投稿時間:2022-04-04 03:20:30 RSSフィード2022-04-04 03:00 分まとめ(28件)

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python	Pythonタグが付けられた新着投稿 - Qiita	ナップサック問題の解法 for Python	https://qiita.com/kzy83/items/64be4f5f1eaf08917f24	DPのメリットフィボナッチ数列このナップサック問題の解放のポイントは、今計算している結果をそれに該当する配列に格納せず、iの配列に格納することだ。	2022-04-04 02:56:10
海外TECH	MakeUseOf	The Best Way to Clean Windows 10: A Step-by-Step Guide	https://www.makeuseof.com/tag/best-way-clean-windows-10-step-step-guide/	windows	2022-04-03 17:30:14
海外TECH	MakeUseOf	9 Fun, Free Mobile Easter Games the Whole Family Can Enjoy	https://www.makeuseof.com/easter-mobile-games/	Fun Free Mobile Easter Games the Whole Family Can EnjoyFancy an Easter themed game for you and the family You re in luck We ve rounded up some of the best Easter mobile games around Let s dive in	2022-04-03 17:30:13
海外TECH	MakeUseOf	Can Data Be Recovered After a Factory Reset on Android Phones?	https://www.makeuseof.com/tag/stop-thieves-recovering-data-factory-reset/	android	2022-04-03 17:15:13
海外TECH	DEV Community	50 Github Repositories for a developer	https://dev.to/dhanushnehru/50-github-repositories-for-a-developer-631	Github Repositories for a developerGithub is a popular platform for tons of resources and there are many repositories which provide free resources on various aspects of software engineering I would like to share github repositories that would help you in the journey of programming FreeCodeCampA non profit organization and best opensource community Over here you can help others code and also learn to code by the various tutorials they have provided Awesome PythonA github repository that lists various python frameworks libraries softwares podcasts resources for python developers Ultimate Node Js ResourcesResources related to Node Js at one place which includes IDE s security testing frameworks blogs and much more You don t know JSYou don t know JS is a popular javascript book which is available in github as well Coding Interview UniversityIf you want to get into top software companies it provides a study plan It also helps yourself to stay prepared for technical interviews for Google Microsoft etc Public ApisAs a developer when dealing with Apis for application you can choose a list of free Apis from this site which ranges from animation games google analytical apis etc App IdeasIt lists a collection of application ideas to improve your coding skills Ultimate Web Development ResourcesLists collection of web development resources which ranges from the list of softwares hosting platforms code challenges fonts etc If you want to get started with web development these resources listed here would help you to get started AwesomeAwesome lists about all kinds of interesting topics and resources Developer RoadmapIt provides a roadmap inorder to become a software engineer The AlgorithmsIf you want to learn algorithms based on different programming languages this one is for you You dont needPeople choose popular projects often not because it applies to their problems It contains a list which you don t need for developing Javascript QuestionsIt contains advanced javascript questions which helps to upgrade yourself as a javascript developer WtfjsA list of funny and tricky JavaScript examples Complete Python BootcampThere is a course in udemy based on the repository name and all the course files are present here Tech Interview HandbookA curated interview preparation materials for busy engineers The Art of Command LineOne github page to master all your command line operations GitignoreIt list useful gitignore templates for your project seconds of codeIt lists short javascript snippets for your next project Computer ScienceA repository which provides the path to become a self taught computer science engineer Data ScienceA repository which provides the path to become a self taught data science engineer How to secure anythingA repository about security engineering Free Programming BooksList all the free programming books available for a programmer Mobile Verification ToolkitIt is a collection of utilities to simplify and automate the process of gathering forensic traces helpful to identify a potential compromise of Android and iOS devices Js conceptsIt lists about Javascript concepts which every developer must know Front end interview handbookIt lists various front end interview preparation materials for busy engineers Project based learningA list of programming tutorials in which aspiring software developers learn how to build an application from scratch These tutorials are divided into different primary programming languages Tutorials may involve multiple technologies and languages Build your own XWhat you cannot create you cannot understand It lists resources which help you to build your own database bots cryptocurrency etc System Design PrimerLearn how to design large scale systems and also preparation for the system design interview Javascript AlgorithmsAlgorithms and data structures implemented in JavaScript with explanations and links to further readings Big List of naughty stringsThe Big List of Naughty Strings is a list of strings which have a high probability of causing issues when used as user input data The book of secret knowledgeA collection of inspiring lists manuals cheatsheets blogs hacks one liners cli web tools and more Node best practicesThe Node js best practices list Real World The mother of all demo apps ーExemplary fullstack Medium com clone powered by React Angular Node Django etc TheAlgorithms PythonLists all Algorithms implemented in Python Project GuidelinesA set of best practices for JavaScript projects Clean Code JavascriptLists all the clean Code concepts adapted for JavaScript Front End ChecklistThe perfect Front End Checklist for modern websites and meticulous developers Css Pro TipsA collection of tips to help take your CSS skills pro Javascript Testing Best PracticesComprehensive and exhaustive JavaScript amp Node js testing best practices Java Design PatternsLists various design patterns implemented in Java First ContributionsLists Materials to contribute to open source projects SlidevLists the presentation slides for developers Cheat shUnified access to the best community driven cheat sheets repositories of the world Awesome PrivacyA curated list of services and alternatives that respect your privacy because PRIVACY MATTERS BlockchainTo create a simple block chain using python Ionic frameworkA powerful cross platform UI toolkit for building native quality iOS Android and Progressive Web Apps with HTML CSS and JavaScript PixijsThe HTML Creation Engine Create beautiful digital content with the fastest most flexible D WebGL renderer SupercookieSupercookie uses favicons to assign a unique identifier to website visitors Unlike traditional tracking methods this ID can be stored almost persistently and cannot be easily cleared by the user How web worksDetails information about how DNS HTTP protocol servers work or about Render Tree DOM Tree page painting etc It is a useful repository to learn the basics of how the web works Thanks for reading If you have any other valuable github repositories to share feel free to drop below Connect with me via Twitter	2022-04-03 17:44:22
