投稿時間:2021-07-24 08:22:29 RSSフィード2021-07-24 08:00 分まとめ(26件)

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TECH	Engadget Japanese	仕事の振り返りや翌日のタスクを簡単記録！「1日を振り返る」ショートカットが便利：iPhone Tips	https://japanese.engadget.com/shortcut-221040513.html	iphonetips	2021-07-23 22:10:40
IT	ITmedia 総合記事一覧	[ITmedia News] 開会式で地球をかたどったドローンは1824台のIntel製「Shooting Star」	https://www.itmedia.co.jp/news/articles/2107/24/news021.html	intel	2021-07-24 07:24:00
AWS	AWS Machine Learning Blog	Detect defects and augment predictions using Amazon Lookout for Vision and Amazon A2I	https://aws.amazon.com/blogs/machine-learning/detect-defects-and-augment-predictions-using-amazon-lookout-for-vision-and-amazon-a2i/	Detect defects and augment predictions using Amazon Lookout for Vision and Amazon AIWith machine learning ML more powerful technologies have become available that can automate the task of detecting visual anomalies in a product However implementing such ML solutions is time consuming and expensive because it involves managing and setting up complex infrastructure and having the right ML skills Furthermore ML applications need human oversight to ensure accuracy …	2021-07-23 22:57:46
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	UIButton 横幅の自動調整をコードで	https://teratail.com/questions/350959?rss=all	UIButton横幅の自動調整をコードでiOSアプリをSWIFTで作っています。	2021-07-24 07:43:38
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	rails actioncableについて	https://teratail.com/questions/350958?rss=all	portnbsprailsactioncable	2021-07-24 07:26:31
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	送信できない[ラズパイでスマートリモコン]	https://teratail.com/questions/350957?rss=all	送信できないラズパイでスマートリモコン目的ラズパイのスマートリモコン化発生している問題・エラーメッセージエラーメッセージは、なし送信コマンドを実行しても機器の電源がONしないやった事pythonirrppyrgfcodesTVonnoconfirmpostpythonirrppypgfcodesTVon試したことWiringnbspPiを使ってコード送信TVをつけることができた。	2021-07-24 07:05:42
海外TECH	DEV Community	Reactive Programming 🌫️ - Demystified using RxJS	https://dev.to/gitpaulo/reactive-programming-demystified-using-rxjs-53g5	Reactive Programming ️ Demystified using RxJSIf you re looking for an RxJS quick start then this article is not for you Here I will be tackling Reactive Programming with the goal of shedding some light on its theory using RxJS as the example I will be explaining the core Reactive Programming concepts relating them to RxJS and how works they work in practice Hopefully by the end of the read you ll have a truer understanding of RxJS and be able to pick up any Rx Implementation and immediately start coding Let s get started StatementRxJS is an API for asynchronous programmingwith observable streams To understand what this means we need to define what is meant by asynchronous programming and what observable streams are The best place to start Reactive Programming Reactive ProgrammingReactive Programming not to be confused with Functional Reactive Programming is a subset of Asynchronous Programming and a paradigm where the availability of new information drives the logic forward rather than having control flow driven by a thread of execution Asynchronous Programming is a means of parallel programming in which a unit of work runs separately from the main application thread Generally this is achieved via a messaging system where threads of execution competing for a shared resource don t need to wait by blocking preventing the thread of execution from performing other work until current work is done and can as such perform other useful work while the resource is occupied This concept is vital for Reactive Programming because it allows for non blocking code to be written Bellow a visualisation of the process Asynchronous Message SystemSynchronous blocking communication left is resource inefficient and easily bottlenecked The Reactive approach right reduces risk conserves valuable resources and requires less hardware infrastructure Messages vs EventsReactive Programming is generally Event driven Events are simply undirected messages At their core they are for all intents and purposes an extension of an event The Application Program Interface API for Reactive Programming libraries are generally either Callback based where anonymous side effecting callbacks are attached to event sources and are being invoked when events pass through the dataflow chain Declarative through functional composition usually using well established combinators like map filter fold etc Reactive SystemsThe Reactive Manifesto defines that reactive systems are Responsive responsive systems focus on providing rapid and consistent response times Resilient resilient systems handle problems as they occur and stay responsive in the face of failure Elastic elastic systems stays responsive under the varying workload and ergo have the ability to scale Message Driven message driven systems rely on asynchronous message passing to establish to ensure that change is propagated between components without interruptions Principles of Reactive Systems Reactive Programming amp Reactive SystemsHow do these two relate In summary Reactive Programming is a technique for managing internal logic and dataflow transformation within components of a system It is a way of providing clarity performance and resource efficiency of code Reactive Systems is a set of architectural principles It puts the emphasis on distributed communication and gives us tools to tackle resilience and elasticity in distributed systems Reactive Programming should be used as one of the tools to construct