投稿時間:2023-05-27 21:11:41 RSSフィード2023-05-27 21:00 分まとめ(10件)

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TECH	Techable（テッカブル）	超小型EV専用駐車場「EVエコパーク」で自動ワイヤレス充電の運用実証が開始	https://techable.jp/archives/208262	技研製作所	2023-05-27 11:00:46
海外TECH	Ars Technica	The lessons of a wildfire that destroyed a town and burned for 15 months	https://arstechnica.com/?p=1942536	conceive	2023-05-27 11:00:42
海外TECH	MakeUseOf	How to Use ChatGPT on Google Sheets With GPT for Sheets and Docs	https://www.makeuseof.com/how-use-chatgpt-google-sheets/	google	2023-05-27 11:15:18
海外TECH	DEV Community	🚀 GraphQL: Revolutionizing Data Communication! 💻🔥	https://dev.to/tsarthur/graphql-revolutionizing-data-communication-4gof	GraphQL Revolutionizing Data Communication Why GraphQL GraphQL beautifully solves three crucial problems Fetching data for a view used to require multiple round trips to the server With GraphQL you can retrieve all the initial data needed for a view in just one request REST APIs on the other hand often involve complex parameters and conditions that are difficult to manage and scale Clients used to be tightly coupled to servers But with GraphQL clients communicate using a request language that eliminates the need for servers to hardcode data shapes or sizes This decoupling empowers us to maintain and enhance clients independently from servers Front end developers often faced a frustrating experience Thankfully GraphQL offers a declarative language for expressing data requirements in user interfaces Developers can focus on what they need without worrying about how to make it available There s a strong connection between UI data requirements and the way developers describe that data in GraphQL This article will delve into the details of how GraphQL tackles these challenges But before we dive in let s start with some simple definitions What is GraphQL Imagine GraphQL as a language If we teach this language to a software application that application can effectively communicate its data requirements to a backend service that also understands GraphQL Learning GraphQL is easier for new applications compared to mature ones much like how children pick up languages more quickly than adults Starting from scratch with GraphQL is a breeze but introducing it to an existing application requires some effort To enable a data service to understand GraphQL we need to implement a runtime layer and expose it to clients who want to interact with the service This runtime layer acts as a translator representing the data service and interpreting the GraphQL language It s important to note that GraphQL itself isn t a storage engine it requires a translating runtime layer This runtime layer which can be implemented in any language defines a graph based schema that exposes the capabilities of the data service it represents Clients speaking GraphQL can query this schema within its defined capabilities This approach decouples clients from servers enabling independent evolution and scalability for both A GraphQL request can either be a query read operation or a mutation write operation In both cases the request is a simple string that a GraphQL service can interpret execute and respond to with data in a specified format JSON is commonly used for responses in mobile and web applications What is GraphQL The Explain it like I m version GraphQL is like a bridge for communication Imagine you have a client and a server and they need to talk to each other The client has to tell the server what data it needs and the server has to provide the requested data to the client GraphQL comes in the middle to make this communication smoother But why can t the client talk directly to the server you may ask Well it actually can However there are reasons to consider adding a GraphQL layer between clients and servers One of the main reasons and the most popular one is efficiency Typically the client needs to ask the server about multiple resources while the server knows how to respond with just one resource This results in the client making multiple round trips to the server to gather all the required data With GraphQL we can shift this complexity of multiple requests to the server side handling it through the GraphQL layer The client asks a single question to the GraphQL layer and receives a response that precisely meets its needs Using a GraphQL layer brings numerous benefits For instance it simplifies and standardizes communication with multiple services When multiple clients are requesting data from various services a GraphQL layer in the middle can streamline and unify this communication While it s also possible to achieve this with REST APIs GraphQL provides a structured and standardized approach Instead of each client directly contacting different data services as shown in the previous example they can communicate with the GraphQL layer The GraphQL layer then handles the communication with the individual data services This way GraphQL not only isolates clients from the need to communicate in multiple languages but also translates a single request into multiple requests to various services using different languages Imagine you have three people who speak different languages and possess different knowledge Now imagine you have a question that requires combining the knowledge of all three individuals If you have a translator who speaks all three languages answering your question becomes easy This is precisely what a GraphQL runtime does Computers aren t yet intelligent enough to answer any question on their own so they rely on algorithms This is why we need to define a schema on the GraphQL runtime which clients utilize The schema is like a document that lists all the questions a client can ask the GraphQL