海外TECH	DEV Community	The Ultimate Guide To Getting Started In Data Science	https://dev.to/brayan_kai/the-ultimate-guide-to-getting-started-in-data-science-4h9b	The Ultimate Guide To Getting Started In Data Science IntroductionI dare suggest that Data Science is one of the sexiest careers in the twenty first century Breaking into the field of Data Science especially one as sophisticated and multidimensional as this one is not simple We re in an odd era where even the concept and expectations of Data Science differ from one organization to the next What data scientists perform what they need to know and the types of firms that need to hire data scientists are all changing rapidly Why on earth then would there be only one path to take in the first place I can t think of a better time to start if you re looking to break into data science Start now In this article I am going to explain how one can best get started in Data Science from a personal perspective The Goals of this articleAfter reading this article the reader should gain the following from it The reader should be encouraged and able to kick start their journey into data science The reader should be able to get the best way on starting their data Science journey Why Data SciencePeter Sondergaard the Senior Vice President and Global head of research at Gartner Inc once said that i nformation is the oil of the st century and analytics is the combustion engine This is just a sliver of how lucrative the field of data is Choosing to be a data scientist is a great choice not because you are going to get money from it but because you have taken a step to care for the world Data Science involves changing different sad stories into grinning stories stories we transform for the better with data So choose to care and Love the planet It s all about you caring for the people not just users What is Data ScienceData Science is a universally recognized term that escapes every single complete definition It is a volatile field whose methods and goals evolve with every technological advancement The definition of data science years ago is not the same today Since no one definition fits it Let us define the key processes in data science and how they fit into each other Acting as the building block to the bigger data science picture That way I believe one will be able to visualize understand and conceptualize what data science truly is This also will help if one wants to be a competitive job applicant they will need to understand how various data science activities fit into the big picture as earlier stated One will get to learn about the timing of different data processing analyses as well as who carries them out and let s not forget how Does that make sense DataIf you want to work in medicine you will first learn how the human body functions and then decide whether you want to be a pediatrician or a nurse or an oncologist etc that is what we are about to do here but for data science Okay so let s get started by talking about data since Before there was anything there was data Data is the foundation of Data Science Therefore we need to have a clearly understanding of what data is In the context of data science there are two types of data Traditional DataTraditional data is data that is structured and stored in databases that can be managed from one computer It is in table format containing numeric and text values Traditional data may come from sources like basic customer records of a retail store or the historical price of crude oil in the middle east oil producer countries Big DataBig Data on the other hand is bigger than traditional data and not in the trivial sense It isn t simply represented by numbers or texts but also by images audio mobile data and so on In addition big data has high velocity this is to means that its retrieved and computed in real time And finally think about its volume big data is measured in tera Peta and exabytes and hence often distributed into a network of computers Big data is all around us A consistently growing number of companies and industries generate use and generate big data Consider online communities like tick tock Facebook and LinkedIn They generate a massive amount of user data This is a lot of data being generated Right now digital data in the world amounts to zettabytes Having known what data is and its different forms now imagine the following scenario You are already a data scientist professional and you are working for a private airline company A superior member of staff tells you one of the two things below what is the difference between the two We need to consider client satisfaction in the next quarter so we can predict the churn rate Oversee the process and come up with some numbers We have an enormous amount of customer data from the previous quarter Can you oversee the analysis and deliver an approximation of churn rates for the next quarter If You have noticed the difference between the two is that unlike in the second case you do not have data in the first case You will need to gather it probably through surveys and so on So you have conducted the survey and received responses Is this data ready to be analyzed Not Exactly This is called raw data since you haven t done any processing on it It is untouched data that cannot be analyzed straight away This takes us to the next point which is Preprocessing of data Preprocessing Preliminary Data Science Preprocessing is what we can think of as preliminary data science Preprocessing is a crucial group of operations that converts raw data into a format that is more understandable and hence useful for further processing Plus it fixes the mistakes that occurred during the gathering phase Like when we are thinking about customer data it s unrealistically easy to have a person registered as “KNOP years old called “Ukraine flight number “Isabel Valentine from “ as her country Those data entries are incorrect and therefore must be handled before proceeding to any type of analysis right That is why there are tons of preprocessing practices in place Will tell you about some of the common ones i Class LabellingThe first is class labeling your observations This consists of arranging data by category or labeling data points to the correct data type For example numerical or categorical The number of passengers on a day s flight would be numerical you can manipulate this information mathematically and the passenger s occupation and country of origin are categorical because no mathematical operations can be done on this information Just keep in mind that with big data the classes are extremely varied therefore instead of numerical vs categorical the labels will be text digital image data digital video data digital audio data and so on ii Data Cleansing or Scrubbing These are techniques for dealing with inconsistent data like misspelled categories and missing values You know a lot of people sharing their name and occupation but omitting their age or gender iii Data Shuffling Data shuffling is another interesting one Imagine shuffling a deck of cards It ensures that your dataset is free from unwanted patterns caused by problematic data collection For example if the first observations in your data are from the first passengers who boarded the first flight of the day This data isn t randomized and is likely to reflect just the behavior of those passengers when the airline had just been rolled out In a word data shuffling prevents patterns due to sampling to emerge iv Data MaskingFinally consider data masking This is primarily a big data specific technique When collecting data on a mass scale you can accidentally put your hands on a lot of sensitive information which you need to urgently hide from yourself Masking aims to ensure that any confidential information in the data remains private without hindering the analysis and extraction of insight Essentially the process involves concealing the original data with random and false data allowing the scientist to conduct their analyses without compromising private details Let s not forget that all of this is just the very beginning of doing data science Pre processing of data to make it usable is laying the groundwork Alright let s assume your databases are clean and organized at this point so let s get into the real deal now Looking at DataBefore we begin I want to make sure that we all moving together There are two ways of looking at data One is with the intent to explain behavior that has already happened and you have gathered data for it The second way is to use data that you already have to predict future behavior that has not yet happened One needs to be very clear on this distinction because it can be what tilts the scales one way or another when you are deliberating which data science path is best for you There is also a temporal relationship between the two ways of looking at data Before data science jumps into predictive analytics it must look at the patterns of behavior the past provides It must analyze them to draw insights which will then inform the direction in which forecasting should go This brings us to the next part which is Exploratory data analysis Explain first before predicting In this stage the data scientist after collecting the data and ensuring it is clean They now take the data in three fundamental operations First extract meaningful metrics from the data set For example in our airline case the data scientist would extract the average quarterly revenue per new customer Second identify the Key Performance Indicators that is only those metrics that will clearly show how the business