a Reactive System Defining the Paradigm in PracticeRight so what is exactly is Reactive Programming There are many definitions out there some of which I think not even their authors understand what they mean In the wise words of andrestaltz Lets cut the bullshit Reactive programming is programming with asynchronous data streams Beautiful concise and above all explainable In fact this definition is almost the same as the statement about RxJS I presented before That is because RxJS is within the Reactive Programming paradigm Now as promised I ll be showing you guys what is meant by asynchronous data streams StreamsThe key idea in Reactive Programming is that everything for the most part can be a stream Streams are cheap and ubiquitous A stream is a sequence of ongoing events ordered in time It can only emit things a data typed value an error or a termination signal This definition is important to remember since it remains the same no matter the implementation of the paradigm The way I like to think about streams is by visualising a water pipe with a closing mechanism where each water molecule or set of is an emitted value Water pipe stream analogyThe closing mechanism can be triggered manually by turning the tap representing a termination signal or implicitly if the pipe fails to do its function representing an error A closed pipe can no longer push out water and we call it as a completed stream Now let us focus on the first sentence of our definition A stream is a sequence of ongoing events ordered in time Capturing values analogyIn other words water droplets data are being pushed out of the pipe stream as time program execution passes How do we capture these droplets to act on them In most implementations of Reactive Programming we capture these emitted events only asynchronously by defining functions that are called and passed one of the three appropriate outputs as a parameter On value emission Each time a value is pushed through the stream it will be emitted and captured here Can happen multiple times On error emission When the stream error it will be captured here and the stream terminates Happens only once On termination When the stream is terminated it will be captured here Happens only once That covers capturing It s time to move into the manipulation of streams themselves We do this via Operators OperatorsOperators offer a way to manipulate streams by transforming them A transformation in our context is simply a function f that maps a stream into another stream i e f S →S This function we call an operator To visualise this simple imagine placing one or more appliances within the pipeline of our stream These appliances could have filters in them or could modify the contents of the water or other transformations thereby transforming our stream into a new stream Water pipe stream analogy with operators In the image above our initial stream of type Unpurified Water was transformed into a stream of type Purified Water transforming the data that gets observed at the end of the pipeline from its original form To explain operators and their effects on real streams of data we will have to dive into the world of Marble Diagrams Marble DiagramsBefore explaining marble diagrams we need to improve our terminology a little bit Redefining Some TermsNow because we will be dealing with ReactiveX in the next chapter it s time to introduce some of the required terminologies Don t worry for now I will only be giving abstracted definitions to a few terms that map to terms I ve already covered Below the same diagrams as before but with the new terminology included Water pipe stream analogy w terminology and for the operator diagram Water pipe stream analogy with operators w terminology Simple definitions for these terms are Stream gt Observable A structure representing a stream of values over time Tap gt Subscriber Sometimes called the consumer the code that calls the subscription process on an observable structure Turning the tap gt Subscription The method that opens the stream for the observer Closing the tap gt Completing The action of marking the stream as completed meaning it is terminated Bucket gt Observer The structure that captures our pushed values allowing us to act on them Appliances gt Operators Functions that transform the stream We will be returning to more precise definitions later since they are pretty much required to read any sort of RX documentation without inducing a headache So don t worry if you don t quite understand what these mean yet However we will be using this new terminology from now on so I recommend keep the term mapping in your head Marble Diagrams The ObservableOkay time for actual marble diagrams Learning Reactive Programming can be a daunting task so the Rx team came up with the concept of marble diagrams to help with visualising observables and their operators These diagrams are incredibly intuitive and are commonly found in any Rx Operator documentation They allow for easy understanding of the operators without having to read much else Good alternative to a chunky wall of text filled with terminology I ll try to explain how to read them as best I can Overview of a Marble Diagram Okay my bad haha sorry Let s go step by step Marble diagrams describe observables Observables are streams of values through time So we need a time axis Marble Diagram time axis Now that we have a time axis we need to represent our observable outputs If you recall our earlier