投稿時間:2022-03-27 21:20:13 RSSフィード2022-03-27 21:00 分まとめ(22件)

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python	Pythonタグが付けられた新着投稿 - Qiita	Python(Django)でダッシュボード作る(WSL2)	https://qiita.com/akitkat/items/73e629e51aac36f0fc37	日本語のドキュメントもあるので助かりますPythonがインストールされているか確認するpythonVでインストールしてなかったらPythonをインストールするsudoaptgetupdatesudoaptinstallpythonypipがインストールされているか確認するpipVでインストールしてなかったらpipをインストールするsudoaptgetupdatesudoaptinstallpythonpipyダッシュボードのテーマをclone今回は以下を使っていこうと思います。	2022-03-27 20:33:49
js	JavaScriptタグが付けられた新着投稿 - Qiita	自作大富豪の再宣伝です	https://qiita.com/doumeishi/items/db79ec77cd0477342bf5	android	2022-03-27 20:44:04
Ruby	Rubyタグが付けられた新着投稿 - Qiita	Rubyスクリプトをどうコンパイルするのか？	https://qiita.com/wangqijiangjun/items/57d4ae47c8e2af8f798b	まとめまとめると、YARVはこれまで見てきたようなデータ構造をしていて、一番大事なポイントは、スタックマシンであることです。	2022-03-27 20:52:45
AWS	AWSタグが付けられた新着投稿 - Qiita	各種ブラウザでAWS Extend Switch Roles～6つ以上のスイッチロールを管理	https://qiita.com/emiki/items/4864a9c91d08faeb845b	Configuration を クリック する 。	2022-03-27 20:38:30
Ruby	Railsタグが付けられた新着投稿 - Qiita	Rubyスクリプトをどうコンパイルするのか？	https://qiita.com/wangqijiangjun/items/57d4ae47c8e2af8f798b	まとめまとめると、YARVはこれまで見てきたようなデータ構造をしていて、一番大事なポイントは、スタックマシンであることです。	2022-03-27 20:52:45
技術ブログ	Developers.IO	Autifyのテストシナリオをテストプラン機能でスケジュール実行してみた	https://dev.classmethod.jp/articles/scheduling-autifys-test-scenario-with-the-test-plan-function/	autify	2022-03-27 11:55:04
技術ブログ	Developers.IO	AI가 코딩하는 시대 도래.? AI를 기반으로 개발자에게 코드를 제안해주는 GitHub Copilot!!	https://dev.classmethod.jp/articles/introduce-github-copilot/	AI가코딩하는시대도래 AI를기반으로개발자에게코드를제안해주는GitHub Copilot 안녕하세요 클래스메서드MAD 사업부의정현재입니다 얼마전신청하였던GitHub Copilot Technical Preview 사용이승인이되서여러가지만져보았는데요 이번블로그에서는	2022-03-27 11:20:22
技術ブログ	Developers.IO	Parsec Relay ServerでParsec Error 6023&6024を解決し、Parsecホストに接続できました	https://dev.classmethod.jp/articles/use_parsec_relay_server_to_ensure_p2p_connections/	parsec	2022-03-27 11:03:25
海外TECH	Ars Technica	Leica’s new camera puts skill back into focus	https://arstechnica.com/?p=1843684	ability	2022-03-27 11:30:17
海外TECH	DEV Community	Introduction to Machine Learning and Hello World in Neural Networks	https://dev.to/nawodyaishan/introduction-to-machine-learning-and-hello-world-in-neural-networks-51e1	Introduction to Machine Learning and Hello World in Neural NetworksHi fellows Here we are going to build basic pattern recognition models using neural networks Neural Networks are a more advanced topic in machine learning that belongs to deep learning butin this basic introductory example we use the external libraries to make things easy a little bit First of you have to have some basics prerequisites of machine learning What is Machine Learning Yes as the topic says machines are learning Machine learning is all about how machines are learning and how do we teach the machines to learn In so near future machines can learn and do the thing that we humans do From the computer programming perspective traditionally we write computer programs by defining rules and data by ourselves to the computer As the following diagram the user gives rules and data and answers come out But in a machine learning scenario we give answers and data to the machine the computer and it produces the rules the connection between answers and data itself Basically the thing happening here is we give the exiting examples to the computer which we cant figure out how it s happening and through machine recognizes the how it happening by the rules Let s take a quick simple example Here I show you a Human coded BMI Calculator using Python height input as h and weight in as w h float input Please Enter Your Height in cm w float input Please Enter Your Weight in kg BMI w h As above code we can calculate each person s BMI index and give feedback on their inputs as follows print f You BMI Index is BMI if BMI lt print You are slightly underweight elif BMI lt print You are pretty healthy elif BMI lt print You are slightly overweight elif BMI lt print You are severely overweight elif BMI lt print You are obese else print You are severely obese Get Some Help But what if we want to calculate different health indexes using the same or different input data like Body Adiposity Index AKA BAI Waist to Hip etc this approach has to be failed So as previous diagrams explain we teach computers that this is BMI and how to calculate BMI this is BAI how to calculate that using given example data and outputs So those will become Answers and Data according to our previous diagrams what is happening inside is the computer is learning the pattern of data and answers using machine learning algorithms So this has opened a new horizon in the computer science and data science world Machine Learning Road MapIntroduction to Machine LearningSupervised Learning and Linear RegressionClassification and Logistic RegressionDecision Tree and Random ForestNaïve Bayes and Support Vector MachineUnsupervised LearningNatural Language Processing and Text MiningIntroduction