is doing Third analyze the data to extract insights from it So why is the Exploratory Data analysis Stage important and the data science stepping stone Well consider this The airline company we are working for is running a marketing campaign and you have received the data You examine it and identify one of the metrics It indicates all the traffic to a page on the company s website Then you think about what a KPI could be in this case and you realize that a KPI would show the volume of the traffic to the same page but only if generated from users who have clicked on a link in your ad campaign to get there This way you can check if the ads you are positioning are working and driving customers to click on a link in turn this would determine whether you should continue to spend on ads or not Of course this is not where a data scientist s responsibilities conclude Data Science is about telling a story I repeat Data Science is about telling a story And crunching the numbers is just the introduction to the story So apart from handling strictly numerical information Data Science and specifically Exploratory data analysis are about visualizing the findings and creating easily digestible images supported by the most relevant numbers After all levels of management should be able to understand the insights from the data and inform their decision making And this is in the hands of the Data Scientist Data Scientists create dashboards and reports accompanied by graphs diagrams maps and other comparable visualizations to present the findings most relevant to the current objectives A real life example can be as follows Let s say you are a hotel manager would you keep the prices of rooms constant all year round Probably not when you want to attract visitors when the tourist season is not in bloom and if you want to capitalize on it when it is And would you inform your strategic decision to lower or increase room prices A data Scientist will now perform the above mentioned processes coming up with the best strategy Once all the work above has been done the information can now become the basis for predicting future values This now takes us to the next part which is now Predictive Analysis Predictive AnalysisHere now is where it becomes truly awesome Here now one can make forecasts and predictions The accuracy of your forecasts though will differ based on the methods and techniques you decide to apply And this is where the more popular Data Science concepts come into play Examples of such techniques are Neural Networks Deep Learning Time series and Random Forests But just as there is a distinction between traditional and big data there is also a distinction between traditional methods in predictive analytics and Machine Learning Traditional Methods In Predictive AnalyticsTraditional Data invites Traditional analytics like Linear Regression Cluster Analysis and Factor Analysis just to mention So what statistical knowledge do you need for traditional analytics in Data Science Most often Data Science Employs one of the below mentioned five analyses Linear RegressionLogistic RegressionCluster AnalysesFactor AnalysesTime Series Analysisa Linear Regression This method is used for quantifying casual relationships among the different variables included in the analysis You will use this if you need to assess the relationship between for example house prices the size of the house and the year they were built The model calculates the coefficients with which they can predict the price of a new house if you have the rest of the information available There is a linear line that governs the relationships between the size and the priceb Cluster AnalysisThis Exploratory Data Science technique is applied when the observations in the data form groups according to the same criteriaIt takes into account that some observations show similarities and facilitate the discovery f new significant predictors ones that were not part of the original conceptualization of the data c Factor AnalysesIf the cluster analysis is about grouping observations together this analysis is about grouping features together Data Scientists resort to using it to reduce the dimensionality of a problem For example if you have a questionnaire of questions and every questions are trying to determine a single general attitude This analysis will identify the factors Once a factor analysis identifies some factors they can be used for a regression that will deliver a more interpretable prediction A lot of other Data Science techniques are integrated like this d The Time Series AnalysisThis is a popular method for following the development of specific values over time It is widely used in economics and finance because their subject matter is stock prices and sales volume which are variables that are typically plotted against time e Logistic Regression Since not all relationships between variables can be expressed as linear Data Science makes use of methods such as logistic regression to create non linear models Logistic Regression Operate with s and s For Instance think about the process of hiring new staff Companies apply logistic regression algorithms to filter job candidates during the screening process If the algorithm estimates that the probability a prospective candidate will perform well in the company within the year is above it will return or a successful application Otherwise will return and the candidate won t be called in for the interview The above is at the core of the traditional methods for predictive analytics in Data Science Machine LearningMachine learning compared to Traditional methods of predictive analytics is far much equipped to handle big data As you can imagine machine learning steps on the shoulders of classical statistical forecasting People in the data science industry refer to some of these methods as machine learning too but when I talk about machine learning I am referring to newer smatter better methods like Deep Learning Don t worry I am still going to tackle this subject and will explain everything clearly	2022-04-03 17:26:24
海外TECH	DEV Community	How to reload an SSR Page	https://dev.to/perkinsjr/how-to-reload-an-ssr-page-2a9g	How to reload an SSR PageWhen using SSR you might need to update the data that has been served because a user has done something such as updating a database or subscribed to your product This poses a problem Next js doesn t have a feature like refetchprops but if the team over at Vercel want to implement it I am all for it One solution would be just to hard refresh the page but that feels almost an anti pattern So how do we do tackle this without using a hard refresh First we should talk about the usual SSR flow that we think of when talking about it The usual SSR flowWhen we think of Server Side Rendering we have a two flows in mind and it usually goes something like A user clicks a link that sends them to your website Next js calls the getServerSideProps method and generates the HTML with the data from your api s The user receives that HTML file and React rehydrates on the client OrThe User is already on your site and they click a Next Link to navigate to the server rendered page Next js calls your getServerSideProps method on the server but instead of generating an HTML file as in scenario one It sends the data as JSON instead React uses that data as the props when rendering the new page in browser This is what I love about Next js two different scenarios handled slightly differently to increase performance and the user is none the wiser The solutionSo the solution is to use built in functionality of Next js router Using this we can ask Next js to retrieve the latest from SSR without a hard refresh If you are in a rush here is the solution import useRouter from next router import useRouter from next router export default function YourPage props const router useRouter const dataToUpdate some object API that updates your DB const update fetch api update method PUT body JSON stringify dataToUpdate if update status ask next router to replace the current path with the current path router replace router asPath How does this work When describing SSR the second path we talked about how Next js returns a JSON when you use Next Link through a client side transition This is exactly what we are doing by using router replace we are telling Next js to perform a client side transition If you are wondering what router replace does it does the exact same thing as route push except it doesn t add history to the stack This means if the user hits the back button it will perform as expectedThis means that when this client side transition happens getServerSideProps fires and the JSON returns with the latest information from your database or API	2022-04-03 17:25:39