definition an observable can only output a value a termination signal or an error Let s start with the easy one the termination signal Marble Diagram termination signal In similar fashion we have our error output Marble Diagram error Finally lets represent our emitted value Marble Diagram value push emission There can be multiple values across the time axis as long as there is no termination or error output behind them as those will unsubscribe from the observable Done simple right On to the next part operators in marble diagrams Marble Diagrams The OperatorsAs previously mentioned operators are functions that transform observables That means they take as input one or more observables and output a new observable We can represent them in a marble diagram like so Marble diagram of a filter operator The block in between is our operator function taking in an observable and returning another So our function is filtering the input observable by taking the modulus to determine whether a pushed value is even and if it is it allows that push value to pass through essentially filtering the stream As mentioned before operators can have more than one observable as input such is the case for operators such as switchMapMarble diagram of a switch map operator The switchMap operator is a very popular one that has a handful of practical applications It is generally used to implement a discard action between the input streams which can save a lot of trouble and computation in practice In summary every time the Input Observable emits a value Input Observable emits all of its values unless Input Observable emits a new value before the Input Observable completes If you look at the output observable you will notice that there are only two s This is because Input Observable could not be complete before Input Observable emitted the value You easily confirm this because the space between and is much less than the size of the axis for Input Observable suggesting there was only time to emit the first two values In Practice RxJS Overview of RxJSRxJS is a library extending ReactiveX for composing asynchronous and event based programs by using observable sequences with JavaScript It provides one core type the Observable satellite types Observer Schedulers Subjects and operators map filter reduce every etc to allow the manipulation of the observable streams with easy and significantly reducing the amount of code needed to solve asynchronous problems Advantages VS Disadvantages Advantages​Growing very rapidly ​RxJs alone has mil weekly downloads ​Provides a very high quality asynchronous API ​Lightweight amp memory optimised ​Easy error handling ​Makes asynchronous programming much faster in most applications ​ Disadvantages​Relatively steep learning curve ​Implies a functional programming style data immutability ​Testing debugging can be a learning process RxJS GlossaryIn RxJS some arguably established definitions are EntitiesObservable represents the idea of an invokable collection of future values or events Observer is a collection of callbacks that knows how to listen to values delivered by the Observable Subscription represents the execution of an Observable is primarily useful for cancelling the execution Operators are pure functions that enable a functional programming style of dealing with collections with operations like map filter concat reduce etc Subject is equivalent to an EventEmitter and the only way of multicasting a value or event to multiple Observers Schedulers are centralized dispatchers to control concurrency allowing us to coordinate when computation happens on e g setTimeout or requestAnimationFrame or others Producer The code that is subscribing to the observable This is whoever is being notified of nexted values and errors or completions Consumer Any system or thing that is the source of values that are being pushed out of the observable subscription to the consumer ConceptsUnicast The act of one producer being observed only one consumer An observable is unicast when it only connects one producer to one consumer Unicast doesn t necessarily mean cold Multicast The act of one producer being observed by many consumers Cold An observable is cold when it creates a new producer during subscribe for every new subscription As a result a cold observables are always unicast being one producer observed by one consumer Cold observables can be made hot but not the other way around Hot An observable is hot when its producer was created outside of the context of the subscribe action This means that the hot observable is almost always multicast It is possible that a hot observable is still technically unicast if it is engineered to only allow one subscription at a time however there is no straightforward mechanism for this in RxJS and the scenario is unlikely For the purposes of discussion all hot observables can be assumed to be multicast Hot observables cannot be made cold Push Observables are a push based type That means rather than having the consumer call a function or perform some other action to get a value the consumer receives values as soon as the producer has produced them via a registered next handler Pull Pull based systems are the opposite of push based In a pull based type or system the consumer must request each value the producer has produced manually perhaps long after the producer has actually done so Examples of such systems are Functions and Iterators Observables amp