to Deep LearningTime Series Analysisif you want to study machine learning in depth I recommend these courses for a successful career through machine learning Simple Number Pattern Prediction using Neural NetworksHere I am going to show you how to do a simple pattern recognition like above using Neural Networks which is a part of Deep Learning Deep Learning is a more complicated advanced topic of machine learning but it is easier with neural networks to do simple pattern recognitions using external Python Libraries like NumPy Pandas and Tensorflow As previously said machine learning is the computer learning pattern to do certain things So as an example following number sequence has a pattern try to recognize this pattern x y so the relationship is y x In our mind you might figure out that between and there is a difference of and between and there is difference so there might be multiple of x with and or   of some value So let s implement this in the Python programming language Waaaiiiit  Why Python Python is simple and consistent already have massive community support worldwide have tons of libraries and frameworks for machine learning and data science NumPy Pandas Matplotlib Seaborn for Data Analysis and Visualization TensorFlow Keras Scikit learn for Machine learning OpenCV Pillow for Computer vision NLTK spaCy for Natural language processing Let s dive into our first code First we import Keras API application programming interface from TensorFlow Here keras make it easy with its set of functions for neural networks In this line of code we implemented the simplest possible neurons Dense defines the connected neurons As there is only one layer of dense here there is only one layer on neurons in here And input shape of this layer is also the simplest form with one value import kerasmodel keras Sequential keras layers Dense units input shape But when it comes to machine learning we need to calculate using Linear algebra calculus and more advanced theories but in Tensorflow and Keras those complicated ones are already implemented but if you need to optimize and go deep you want Machine Learning Concepts with Advcanec Scientific mathematical Background Then we implement loss function and optimizer The loss function guesses the relation between x and y and gives the measured result data good or bad how much loss or close to the optimizer to make the next guess Optimizer decides the accuracy of the guess done by the loss function Optimizers are methods or approaches that adjust the properties of your neural network such as weights and learning rate to decrease losses The main logic is here to make each guess made by loss function to be better than one before model compile optimizer sgd loss mean squared error When gues are making some progress with gues becoming better and better the convergence is being used To study more about convergence visit this site Next we import the NumPy library to do calculations easily import numpy as npnext we implement two flat arrays to x and y values xs np array dtype float ys np array dtype float In the next cell we figure out how do these xs value fit in ys values by implementing model fit method for number of times epochs means the training loop will do times its guesses Training the modelmodel fit xs ys epochs And the output looks like thisEpoch    s ms step   loss Epoch    s us step   loss ……    s us step   loss e Epoch    s us step   loss e Epoch    s us step   loss e This is called training the model After running training loops you can see that loss is getting lower so next we do prediction of our custon number for X using predict method print model predict and the output should be close to but instead it showed This is happening because of insufficient training data if we Train the model with loops answer will look like this So with model training it becomes close to the real answer You can find the source code for this here Simple House Price Prediction using Neural Network Basics and TensorflowHere we are going to do a real life scenario to Build a Neural network using TensorFlow Here is the simple formula for the predictionHouse of Price with one bedroom kHouse of Price with one bedroom kAccordingly the price of the houses increases by the number of bedrooms Here we going to build a neural network to predict the prices of houses according to their bedrooms here is the two x and y data for thisx y And Let s start by importing essential libraries for thisimport tensorflow as tfimport numpy as npfrom tensorflow import kerasThen we implement whole methods as loss function optimization and defining number arrays defining training loops Here epochs inside a basic python function called house model and return model with empty arguments def house model xs np array dtype float ys np array dtype float model tf keras models Sequential tf keras layers Dense units input shape model compile optimizer sgd loss mean squared error model fit xs ys epochs return modelThen we assign the number of beds to value to new y and use predict method and execute the house model function new y model house model prediction model predict new y After training the data times the prediction will print as followsprint prediction You can find the source code from here If you want to continue your self study in Neural networks while parallel to Machine Learning You can follow the DeepLearning Coursera specialization by applying for financial Aid Visit CourseraSo I believe this guide would ve provided some basic introduction on how machine learning and artificial intelligence are applied through the neural network Thank you	2022-03-27 11:35:44