海外TECH	DEV Community	Adding Google Analytics using Publish	https://dev.to/emin_ui/adding-google-analytics-using-publish-19c3	Adding Google Analytics using PublishFor regular front end dev this is a quick fix Just add some scripts to your head and you can be on your merry way But if you are a Swift developer playing with publish it s a bit different Still quite easy though So you have your Publish made website ready to go but now you want to track some stuff with Google Analytics or another analytics website This quick tutorial should help out If you have some front end experience it will definitely be helpful and easier as you are aware how these scripts are constructed But for someone like myself first ever language is Swift it can be a bit confusing Publish is an awesome tool that helps us create a website in a jiffy and we can use standard HTML tags no problem But scripts are a bit of a different beasts and it took me some trial and error Getting the tracking codeFirst things first you need to register on google Analytics and follow all the steps until you are logged in This is pretty standard and google already has a nice on boarding process so you should have no issues there If you do let me know on emin roblack gmail comNext we need to get the tracking code which is inserted into every HTML we want to track using analytics This is done by going to the ADMIN menu inside your google dashboard and then Tracking Info gt Tracking Code On that page you should find some code that looks a bit like in the snippet below Copy all that and let s get Swifty lt Global site tag gtag js Google Analytics gt lt script async src gt lt script gt lt script gt window dataLayer window dataLayer function gtag dataLayer push arguments gtag js new Date gtag config UA lt script gt Adding the head scriptNow we get to the fun stuff We are going to create an extension on the Node so adding this tracker on multiple pages is easier in the future So go to your theme file or a default Foundation theme if you are using that one Whatever the case is you should be able to find madeIndexHTML function that generates your homepage HTML There near the top and OUTSIDE of your Theme extension add the following code public extension Node where Context HTML DocumentContext static func googleTrackerHead gt Node head script src script window dataLayer window dataLayer function gtag dataLayer push arguments gtag js new Date gtag config UA public extension Theme Using the code you got from Google Analytics replace the strings in the above code with your own tracker info Now in general you should have your extensions in a separate Swift file like Node Extensions swift or similar But for this I placed it in the same Theme file as I don t plan to extend as much and this is a quite specific use case We have created a function which will return a head whenever called so next we just need to call it Inside func makeIndexHTML for index and under the current head add our newly created function lang context site language head for index on context site stylesheetPaths stylePaths googleTrackerHead body I commented out the current code which you should not edit just so you can see where to place our new function The waiting gameNow we play the waiting game If you did everything correctly you should start getting some information in your Google Analytics after a day or so On the page where you got the script from there is a Send Test Traffic button and it says that it takes about seconds to show some results but for me it was much much longer Thank you for reading you lovely person ️Lets hook up on Twitter	2022-04-03 17:22:04
海外TECH	DEV Community	On the road again with New Relic in 2022	https://dev.to/newrelic/on-the-road-again-with-new-relic-in-2022-2l4g	On the road again with New Relic in This post originally appeared on The Observatory As a former road warrior I attended between three and ten events every year not to mention trips from my base of operations an undisclosed remote location code named my house in Cleveland to various corporate offices I looked forward to each trip and saw it for the privilege it is Now after more than two years of a global pandemic there is so much I m anticipating as I m heading out to LeadDev NYC on April Even before I set foot in the Metropolitan Pavilion I m thrilled about Being back in New York City itself where I spent my college years just years ago Seeing my New Relic colleaguesーin some cases for the first time Sampling a significantly wider range of kosher cuisine than my hometown provides And once I step onto that conference floor that s when the real fun will start Staying true to the name of the event there s a slate of leadership workshops on April geared to every level of practitionerーfrom the people who just want to be better devs to those who want to move into leadership roles to leaders who want to learn how to scale up Then there are the speaking sessions covering everything from coding to career to on call systems and a conversation about Capuchin monkeys that I m not going to miss The sessions that caught my eye include Effective observability in microservice architectures on April focuses on the observability practices and microservice architecture patterns that align well Software estimation embracing nuance and controlled chaos on April promises a primer on software estimation so you can learn steps to confidently deliver on your commitments Equipping your team to support junior developers on April discusses building junior inclusive practices through active reflection sustainable processes and a focus on empathetic communication The Map Book Visual storytelling with roadmaps on April covers how to use an illustrative roadmap to tell a story and inform your team on needed details in an entertaining intuitive way Blame shame and panic how not to respond when things go wrong on April explores reactions to being in the chain of responsibility protecting teams and helping them feel safe enough to take responsibility and grow from challenging experiences Calling out a terrible on call system on April describes how the core streaming team at Netflix improved their on call system What Capuchin monkeys know that engineering leaders don t on April advises how managers can retain top talent by making their teams happier and more productive Also MONKEYS I m especially eager to hear the Equipping your team to support junior developers as I m a junior dev myself Yes at the tender age of after years in IT it s possible to be a junior dev And I hope that s one of speaker Aisha Blake s points “Junior is a transitory and temporary state of being How we structure our teams to help new folks comfortably enter and establish themselves as junior and then quickly grow in confidence experience and fluency is a key driver of innovation Wherever you see yourself on the spectrum you can check out the full list of workshops and sessions at leaddev com leaddev new york agenda I can t say for sure what the highlight will be but you can bet I ll be posting my reactions after the event is over	2022-04-03 17:20:59