layer There is flexibility in how the schema is used because we re dealing with a graph of interconnected nodes The schema primarily represents the boundaries of what the GraphQL layer can answer Still not clear Let s call GraphQL what it truly is a replacement for REST APIs So let me address the question you re likely wondering now What s wrong with REST APIs The biggest problem with REST APIs is the nature of multiple endpoints These require clients to do multiple round trips to get their data REST APIs are usually a collection of endpoints where each endpoint represents a resource So when a client needs data from multiple resources it needs to perform multiple round trips to a REST API to put together the data it needs In a REST API there is no client request language Clients do not have control over what data the server will return There is no language through which they can do so More accurately the language available for clients is very limited For example the READ REST API endpoints are either GET ResourceName to get a list of all the records from that resource orGET ResourceName ResourceID to get the single record identified by that ID A client can t for example specify which fields to select for a record in that resource That information is in the REST API service itself and the REST API service will always return all of the fields regardless of which ones the client actually needs GraphQL s term for this problem is over fetching of information that s not needed It s a waste of network and memory resources for both the client and server One other big problem with REST APIs is versioning If you need to support multiple versions that usually means new endpoints This leads to more problems while using and maintaining those endpoints and it might be the cause of code duplication on the server The REST APIs problems mentioned above are the ones specific to what GraphQL is trying to solve They are certainly not all of the problems of REST APIs and I don t want to get into what a REST API is and is not I am mostly talking about the popular resource based HTTP endpoint APIs Every one of those APIs eventually turns into a mix that has regular REST endpoints custom ad hoc endpoints crafted for performance reasons This is where GraphQL offers a much better alternative How does GraphQL do its magic There are a lot of concepts and design decisions behind GraphQL but probably the most important ones are A GraphQL schema is a strongly typed schema To create a GraphQL schema we define fields that have types Those types can be primitive or custom and everything else in the schema requires a type This rich type system allows for rich features like having an introspective API and being able to build powerful tools for both clients and servers GraphQL speaks to the data as a Graph and data is naturally a graph If you need to represent any data the right structure is a graph The GraphQL runtime allows us to represent our data with a graph API that matches the natural graph shape of that data GraphQL has a declarative nature for expressing data requirements GraphQL provides clients with a declarative language for them to express their data needs This declarative nature creates a mental model around using the GraphQL language that s close to the way we think about data requirements in English and it makes working with a GraphQL API a lot easier than the alternatives The last concept is why I personally believe GraphQL is a game changer Those are all high level concepts Let s get into some more details To solve the multiple round trip problem GraphQL makes the responding server just a single endpoint Basically GraphQL takes the custom endpoint idea to an extreme and just makes the whole server a single custom endpoint that can reply to all data questions The other big concept that goes with this single endpoint concept is the rich client request language that is needed to work with that custom single endpoint Without a client request language a single endpoint is useless It needs a language to process a custom request and respond with data for that custom request Having a client request language means that the clients will be in control They can ask for exactly what they need and the server will reply with exactly what they re asking for This solves the over fetching problem When it comes to versioning GraphQL has an interesting take on that Versioning can be avoided altogether Basically we can just add new fields without removing the old ones because we have a graph and we can flexibly grow the graph by adding more nodes So we can leave paths on the graph for old APIs and introduce new ones without labeling them as new versions The API just grows This is especially important for mobile clients because we can t control the version of the API they re using Once installed a mobile app might continue to use that same old version of the API for years On the web it s easy to control the version of the API because we just push new code For mobile apps that s a lot harder to do Not totally convinced yet How about we do a one to one comparison between GraphQL and REST with an actual example RESTful APIs vs GraphQL APIs ーExample ️Let s imagine that we are the developers responsible for building a shiny new user interface to represent the Star Wars films and characters The first UI we ve been tasked to build is simple a view to show information about a single Star Wars person For example Darth Vader and all the films this person appeared in This view should display the person s name birth year planet name and the titles of all the films in which they appeared As simple as that sounds we re actually dealing with different resources here Person Planet and Film The