SubscriptionsBy now we should agree that observables are simply structures that lazy push collections of multiple values Subscriptions are the resulting structure representing a disposable resource usually the execution of an Observable Heres how we code them in RxJS import Observable from rxjs Instantiate an observable const observable new Observable subscriber gt subscriber next pushes a value subscriber next subscriber next setTimeout gt subscriber next subscriber complete terminates observable stream Subscribing to an observable console log just before subscribe observable subscribe The three possible outputs of an observable stream next x console log got value x error err console error something wrong occurred err complete console log done creates subscriptionconsole log just after subscribe Unsubscribing to an observable setTimeout gt observable unsubscribe terminates subscription Hot vs Cold ObservablesA cold observable starts producing data when some code invokes a subscribe function on it A cold observable import Observable from rxjs Creating a cold observableconst observable Observable create observer gt observer next Math random We explicitly push the value to the stream Subscription observable subscribe data gt console log data random number Subscription observable subscribe data gt console log data random number A hot observable produces data even if no subscribers are interested in the data A hot observable import Observable from rxjs Coming from an event which is constantly emmit valuesconst observable Observable fromEvent document click Subscription observable subscribe event gt console log event clientX x position of click Subscription observable subscribe event gt console log event clientY y position of click Promises vs ObservablesThe main differences are Promises are eager Observables are lazy ​Promises are single value emissions Observables are multi value streams ​Promises have no cancelling or operator APIs Observables do Promise vs Observable A stackblitz example of RxJS vs Promises Observables can be PromisesAlthough observables are not an extension of the Promise A specification RxJS still provides means to transform an observable into a true Promise An example follows import Observable from rxjs Return a basic observableconst simpleObservable val gt Observable of val delay Convert basic observable to promiseconst example sample First Example toPromise Now its a promise then result gt console log From Promise result After ms output First Example With the use of RxJS s toPromise method any observable can be converted to a promise Note that because it returns a true JS Promise toPromise is not a pipable operator as it does not return an observable ObserverIn practice an Observer is a consumer of values delivered by an Observable Observers are simply a set of callbacks one for each type of notification delivered by the Observable next error and complete The following is an example of a typical Observer object const observer next x gt console log Observer got a next value x error err gt console error Observer got an error err complete gt console log Observer got a complete notification To use it pass it to a subscribeobservable subscribe observer That s it for observers really OperatorsRxJS is mostly useful for its operators even though the Observable is the foundation Previously we studied operators as functions that transformed streams Nothing changes here just terminology RxJS has a very vast library of operators We will only be touching on a few simple ones to cover what we ve talked about already import from from rxjs import filter from rxjs operators from pipe filter x gt x subscribe console log If you remember our filter example from before this should be fairly simple to understand PipelineA pipeline is simply a series of operators that get executed in order Something obvious but that people forget every pipeline operator must return an observable The same exmaple as before but with chaining operators import from from rxjs import filter take map from rxjs operators from pipe filter x gt x take map firstValue gt The first even number was firstValue subscribe console log There are a ton more operators that do vastly different things in categories such as Creation Filtering Combination Error Handling Transformation Multicasting etc I encourage you to try a few from each of the categories out This is the power of RxJS there s a lot already done for you SubjectsA Subject is like an Observable but can multicast to many Observers Subjects are like EventEmitters they maintain a registry of many listeners In fact part of a subject is literally an observable and you can get a reference to that observable The easiest way to think of a subject is quite literally Subject Observer ObservableExample import Subject from from rxjs const subject new Subject lt number gt subject subscribe next v gt console log observerA v subject subscribe next v gt console log observerB v subject next subject next Logs observerA observerB observerA observerB const observable from observable subscribe subject You can subscribe providing a Subject Logs observerA observerB observerA observerB observerA observerB IMO the best use case for Subjects is when the code it is referenced in is the one that is producing the observable data You can easily let your consumers subscribe to the Subject and then call the next function to push data into the pipeline Be wary of overusing them since most