海外TECH	DEV Community	Pretty Print, please	https://dev.to/emin_ui/pretty-print-please-1hh6	Pretty Print pleaseWhen doing some light debugging most of us tend reach for the good old print statement right Yeah it s just me You might add some amp amp amp or to make your print REALLY stand out from all that output but after a while it gets really hard to find anything in there That is where this helper method comes in And also EMOJIS I found this awesome post by Andyy Hope where he really goes into detail how everything works so if you are interested I recommend going over that whole post It has parts and is WELL worth a read For all of you anxious to try it out right away behold this helper method ️Create a new Swift file in your project and paste this code import Foundationenum log case ln String case obj String Any case error Error case url String case any Any case date NSDate postfix operator postfix func target log guard let target target else return func log lt T gt emoji String string String object T if DEBUG print emoji string → object endif switch target case ln let line log ️ line case obj let string let obj log string obj case error let error log ️️️ error case url let url log url case any let any log ️ any case date let date log date To make use of that DEBUG flag find the following Go to your Project SettingsOpen Build SettingsIn the search type Flag Open Swift Compiler Custom Flags and Active Compilation ConditionsFor Debug insert a value gt DEBUG And now for the fun part Anywhere in your code use thislog ln So long PRINT Been nice knowin ya That prints ️→So long PRINT Been nice knowin ya Important that little at the very end is very important That is a postfix operator and without it the log won t print out Andyy goes over that in detail in his post so head on there if you are interested how all that works You can even use your own character but Andyy recommended it and who am I to doubt Andyy Other available logsInputOutputlog ln Text ️→Textlog obj My Object Object My Object →Object Propertieslog error error ️️️→Error Propertieslog url undeadpixel dev →undeadpixel devlog date Date → log any Whatever you want ️→Whatever You wantIt is also quite easy to spot the logs that you added Sometimes when I want to search over the project for a specific print and I type print in the searchBar all of the prints from every file are there Now number of results is far narrower so my own code is easier to spot That s it Feel free to modify the helper and add your own emoticons or customise it to your hearts content Thank you for reading you superb person ️Get in touch on TwitterCheers	2022-04-03 17:18:17
海外TECH	DEV Community	Missing compliance pain in the 🐴	https://dev.to/emin_ui/missing-compliance-pain-in-the-4nak	Missing compliance pain in the For the most part uploading applications on the AppStore is really straightforward But you know that one thing you need to do after each upload has been processed Yeah that one missing the code compliance thing It s definitely there for a reason If you are using any kind of encryption you need to state that properly But for the MOST of us I believe which do some low level type apps and rarely use encryption it has become one thing that is pain in the ass and with each upload you need to wait for the processing to complete so you can just tap that one radio button Well no more It is surprisingly simple So simple it makes you wonder why isn t it there by default Just add this key ITSAppUsesNonExemptEncryption to your Info plist and set it to NO And Boom You are now ready to upload without any hassle And next time your build is processed it goes straight to your Testflight Thank you for reading you superb person ️Get in touch on TwitterConsider subscribing to the newsletter below if you loved the content Cheers	2022-04-03 17:15:05
海外TECH	DEV Community	Lottie Animations 🐘	https://dev.to/emin_ui/lottie-animations-an8	Lottie Animations This library has been out there for a while and it keeps getting better I literally thought everyone knew about it but after a recent talk with a friend of mine I realised that is not the case So tap play on that coding playlist you have and let s do this It s SO easy Step Install CocoaPodsYou could do this with both SPM or Cococapods but let s use the latter in this tutorial because reasons If you already know how to handle cocoapods skip forth this is not the section you are looking for Open up the Terminal app and paste type this sudo gem install cocoapodsThis will install cocoapods dependencies on your Mac You only need to do this once on your machine and you are good to go for any future pods not related to this project Next you need to navigate to your project directory using the Terminal app It s pretty straightforward and there are few way to do it If you are not familiar with navigation using standard terminal commands you can always just drag the project folder to your terminal window and press Enter For example if you placed your folder on the desktop path should look something like this Desktop LottieTestNote If you are having issues with the Terminal and are not familiar with it reach out to me on Twitter I will love to help out While inside your project folder you need to prepare the project for your lovely pods It will create a Podfile to which you will add all the pods you want to install Think of it as a wish list and Cococapods as the Santa So type this pod initAfter some quick setup it will be done and now you need to open the Podfile Enter this into your Terminal window open PodfileIt should look something like this Uncomment the next line to define a global platform for your project platform ios target LottieTest do Comment the next line if you don t want to use dynamic frameworks use frameworks Pods for LottieTestendFirst replace the platform line with the right minimum version of iOS you plan to support It really depends on your project and Cocoapods will snag the right version of the pod based on this At the moment we are close to iOS so I will use iOS as the minimum version You also need to remove the since that is a comment syntax like in Swift platform ios And finally we can tell our Santa what we are after this year So under Pods for LottieTest line enter this pod lottie ios Save that Podfile and close it In your Terminal app you should be still inside your project folder If your project is opened in Xcode close it and type in this final command pod installIf you are doing this for the first time I know it seems like a lot and probably confusing but very soon you will be doing this with your eyes closed Your finger will know what to do Note When using Cocoapods once pods are installed you will no longer use the standard file to launch the project or in our case ️LottieTest xcodeprojFrom now on you need the use the newly generated project file ️LottieTest xcworkspaceYou can see that the extension is different and file icon is mostly white instead of blue Open that xcworkspace file and let s get to the good stuff Step Getting the JSONOnce the pod is installed we only have a few steps to go through to make our app come alive If you have some animation skills you could easily create your own animations as there is a simple plugin that can convert most animations into JSON files You can go on LottieFiles for more info on how to do that or just browse that site and find the right animation for you Most of them are free to use and some more complex ones do cost but are well worth it For this example i will use this crazy awesome elephant but you are free to use anything you want as usage is completely identical Tap the download button and then choose Lottie JSON But before that look at how crazy this mt cka is Love it Note Before importing the JSON file make sure to rename it to something meaningful When you try to preview it inside the Xcode it tends to get buggy since this json contains LOTS of text so it might become unresponsive Hoping this will be handled soon In any case there is nothing much you can do with the animation if you try to edit the contents anyway So move that file into your project navigator but OUTSIDE the Assets xcassets folder and we should be ready for the next step Step Pod import and setupYou ve been through quite few steps of setting everything up and you are ready to see the fruits of your labour In your Main storyboard place the UIView in the middle of the screen and possibly add some constraints so it would take up the whole screen or just a part of it Important While your view is selected open the Identity Inspector and change the class to AnimationView and module to LottieInside your ViewController swift import the Lottie pod You should have the autocomplete come up as soon as you start typing If you don t then you probably had some issues with the installation so go over that step again import LottieNext create an outlet for your view inside ViewController swift Step Animation time Your project is not ready for any animations you can throw at it Let s to exactly that Inside viewDidLoad type this lottieView animation Animation named elephant Make sure NOT to include the extension json for the filename This will load the animation but it won t play it So add this under that line lottieView play Thats it Look at him go You can further edit this animation by modifying contentMode or loop etc feel free to go through the documentation and explore Here are few exampleslottieView backgroundColor clearlottieView contentMode scaleToFilllottieView loopMode loop autoReverse playOnceThank you for reading Feel free to get in touch on Twitter twitter Consider subscribing to the newsletter below if you loved the content Or don t Free country Cheers	2022-04-03 17:11:16