relationship between these resources is simple and anyone can guess the shape of the data here A person object belongs to one planet object and it will have one or more film objects The JSON data for this UI could be something like data person name Darth Vader birthYear BBY planet name Tatooine films title A New Hope title The Empire Strikes Back title Return of the Jedi title Revenge of the Sith Assuming a data service gave us this exact structure for the data here s one possible way to represent its view with React js The Container Component lt PersonProfile person data person gt lt PersonProfile gt The PersonProfile Component Name person name Birth Year person birthYear Planet person planet name Films person films map film gt film title This is a simple example and while our experience with Star Wars might have helped us here a bit the relationship between the UI and the data is very clear The UI used all the keys from the JSON data object we imagined Let s now see how we can ask for this data using a RESTful API We need a single person s information using a RESTful API Here s how we might structure the request GET people personId This endpoint would return the following JSON response name Darth Vader birthYear BBY planetId filmIds other information we do not need To display the person s information we would need to make additional requests to retrieve the related data For example to get the planet name we would need to make another request to the homeworld URL GET planets The response would be GET films GET films GET films GET films Each of these requests would return the film information title A New Hope To display the data in the UI we would need to handle these asynchronous requests and wait for all the responses before rendering the complete view This can result in multiple round trips to the server and potential over fetching of data In contrast with GraphQL we can make a single request to retrieve all the required data in one go without the need for multiple requests or over fetching The GraphQL query for fetching the same data would look like this query person personId name birthYear planet name films title The GraphQL server would respond with exactly the requested data data person name Darth Vader birthYear BBY planet name Tatooine films title A New Hope title The Empire Strikes Back title Return of the Jedi title Revenge of the Sith By using GraphQL we simplify the data retrieval process reduce the number of network requests and eliminate over fetching resulting in more efficient and flexible data fetching for our UI The Price of GraphQL s Flexibility There are always trade offs even in the world of GraphQL While GraphQL brings tremendous flexibility it also introduces certain challenges and considerations One significant concern is the potential for resource exhaustion attacks also known as Denial of Service DoS attacks GraphQL servers can be targeted with complex queries that consume excessive server resources It s relatively easy to query deep nested relationships e g user gt friends gt friends or use field aliases to request the same field multiple times Resource exhaustion attacks are not unique to GraphQL but when working with GraphQL we must be particularly cautious about them Fortunately there are mitigations we can employ We can perform cost analysis on queries in advance and enforce limits on the amount of data that can be consumed Implementing timeouts to terminate long running requests is another effective measure Additionally since GraphQL functions as a resolving layer we can handle rate limit enforcement at a lower level beneath GraphQL These measures help protect the server from resource heavy queries If the GraphQL API endpoint we aim to safeguard is not public and is intended solely for internal consumption by our own clients web or mobile we can employ a whitelist approach This involves pre approving queries that the server can execute Clients can then request the execution of pre approved queries using a unique query identifier Facebook has adopted this approach to enhance security Authentication and authorization are other critical considerations when working with GraphQL The question arises do we handle them before after or during the GraphQL resolve process To answer this question let s view GraphQL as a domain specific language DSL layered atop our backend data fetching logic Authentication and authorization become additional layers GraphQL does not directly facilitate the implementation of authentication or authorization logic that s not its purpose However if we choose to place these layers behind GraphQL we can utilize GraphQL to transmit access tokens between clients and the enforcement logic This approach closely resembles how authentication and authorization are handled with RESTful APIs GraphQL poses some challenges when it comes to client data caching Unlike RESTful APIs which are naturally cache friendly due to their resource oriented nature caching GraphQL responses requires a bit more effort While we can use the query text itself as a cache key this approach has limitations and may lead to inefficiencies and data consistency issues Overlapping results from multiple GraphQL queries can be problematic with this basic caching approach Fortunately there is an elegant solution to this problem a Graph Query deserves a Graph Cache By normalizing the response of a GraphQL query into a flat collection of records and assigning each record a globally unique ID we can cache individual records instead of entire responses However this is not a straightforward process Records may reference other records resulting in a cyclic graph that requires careful handling and traversal when populating and reading from the cache