problems are solvable with only data transformation and Observables SchedulersFinally schedulers They might seem hard to understand but are quite simple at a surface level which is more than enough for us to know about In essence schedulers control the order of tasks for Observables There are only a few of them and they won t be changing anytime soon here they are Table of the types of schedulers You can use schedulers by passing them to observables through a handful of operators usually of the creation category as arguments The most basic example forcing a synchronous observable to behave asynchronously import Observable asyncScheduler from rxjs import observeOn from rxjs operators const observable new Observable observer gt observer next observer next observer next observer complete pipe observeOn asyncScheduler console log just before subscribe observable subscribe next x console log got value x error err console error something wrong occurred err complete console log done console log just after subscribe Logs just before subscribe just after subscribe got value got value got value doneNotice how the notifications got value were delivered after just after subscription This is because observeOn asyncScheduler introduces a proxy Observer between the new Observable and the final Observer Other schedulers can be used for different timings We are done Amazing RxJS ResourcesRxJS visualizer Instant marble diagrams Docs with marble diagrams Operator decision tree Reference bencabanes marble testing observable introduction fadc	2021-07-23 22:38:48
海外TECH	DEV Community	5 of The Best Study Materials for Google [Recommended by Google]	https://dev.to/cleancodestudio/5-of-the-best-study-materials-for-google-recommended-by-google-2eo3	of The Best Study Materials for Google Recommended by Google Email snippet from my Google recruiter Listing off Google Recommended Study Materials for Google Two days ago I landed a gig at Amazon hip hip Hip Hip Array I was also rejected by Google a week and a half ago b b To be or not to beAll FAANG interviews are hard let me have a lt br gt let me have a break All FAANG interviews are EXTREMELY hard I wouldn t agree with this statement FAANG interviews are different Different does NOT mean EXTREME or EXTREMELY HARDAre they Easy Definitely not easy either So Extremely Hard right Honestly I d say no They re not EXTREME in any regard FAANG interviews aren t EXTREMELY hard They are tedious and time demanding if you DONT have the interview preparation experience So Tedious and time demanding Absolutely Extremely hard Absolutely Note Below is a blog post I wrote outlining my thoughts and insights on the Google interview process while I was in the Google interview process I m in Google s Interview ProcessAt the time of writing this I m in Google s interview process The recruiter emailed me a list of study materials to prepare for Google s interview process The email snippet below is that list of resources This email snippet is directly from my Google recruiter FAANG Study Resource Cracking the Coding Interview Google Recommended My thoughts on Interviewing at FAANG thus far FAANG companies go above and beyond to give you the best resources that ll help you prepare for their interview process They invest a lot of time and money into hiring engineer s that can meet or pass their coding challenges Although that being said FAANG interviews aren t meant to measure how great of an engineer you may end up being They re instead measuring to make sure you are above a minimum threshold FAANG companies don t let any weak links in but that doesn t mean every one is phenomenal or a software engineering God Does Google have a few top of the industry studs Absolutely But of the software engineers at Google aren t any different than you re pretty good software engineers at other organizations The difference at Google Amazon Netflix Apple and Facebook is that no one is below that better than average threshold The truth about their interview process is that many of the senior engineers at FAANG wouldn t be able to pass the interviews again even though they re some of the best in the field At the same time many far less experienced software engineers much would be able to pass the interview process FAANGs Interview process priorities letting good engineers go to keep any bad one s from potentially getting in the Door FAANG s interview process is focused on NOT letting bad engineers in FAANG s interview process wants the best talent who doesn t BUT that is not the top priority of these interview processes If they are stuck between you re amazing and you may be a weak link in the chain then you re not getting through the door Their priority is to not let engineer s below a certain threshold through the door Fortunately and unfortunately the types of interview s they give are very learnable You can study and pretty much anyone willing to invest hours into data structures algorithms and coding challenges would be able to eventually get into Google I d honestly say getting into a FAANG company isn t much harder than getting into a start up It s just different The types of interview s given aren t what real world experience teaches you Weirdly at this top level College universities teach many of the concepts that FAANG tests over Now that being said just because the universities teach the concepts does NOT mean they teach you how to pass the coding challenges it s just the type of