efficient stream processing minimize resource usage and build robust and scalable applications ConclusionNode js Streams are a powerful feature that enables efficient handling of data flow in a non blocking manner By utilizing streams developers can process large datasets handle real time data and perform operations in a memory efficient way Understanding the different types of streams such as Readable Writable Duplex and Transform and following the best practices ensures optimal stream handling error management and resource utilization By leveraging the power of streams developers can build high performing and scalable applications with Node js I hope you have found this article helpful Thank you 2023-08-01 05:45:10
金融 ニッセイ基礎研究所 気候変動問題の生保への影響-アメリカのアクチュアリー会の議論を参考に https://www.nli-research.co.jp/topics_detail1/id=75659?site=nli 目次ーはじめにー気候変動リスク分析の課題気候変動リスクは複雑シナリオ設定が困難データの属性づけも困難ー気候変動リスクのモデリング脆弱と見られる集団の死亡率を高めに調整する人々の移動を反映するリスク軽減策やリスク間の相殺をモデルに織り込むことも考えられる極端さの程度を表す変数として、日最高気温、日最低気温などが考えられるーモデル結果の開示聞き手に応じて、メッセージを調整する開示の目的を踏まえる開示は効果的に行う必要があるーおわりに私見近年、気候変動問題への関心が高まっている。 2023-08-01 14:58:24
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