Implementing a caching logic layer becomes necessary This approach proves to be more efficient overall compared to response based caching Frameworks like Relay js adopt this caching strategy and provide automatic management of the cache Perhaps one of the most critical issues to address with GraphQL is the notorious N SQL query problem GraphQL query fields function as stand alone functions and resolving these fields with data from a database might result in a new database request per resolved field While it s relatively straightforward to analyze detect and solve N issues in a simple RESTful API endpoint by enhancing SQL queries dynamically resolving fields in GraphQL poses a greater challenge Luckily Facebook is at the forefront of tackling this issue with a solution called DataLoader As the name suggests DataLoader is a utility that allows us to retrieve data from databases and make it available to GraphQL resolver functions Instead of directly querying the database with individual SQL queries we can use DataLoader as an intermediary agent to reduce the number of actual database requests DataLoader employs a combination of batching and caching techniques to achieve this optimization If a client request requires querying the database for multiple items DataLoader can consolidate these queries and efficiently load their responses in batches Furthermore DataLoader caches the fetched data making it readily available for subsequent requests involving the same resources By leveraging DataLoader we can mitigate the performance impact of N SQL queries in GraphQL and improve the overall efficiency of our data retrieval process It is a valuable tool for optimizing data fetching in GraphQL applications Thanks for reading Learning React or Node Checkout my books Learn React js by Building Games Node js Beyond the Basics	2023-05-27 11:03:19
海外TECH	Engadget	Japan's ispace says Hakuto-R crashed because it got confused by a crater rim	https://www.engadget.com/japans-ispace-says-hakuto-r-crashed-because-it-got-confused-by-a-crater-rim-113115803.html?src=rss	Japan x s ispace says Hakuto R crashed because it got confused by a crater rimispace is done analyzing data from its failed Hakuto R lunar landing and it sounds like tricky terrain and a late change in the landing site are to blame Apparently Hakuto R was able to complete the whole deceleration process in preparation of touching down on lunar soil The spacecraft activated its descent sequence when it reached an altitude of around kilometers miles and was able to slow down until it was only moving at a speed of less than m s nbsp However its software had mistakenly estimated its altitude to be zero when it was still hovering around kilometers miles above the ground In other words it thought it had already landed when it hasn t yet and it continued descending at a very slow speed near the surface until its propulsion system ran out of fuel ispace wasn t able to establish contact with the spacecraft again but it believes it went on a free fall and ultimately crashed on the moon That s the how but what about the why Well the company thinks the most likely reason why Hakuto R s software suffered from an altitude estimation issue was because it got confused While it was flying to its landing site it passed over a large cliff that was determined to be the rim of a crater The spacecraft s onboard sensor got an altitude reading of kilometers when it passed by the elevated terrain and that was apparently larger than the estimated altitude value the Hakuto R team set in advance nbsp The spacecraft s software erroneously thought that the sensor reported an abnormal value and it kept filtering out its altitude measurements afterward ispace built the ability to reject abnormal altitude measurements into the lander as a safety measure in the event of a hardware issue with the sensor However it backfired for Mission because simulations of the landing sequence failed to incorporate the lunar environment on the spacecraft s route ispace made the decision to change Hakuto R s landing site after its critical design review was already completed in nbsp The Hakuto R Mission was poised to become the first successful moon landing by a private company and the first Japanese lunar landing overall While it didn t get to land on the moon ispace will use the data from the mission to design preparatory landing sequences for Mission and which are scheduled for launch in and respectively nbsp This article originally appeared on Engadget at	2023-05-27 11:31:15
ニュース	BBC News - Home	Passport e-gates at UK airports not working	https://www.bbc.co.uk/news/uk-65731795?at_medium=RSS&at_campaign=KARANGA	gates	2023-05-27 11:28:46
ニュース	BBC News - Home	Phillip Schofield: ITV investigated 'rumours' of relationship	https://www.bbc.co.uk/news/entertainment-arts-65732039?at_medium=RSS&at_campaign=KARANGA	colleague	2023-05-27 11:49:12
ニュース	BBC News - Home	Downing Street crash man on indecent images charge	https://www.bbc.co.uk/news/uk-65729003?at_medium=RSS&at_campaign=KARANGA	chargethe	2023-05-27 11:01:27
ニュース	BBC News - Home	UK government accused of deposit return scheme 'sabotage'	https://www.bbc.co.uk/news/uk-scotland-65731807?at_medium=RSS&at_campaign=KARANGA	deposit	2023-05-27 11:02:26
ニュース	BBC News - Home	Everton, Leicester City or Leeds United? Who will be relegated from the Premier League?	https://www.bbc.co.uk/sport/av/football/65733383?at_medium=RSS&at_campaign=KARANGA	Everton Leicester City or Leeds United Who will be relegated from the Premier League Football Focus pundits Martin Keown and Glenn Murray debate which of Everton Leicester City and Leeds United will be relegated on the final day of the Premier League season	2023-05-27 11:57:17