interview s they give aren t what real world experience usually teaches you If you understand data structures and algorithms really well and happen to invest your time into coding challenges for fun Then you ll probably be in a solid position to do really well If you ve never had to use data structure s and algorithms because you ve never worked at FAANG and have never gone to college and don t love investing your free time into data structures and algorithms like me then you have a lot of learning to catch up on If you ve never taken a college course like me and have never needed to dive deep into data structures and algorithms then this learning curve is going to require to months of your time If you aren t familiar with the types of interviews given at FAANG companies then you ll need that months to months of studying to basically get good at big o notation time complexity space complexity data structures algorithms and coding challenges You ll need a few months to prep up On the other hand there s an upside If you have years in the industry or your brand new you really only need that to months in both instances with everything else being even You have invested time into data structures algorithms or coding challenges at all The upside is if you have little real world experience and are interviewing at FAANG then you still really only need hours per week of studying full time for to months to also pass the coding interview If you can invest hour per week studying full time I d estimate you really only need to maaaybbeee months years experience in the industry or a newbie the time commitment is the same if you haven t learning data structures algorithms or invested into solving coding challenges The months of prep is hard work nothing extreme just hard But if you are able to invest the effort into building your data structure algorithms and coding challenge skills for those months then lala you re making the big bucks at FAANG It s hard work but FAANG pays the big bucks and has plenty of applicants to choose from They don t mind waiting on you to be able to pass their coding challenge Side note you can check FAANG software developer salary ranges at Levels FYI Here s Google s salary range Software Engineer Google L k yr average incomeNote L is one level above entry level at GoogleL s usually have years industry experience What s crazy is that it d honestly probably only take to months for both an engineer who has years of experience in the industry as well as an engineer who is straight out of college or didn t even go to college and has less than a year of experience to study devotedly and pass the interviews gt Statistically getting into Google is x times harder than getting into Harvard Ironically I think that has a lot todo with getting in the door for the actual interview and less to do with the interview process itself Don t get me wrong the interview process is intense far from easy But it hasn t felt any more difficult than learning something like object oriented design patterns If you don t have the experience then you just need to invest the time to learn to different design patterns Once you know them you ll want to begin to recognize those patterns in different contexts When would these patterns be good to use When wouldn t they What s the pros of this pattern What s the cons of this pattern Composition vs inheritance How do I use patterns to create clean code Follow The Clean Code Studio Blog For More ltag user id follow action button background color ffffff important color ffffff important border color ffffff important Clean Code StudioFollow Clean Code StudioClean Code Clean Life Simplify The Google interview process studying for it feels a lot like learning design patterns It s not necessarily easy and can feel boring or daunting at times when you re learning more tedious patterns but it s definitely a feasible task You just can t cram and expect to understand the intricacies of the design patterns Google Recommended Study Resource Example Google Interview You need practice and experience Data structure and algorithm coding challenge problems at FAANG interviews are the same kind of ordeal Instead of having design patterns that utilize an interface and multiple classes that implement a given interface you instead have a coding question that requires an algorithm that can utilize the sliding window technique for O n time complexity that needs to plug in a hash map data structure to keep track of key s and values Instead of figuring out dependencies and which design pattern helps you stay out of dependency hell you re figuring out time complexity space complexity and making sure you re operations aren t growing relatively large relative to the input so that the million data items passed in to populate your parameter s data structure during a single request doesn t cause the function to be a bottle neck due to being incapable of processing data sets of that size You re code must be optimal enough to handle huge data sets at companies like Google Amazon Facebook Microsoft Netflix or Apple These companies handle billions of requests and immense amounts of data Time complexity is simply counting the number of operations executed relative to the size of a given functions input Design patterns are simply intended to manage dependencies and minimize bugs You have to learn how to properly implement given data structures and algorithms to minimize the operations executed