海外TECH	DEV Community	What is a DevCard?	https://dev.to/tmchuynh/what-is-a-devcard-4g10	What is a DevCard Table of Contentsdaily devDevCardsAdding Your DevCard to Your GitHub README md daily devWhat is daily dev daily dev is an open source browser extension that helps developers stay updated with the latest programming newsIt s an extension available on Google Chrome Brave Microsoft Edge and Firefox It is there to help you stay updated on articles from multiple platforms including hashnode dev to Medium DevOps Hacker News Product Hunt and many more daily dev allows you to follow tags that interest you to personalize your feed and suggest new sources for content And each time you open a new tab you ll get an updated feed of articles ready for you to browse How easy To read more about customizing your feed click here Account DetailsYou can set personal information such as Name username and bioCompany and job titleTwitter GitHub and Hashnode accountsWebsite link Reputation Points Reputation is just as it sounds a rough estimation of how much the community trusts you through positive feedback they give on your articles and comments The more reputation you earn the more privileges and tools you get access to on daily dev Note Your reputation points are publicly visible on your profile You earn reputation as follows Your comments gets up voted on Your comments get features Your article gets up voted Your content report leads to a moderator action DevCardsEver want to show off how many articles you read your favorite topics and or publications DevCards easily help you do just that in a beautiful and simple way There are even limited edition cards throughout the year during holidays ie Halloween Christmas etc You can activate your card right here and embed it into your website or GitHub README md Adding Your Card to Your README md	2022-04-03 17:08:45
海外TECH	DEV Community	How to Build a Good API That Won’t Embarrass You	https://dev.to/stx-next/how-to-build-a-good-api-that-wont-embarrass-you-5hi2	How to Build a Good API That Won t Embarrass YouEveryone and their puppy wants an API these days APIs first gained popularity around years ago Roy Fielding introduced the term REST in his doctoral dissertation in the year It was the same year that Amazon Salesforce and eBay introduced their APIs to developers around the world forever changing the way that we build software Before REST the principles in Roy Fielding s dissertation were known as the “HTTP object model and you ll see why that s important soon As you read on you ll also see how to determine if your API is mature what are the main qualities of a good API and why you should focus on adaptability when building APIs The basics of RESTful architectureREST stands for Representational State Transfer and it has long been the holy grail of APIs for services first defined by Roy Fielding in his dissertation It s not the only way to build APIs but it s the kind of standard that even non developers know about thanks to its popularity There are six key characteristics of RESTful software Client Server architectureStatelessnessCacheabilityLayered systemCode on demand optional Uniform interfaceBut that s too theoretical for daily usage We want something more actionable and that s going to be the API maturity model The Richardson Maturity ModelDeveloped by Leonard Richardson this model combines the principles of RESTful development into four easy to follow steps The higher you are in the model the closer you get to the original idea of RESTful as defined by Roy Fielding Level The swamp of POXA level API is a set of plain XML or JSON descriptions In the introduction I mentioned that before Fielding s dissertation RESTful principles were known as the “HTTP object model That s because the HTTP protocol is the most important part of RESTful development REST revolves around the idea of using as many inherent properties of HTTP as possible At level you don t use any of that stuff You just build your own protocol and use it as a proprietary layer This architecture is known as Remote Procedure Call RPC and it s good for remote procedures commands You usually have one endpoint you can call upon to receive a bunch of XML data One example of this is the SOAP protocol Another good example is the Slack API It is a bit more diverse it has several endpoints but it s still an RPC style API It exposes various functions of Slack without any added features in between The code below allows you to post a message to a specific channel Even though it s a level API according to Richardson s model it doesn t mean it s bad As long as it s usable and properly serves the business needs it s a great API Level ResourcesTo build a level API you need to find nouns in your system and expose them through different URLs like in the example below api books will take me to the general book directory api profile will take me to the profile of the author of those booksーif there s only one of them To get the first specific instance of a resource I add an ID or another reference to the URL I can also nest the resources in the URLs and show that they re organized in a hierarchy Going back to the Slack example here s how it would look like as a level API The URL changed instead of api chat postMessage now we have api channels general messages The “channel part of the information has been moved from the body to the URL It literally says that using this API you can expect a message to be posted to the general channel Level HTTP verbsA level API leverages HTTP verbs to add more meaning and intention There are quite a few of these verbs I ll just use a fundamental subset PUT DELETE GET POST With these verbs we expect different behaviors from URLs containing them POSTーcreate new data PUTーupdate existing dataDELETEーremove dataGETーfind the data output of a specific id fetch a resource or an entire collection Or using the previous api books example What does “safe and “idempotent mean A “safe method is one that will never change data REST recommends that GET should only fetch data so it s the only safe method in the above set No matter how many times you call a REST based GET method it should never change anything in the database But it s not inherent in the verbーit s about how you implement it so you need to make sure that this works All other methods will change data in different ways and can t be used at random In REST GET is both safe and idempotent An “idempotent method is one that won t produce different results over many uses DELETE should be idempotent according to RESTーif you delete a resource once and then call DELETE for the same resource a second time it shouldn t change anything The resource should already be gone POST is the only non idempotent method in REST specifications so you can POST the same resource several times and you ll get duplicates Let s revisit the Slack example and see what it would look like if we used HTTP verbs in it to do more operations We could use POST to send a message to the general channel We could fetch messages from the general channel with GET We could delete messages with a specific ID with DELETEーwhich gets interesting because messages are not tied to specific channels so I might want to design a separate API for removing messages This example shows that it s not always easy to design an API there are plenty of options to choose and trade offs to make Level HATEOASRemember text only computer games without any graphics You just had a lot of text with descriptions of where you are and what you can do next To progress you had to type your choice That s kind of what HATEOAS is Text game APIHATEOAS stands for “Hypermedia as the Engine of Application State When you have HATEOAS whenever someone uses your API they can see other things they can do with it HATEOAS answers the question “Where can I go from here But that s not all HATEOAS can also model data relationships We can have a resource and we don t have authors nested in the URLーbut we can post the links so if someone s interested in authors they can go there and explore