within the context of a given challenge You have coding challenges that you can use the sliding window technique because based on the problem it makes sense There s trade offs to using it and certain cases The sliding window technique wouldn t make since in many contexts Maybe instead of a sliding window being used on an array or linked list it makes more since to use a tree or graph For many questions trees and graphs don t make any since at all There s also sleight variations in the sliding window technique fixed window expanding window closing window resizing window using a sliding window with an auxiliary data structure etc that you learn about from a higher level understanding and then dive deeper to learn the contextual use cases and experience based understanding of the little differences in sliding window techniques It s intense preparing for a Google interview no doubt about it On the other hand I was also caught off guard when I was invited to interview at Google A recruiter reached out via LinkedIn If I knew I d be interviewing at Google to months back then I would have been preparing for to months I would have been preparing this entire time and would most definitely be feeling much more confident about the entire process Right now I d say it s a coin flip whether I get in but either way it s been an interesting learning experience and I figured it was one worth sharing Quick points to reference Three types of interviews Technical InterviewData StructuresAlgorithmsCoding Challenges Example Technical Interview Question Behavioral InterviewBehavioral interviewing focuses on a candidate s past experiences by asking candidates to provide specific examples of how they have demonstrated certain behaviors knowledge skills and abilities Example Behavioral Interview Question Given a string s find the length of the longest substring without repeating characters ExampleInput s abcabcbb Output Explanation The answer is abc with the length of Talk about a time when you had to work closely with someone whose personality was very different from yours System Design InterviewDistributed SystemsHigh AvailabilityRedundancy Horizontal ScalabilityLoad BalancersFirewallsWhich Databases should you useEvent systems Example System Design Interview Question Here s a white board design Uber NOTE System Design interview sections are only apart of interview processes for L and above at Google According to a former google interview I studied with So no matter the quality of the resources listed below you ll still have to work your butt off and then most likely unless you have the to months of prep in advance you ll fail a few times before actually getting in somewhere That being said once you re in the door for the interview the first time around it s much easier to get back in the door even if you failed the first round for another interview to months in the future depending on the company Once you re in the first time it sounds like it s much easier to get invited back So with that here is the snippet of google recommended study materialsAnd now without further a due here s the Google interview study resources recommended by Google themselves along with the snipper from my Google recruiter with the list Thanks to the google recruiter I worked with he was awesome Anonymous technical mock interviews with engineers from Google Facebook and other top companies Leet Code Google Interview Practice QuestionsFollow Clean Code Studio For More Content ltag user id follow action button background color ffffff important color ffffff important border color ffffff important Clean Code StudioFollow Clean Code StudioClean Code Clean Life Simplify My Personal Google Amazon and Facebook Interview NotesClean Code Principles	2021-07-23 22:09:01
Apple	AppleInsider - Frontpage News	Apple adds communications chief Stella Low to leadership webpage	https://appleinsider.com/articles/21/07/23/apple-adds-communications-chief-stella-low-to-leadership-webpage?utm_medium=rss	Apple adds communications chief Stella Low to leadership webpageAfter announcing her hire in May Apple on Friday updated its Leadership webpage to reflect the former Cisco executive s new role as VP of Communications The updated webpage includes the customary Apple headshot a rundown of Low s work history and a brief biography In her new position Low will report directly to CEO Tim Cook and is responsible for the company s worldwide communications strategy public relations team and employee communications Apple says With years in marketing and communications Low previously worked for Cisco in a similar role and held positions at Dell and EMC Read more	2021-07-23 22:57:41
Apple	AppleInsider - Frontpage News	Email from Ted Lasso invites Apple TV+ subscribers to watch new season	https://appleinsider.com/articles/21/07/23/email-from-ted-lasso-invites-apple-tv-subscribers-to-watch-new-season?utm_medium=rss	Email from Ted Lasso invites Apple TV subscribers to watch new seasonAs part of an all encompassing media blitz promoting the kickoff of Ted Lasso season two Apple on Friday sent an email out to Apple TV subscribers that has the coach himself inviting viewers to tune in From Ted Lasso the letter addresses users by their first name ーHey there insert name ーand is penned using the titular character s signature down home folksy vernacular One can almost hear actor Jason Sudeikis Midwestern twang My second season with AFC Richmond starts today July rd and I d love it if you could watch our journey More importantly I want you to believe the letter reads A link to the series Apple TV app page is included in the first line Read more	2021-07-23 22:44:46
海外TECH	Engadget	Relaxing behind the wheel of Mercedes’ level 3 autonomous Drive Pilot	https://www.engadget.com/mercedes-drive-pilot-level-3-autonomous-video-220158620.html?src=rss	Relaxing behind the wheel of Mercedes level autonomous Drive PilotThe dream of autonomous driving everywhere is still a long way away But soon Mercedes will launch Drive Pilot its level autonomous driving system in Germany on the S Class and EQS We had a chance to try the system out at the automaker s test track and while it did what it was supposed to do we found it hard to turn off our driving brain while behind the wheel The system works on highways in traffic at speeds up to kph mph Essentially it s for daily commuting But during that time the driver can stop paying attention and the Mercedes is responsible for everything that happens That s not to say you can nap the vehicle still tracks the driver with an in car monitor and it requires the driver to take over when it s about to go faster than mph an emergency vehicle shows up it rains or other situations that the vehicle is not built to handle But you can play Tetris and text people So that s fun Watch our video for the full story	2021-07-23 22:01:58
海外TECH	Engadget	Mercedes EQS first drive: S-Class luxury in an EV	https://www.engadget.com/mercedes-eqs-ev-first-drive-video-220117807.html?src=rss	Mercedes EQS first drive S Class luxury in an EVMercedes has a lot to prove with its first proper EV coming to the United States The EQS will land in dealers this fall at a yet to be announced price point and when it does it ll take on offerings from Tesla and Porsche How will it fare against these EVs We had a chance to drive the EQS for two days and figure out how it stacks up not just against competitors but up against the S Class itself On our drive we got time behind the with rear wheel drive the Matic with all wheel drive and the Edition One version with its two tone paint and Matic powerplant All vehicles have a kWh capacity battery pack and on the WLTP range test the vehicle is rated at miles Of course the more stringent EPA testing needs to be done and that number should fall For now we have a drive and impressions while we wait for range estimates and pricing Watch our first drive video above for the full story	2021-07-23 22:01:17
海外科学	NYT > Science	C.D.C. Warns of Superbug Fungus Outbreaks in 2 Cities	https://www.nytimes.com/2021/07/23/health/superbug-fungus-cdc.html	C D C Warns of Superbug Fungus Outbreaks in CitiesFor the first time the C D C identified several cases of Candida auris that were resistant to all drugs in two health facilities in Texas and a long term care center in Washington D C	2021-07-23 22:40:11
海外科学	NYT > Science	Purnell Choppin, 91, Dies; Researcher Laid Groundwork for Pandemic Fight	https://www.nytimes.com/2021/07/23/science/purnell-choppin-dead.html	Purnell Choppin Dies Researcher Laid Groundwork for Pandemic FightHe explored how viruses multiply An accomplished administrator he also turned the Howard Hughes Medical Institute into a global biomedical powerhouse	2021-07-23 22:25:34
海外科学	NYT > Science	Una intervención en el cerebro ayuda a un hombre paralítico a hablar	https://www.nytimes.com/es/2021/07/20/espanol/implante-cerebral-habla.html	Una intervención en el cerebro ayuda a un hombre paralítico a hablarEn un logro antes inimaginado unos electrodos implantados en el cerebro del hombre transmiten señales a una computadora que muestra las palabras que intenta decir	2021-07-23 22:58:04
海外TECH	WIRED	The Activision Blizzard Harassment Suit Feels Painfully Familiar	https://www.wired.com/story/activision-blizzard-harassment-complaint	industry	2021-07-23 22:52:16
ニュース	@日本経済新聞 電子版	⚡️1回目のワクチン接種後。どこで、なぜ――。記者のコロナ感染記。西武HDが「ザ・プリンスパークタワー東京」など40施設程度を売却へ。フェイクニュースの姿を科学。この1週間、Twitterで読まれた日経記事です。 https://t.co/TcAOeVSn5p	https://twitter.com/nikkei/statuses/1418706876221599749	️回目のワクチン接種後。	2021-07-23 22:57:32
ニュース	@日本経済新聞 電子版	【東京五輪開会式】「祝賀ムードとは程遠く、天皇陛下が『祝意』を表明することには宮内庁内でも懸念があった」「国民に漂う空気感を大会組織委員会が……」。開会宣言は日本語での祭典色が控えめになりました。#Tokyo2020 https://t.co/VLuApsbU7Y	https://twitter.com/nikkei/statuses/1418700005876146180	【東京五輪開会式】「祝賀ムードとは程遠く、天皇陛下が『祝意』を表明することには宮内庁内でも懸念があった」「国民に漂う空気感を大会組織委員会が……」。	2021-07-23 22:30:14
ニュース	@日本経済新聞 電子版	インディアンス、チーム名をガーディアンズに　大リーグ https://t.co/eEBJJQEXP8	https://twitter.com/nikkei/statuses/1418695641979555847	大リーグ	2021-07-23 22:12:53
ニュース	BBC News - Home	Newspaper headlines: Pingdemic 'to last weeks' and healthy 'rewards' planned	https://www.bbc.co.uk/news/blogs-the-papers-57950840	tokyo	2021-07-23 22:46:32
ニュース	BBC News - Home	The Hundred - Birmingham Phoenix v London Spirit: Plays of the day	https://www.bbc.co.uk/sport/av/cricket/57949632	london	2021-07-23 22:47:04
ビジネス	ダイヤモンド・オンライン - 新着記事	中国のファーウェイ、民主系有力ロビイスト起用　ポデスタ氏 - WSJ発	https://diamond.jp/articles/-/277691	起用	2021-07-24 07:26:00
ビジネス	ダイヤモンド・オンライン - 新着記事	上期の米自動車販売、EVが業界上回るペースで成長 - WSJ発	https://diamond.jp/articles/-/277692	自動車販売	2021-07-24 07:20:00
北海道	北海道新聞	五輪、コロナ禍から復活の力に　経済団体、協賛企業は複雑	https://www.hokkaido-np.co.jp/article/570446/	東京五輪	2021-07-24 07:20:02
北海道	北海道新聞	ＮＹ株最高値、３万５千ドル台　終値で初、米景気回復期待	https://www.hokkaido-np.co.jp/article/570483/	景気回復	2021-07-24 07:16:06
北海道	北海道新聞	米、ワクチン２億回分調達　１２歳未満や３回目接種視野	https://www.hokkaido-np.co.jp/article/570486/	記者会見	2021-07-24 07:03:00