This is not as popular as other levels of the maturity model but some developers use it One example is Jira Below is a chunk from their search API They nest links to other resources you can explore as well as a list of transitions for this issue Their API is quite interesting because of the “expand parameter at the top It allows you to choose fields where you don t want links and prefer the full content instead Another example of using HATEOAS is Artsy Their API heavily relies on HATEOAS They also use JSON Plus call specifications which imposes a special convention of structuring links Below is an example of pagination one of the coolest examples of using HATEOAS You can provide links to next previous first last pages as well as other pages you find necessary This simplifies the consumption of an API because you don t need to add the URL parsing logic to your client or a way to append the page number You just get the client ready to use already structured links What makes a good APISo much for Richardson s model but that s not all that makes a good API What are other important qualities Error exception handlingOne of the fundamental things I expect from an API that I consume is that there needs to be an obvious way to tell if there s an error or an exception I need to know if my request was processed or not Lo and behold HTTP also has an easy way to do that HTTP Status Codes The basic rules governing status codes are xx is OKxx means your princess is in another castleーthe resource you re looking for is in another placexx means the client did something wrongxx means the server failedAt the very least your API should provide xx and xx status codes xx are sometimes generated automatically For example the client sends something to the server it s an invalid request the validation is flawed the issue goes down the code and we have an exceptionーit will return a xx status code If you want to commit to using specific status codes you ll find yourself wondering “Which code is best for this case That question isn t always easy to answer I recommend you go to RFC which specifies these status codes they give a wider explanation than other sources and tell you when these codes are appropriate etc Luckily there are several resources online that will help you choose like this HTTP status code guide from Mozilla DocumentationGreat APIs have great documentation The biggest problem with documentation is usually finding someone to update it as the API grows One great option is self updating documentation that isn t detached from the code For example comments aren t connected to the code When the code changes the comments stay the same and become obsolete They can be worse than no comments at all because after a while they ll be providing false information Comments don t update automatically so developers need to remember to maintain them alongside the code Self updating documentation tools solve this problem One popular tool for this is Swagger a tool built around the OpenAPI specification which makes it easy to describe your API The cool part of Swagger is that it s executable so you can play around with the API and instantly see what it does and how it changes To add self updating to Swagger you need to use other plugins and tools In Python there are plugins for most major frameworks They generate descriptions of how API requests should be structured and define what data comes in and what comes out What if you don t want Swagger and prefer something simpler A popular alternative is Slateーa static API you can build and expose on your URL Something in between that s also worth recommending is a combination of widdershins and apihtml It ll allow you to generate Slate like docs from Swagger s definition CacheabilityCacheability may not be a big deal in some systems You might not have a lot of data that can be cached everything changes all the time or maybe you don t have a lot of traffic But in most cases cacheability is crucial for good performance It s relevant to RESTful APIs because the HTTP protocol has a lot to do with cache for example HTTP headers allow you to control cache behaviour You might want to cache things on the client side or in your application if you have a registry or value store to keep data But HTTP allows you to get a good cache essentially for free so if it s possibleーdon t walk away from a free lunch Also since caching is part of the HTTP spec a lot of things that participate in HTTP will know how to cache things browsers which support caching natively as well as other intermediary servers between you and the client Evolutionary API designThe most important part of building APIs and modern software in general is adaptability Without adaptability development time slows down and it becomes harder to ship features in a reasonable time especially when you re facing deadlines “Software architecture means different things in different contexts but let s adopt this definition for now Software architecture the act art of dodging decisions that prevent change in the future With that in mind when you design your software and have to choose between options with similar benefits you should always choose the one that s more future proof Good practices aren t everything Building the wrong thing in the right way is not what you want to do It s better to adopt a growth mindset and accept the fact that change is inevitable especially if your project is going to continue growing To make your APIs more adaptable one of the key things to do is to keep your API layers thin The real complexity should be shifted down APIs shouldn t dictate the implementationOnce you publish a public API it s done it s immutable you can t touch it But what can you do if you have no other choice but to commit to a weirdly designed API You should always look for ways to simplify your implementation Sometimes controlling your APIs response format with a special HTTP header is a leaner solution compared to building another API and calling it v APIs are just another layer of abstraction They shouldn t dictate the implementation There are several development patterns that you can apply in order to avoid this issue API gatewayThis is a facade like development pattern If you break up a monolith into a bunch of microservices and want to expose some functionalities to the world you simply build an API gateway that acts like a facade It will provide a uniform interface for the different microservices which may have different APIs use different error formats etc Backend for frontendIf you have to build one API to satisfy a bunch of different clients it might be difficult Decisions for one client will impact the functionality for others Backend for frontend saysーif you have different clients that like different APIs say mobile apps which like GraphQL just build it for them This works only if your API is a layer of abstraction and it s thin If it s coupled to your database or it s too big with too much logic you won t be able to do this GraphQL vs RESTfulThere s a lot of hype for GraphQL It s kind of the new kid on the block but it has already gathered a lot of fans So much so that some developers claim that it will dethrone REST Even though GraphQL is much newer compared to the RESTful specification they share a lot of similarities The biggest downside of GraphQL is cacheabilityーit has to be implemented in the client or in the application There are client libraries out there that have caching capabilities built in like Apollo but it s still harder than using the almost free cacheability provided by HTTP Technically GraphQL is level in terms of the Richardson model but it has qualities of a good API You might not be able to use several HTTP functionalities but GraphQL is built to solve specific problems One killer use for GraphQL is aggregating different APIs and exposing them as one GraphQL API GraphQL does wonders with underfetching and overfetching which are issues where REST APIs can be difficult to manage Both are related to performanceーif you underfetch you re not using API calls efficiently so you have to make a lot of them When you overfetch your calls take result in a bigger data transfer than necessary which is a waste of bandwidth The comparison of REST vs GraphQL is a great segue into summarizing the most important qualities of a good API You need a clear representation for dataーRESTful gives you that in the form of resources You need a way to show which operations are availableーRESTful does that by combining resources with HTTP verbs There needs to be a way to confirm that there s an error exceptionーHTTP status codes do this possibly with responses that explain them It s nice to have discoverability and possibility to navigateーin RESTful HATEOAS takes care of that It s important to have great documentationーin this case executable self updating docs can take care of that which goes beyond the RESTful spec Last but not leastーgreat APIs should have cacheability unless your specific case dictates that it s not necessary The biggest difference between REST and GraphQL is the way they handle cacheability When you build your API the REST way you get HTTP cacheability essentially for free If you choose GraphQL you need to worry about adding a cache to your client or your application Further readingThis article was based on a recent presentation by Sebastian Buczyński Check out his blog Breadcrumbs Collector and grab his ebook Implementing the Clean Architecture For more reading about APIs check out Phillip Sturgeon s blog or his great book called Build APIs You Won t Hate	2022-04-03 17:06:02
海外TECH	DEV Community	Pygame Boilerplate Apr 2022	https://dev.to/waylonwalker/pygame-boilerplate-apr-2022-2p8o	Pygame Boilerplate Apr I m poking a bit into gamedev Partly to better understand partly because it s stretching different parts of my brain skillset than writing data pipelines does but mostly for the experience of designing them with my yo Wyatt pygame boilerplatesI ve seen several pygame boilerplate templates but they all seem to rely heavily on globl variables That s just not how I generally develop anything I want a package that I can pip install run import test all the good stuff My current starterWhat currently have is a single module starter package that is on github so that I can install it and start building games with very little code InstallationSince it s a package on GitHub you can install it with the git prefix pip install git Example GameYou can make a quick game by inheriting from Game and calling run This example just fills the screen with an aqua color butyou can put all of your game logic in the game method from pygame starer import Gameclass MyGame Game def game self self screen fill if name main game MyGame game run The starterHere is what the current game py looks like I will probably update it as time goes on and I learn more about the things I want to do with it from typing import Tupleimport pygameclass Game def init self screen size Tuple int int caption str pygame starter tick speed int screen size Tuple int int The size of the screen you want to use defaults to p caption str the name of the game that will appear in the title of the window defaults to pygame starter tick speed int the ideal clock speed of the game defaults to Example Game You can make a quick game by inheriting from Game and calling run This example just fills the screen with an aqua color but you can put all of your game logic in the game method python from pygame starer import Game class MyGame Game def game self self screen fill if name main game MyGame game run pygame init pygame display set caption caption self screen size screen size self screen pygame display set mode self screen size self clock pygame time Clock self tick speed tick speed self running True self surfs def should quit self check for pygame QUIT event and exit for event in pygame event get if event type pygame QUIT self running False def game self This is where you put your game logic def reset screen self fill the screen with black self screen fill def update self run one update cycle self should quit self reset screen self game for surf in self surfs self screen blit surf pygame display update self clock tick self tick speed def run self run update at the specified tick speed until exit while self running self update pygame quit if name main game Game game run	2022-04-03 17:04:47
海外TECH	DEV Community	Converting Date to String and back	https://dev.to/emin_ui/converting-date-to-string-and-back-p6l	Converting Date to String and backThere you are coding away all is fine birds are chirping keys are not getting stuck on your MBPro but in the distance Date approaches Jokes aside dates are not that hard to work with most of the time Accuracy isn t that important for majority of apps but if you go down the rabbit hole of dates there is no telling where you might end up Computerfile said it best in this video so do check it out as it is quite fun and it will gives you a bit more insight If you create a Date in your code and print it you will get something like so ️var today Date print today prints gt When working with an API you will most probably get T Looks like a long string of something right But fear not it s actually very well structured and quite logical once you know what to look for The most common standard or standard standard is ISO and this is how it is constructed And now all of that makes complete sense Except for that Z thing Like Zee UTC Get that Date Now that we know what we are looking at first we need to convert String gt Date Info we got from backend let stringDateFromAPI T Creating a formatter and setting the current localelet formatter DateFormatter formatter locale current Telling the formatter what what kind of format we are expecting formatter dateFormat yyyy MM dd T HH mm ssZ Creating the date objectlet dateFromAPI formatter date from stringDateFromAPI print dateFromAPI Unknown But now its a date not a string We got our Date all nice and tidy From here on we have LOADS of choices for time formatting Keep in mind that the hours and minutes are based on the current user location since we used current for the locale setting In case that you want to use the source time just omit that formatter setting This date can be converted to a proper string now in various ways Here I will show you main approaches that I use Going Native  ⌥ Swift DateFormatter already has some pre defined formats that might get the job done Take a look at the print output for each If you don t need a lot of control of your date feel free to use these ️ Since dateFromAPI is an optional Date I am using todays date as a default let nativeFormatter DateFormatter nativeFormatter locale currentnativeFormatter dateStyle fullprint nativeFormatter string from dateFromAPI Date Tuesday January nativeFormatter dateStyle longprint nativeFormatter string from dateFromAPI Date January nativeFormatter dateStyle mediumprint nativeFormatter string from dateFromAPI Date Jan nativeFormatter dateStyle noneprint nativeFormatter string from dateFromAPI Date nativeFormatter dateStyle shortprint nativeFormatter string from dateFromAPI Date Custom Formatting ⌥ In case you need a more granulated control just create your own custom formatter Maybe even add some emojis to it ‍ ️let customFormater DateFormatter customFormater locale currentcustomFormater dateFormat MMM d yyyy print customFormater string from dateFromAPI Date Jan When creating a custom format pay attention which notation you are using for the dateFormat It can get a wee bit touchy feely For example lower caps m is used for minutes while capital M for months Here are some examples below and their output ️InputOutputMMMJanMMMdddyyyyyyyyyyHH mm hh mm hh mm a PMETueYou are now able to mix n match to create your custom DateFormatter You will fear the dates no longer As promised here is the extension on String you can use for your projects and handle most API responses extension String func convertToReadableDate gt String let formatter DateFormatter formatter locale current formatter dateFormat yyyy MM dd T HH mm ssZ guard let dateFromAPI formatter date from self else return nil formatter dateFormat MMM d yyyy return formatter string from dateFromAPI Usage label text someDateString convertToReadableDate Thank you for reading Feel free to get in touch on TwitterCheers	2022-04-03 17:04:28
ニュース	@日本経済新聞 電子版	ロシア、来月の「勝利宣言」意識か　南・東部制圧へ攻勢 https://t.co/8n1ly8nwhu	https://twitter.com/nikkei/statuses/1510677685915496449	勝利宣言	2022-04-03 17:56:42
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ビジネス	ダイヤモンド・オンライン - 新着記事	【シニア起業】40代からの「副業」が最も多い理由 - 40代からは「稼ぎ口」を2つにしなさい	https://diamond.jp/articles/-/300858	新刊『代からは「稼ぎ口」をつにしなさい年収アップと自由が手に入る働き方』では、余すことなく珠玉のメソッドを公開しています。	2022-04-04 02:55:00
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