海外TECH	DEV Community	Simple Pub-Sub System using Redis and Python	https://dev.to/rohit20001221/simple-pub-sub-system-using-redis-and-python-25jh	Simple Pub Sub System using Redis and PythonHi guys i am here with an another blog post now let us build a simple publish subscribe system using python and redis Running the redis serveri am using docker to start a redis instance in my computer it s very easy to run a redis instance using docker and also it s very easy to remove redis instance and the fun part is redis running through docker would not affect our system running redis instancedocker run name demo redis p d redis alpineif you want to stop or remove redis instance running through above command you can do the followingdocker container stop demo redis lt stop the redis instancedocker container rm demo redis lt remove the redis container Creating the publisherimport redis initializing the redis instancer redis Redis host port decode responses True lt this will ensure that binary data is decoded while True message input Enter the message you want to send to soilders r publish army camp message let s think publisher as a commander in army and he wants to send message to the soilders so here the the topic that he wants to publish message is army camp this analogy is only for fun Creating the subscriberimport redisr redis Redis host port decode responses True pubsub method creates the pubsub object but why i named it mobile just kidding think of it as the waki taki that listens for incomming messagesmobile r pubsub use subscribe method to subscribe to topic on which you want to listen for messagesmobile subscribe army camp listen returns a generator over which you can iterate and listen for messages from publisherfor message in mobile listen print message lt you can literally do any thing with this message i am just printing it Here is a demo video of running the above code	2022-03-27 11:23:06
海外TECH	DEV Community	StrictionD	https://dev.to/striction_d/strictiond-5h5l	StrictionD	2022-03-27 11:18:52
海外TECH	DEV Community	The project you created with replit is taking a long time to respond. Is this just me?	https://dev.to/tsumuri1017/the-project-you-created-with-replit-is-taking-a-long-time-to-respond-is-this-just-me-4hd6	The project you created with replit is taking a long time to respond Is this just me The response time of the website publishedby replit is taking too long Is this a temporary issue Or is there a solution	2022-03-27 11:12:34
海外TECH	DEV Community	Being an Imposter	https://dev.to/debs_obrien/being-an-imposter-4bl7	Being an ImposterIf you ever look at the home page of my site or the intro slide of my talks you will probably think I am the biggest show off in the world I am and I tell everyone I am a GitHub Star a Microsoft Most Valuable Profession a Google Developer Expert a Media Developer Expert a Nuxt ambassador and an Auth Ambassador However really this is for my benefit to remind me that I am good enough because for some reason I seem to not see my own achievements and feel like I am not doing enough I am an imposter I doubt my abilities and find it difficult to accept my accomplishments and wonder if I deserve them Invincible at At years of age I was invincible I was in Mallorca working as a kids entertainer earning € a week Yes a week I had free accommodation and I was having fun so I didn t care My dream was to be a hollywood star and although I did get to star be an extra in scenes alongside Jared Leto I never actually made it as an actress So when I saw a TV series being filmed on the beach I went up to the producer and said I would love to be a runner someone who runs whatever tasks given to them for free and help And so I did I loved it And when it finished I asked the producer how can I work in TV He gave me his business card and said come to London and I will give you work experience in the London Weekend TV Studios And so at with no money and no job I moved to London I got a job in a bar to pay the rent and then worked for free in the TV studios learning as much as I could I then walked from door to door handing my CV to as many companies as possible My CV now had London Weekend TV Studios on it I am not exaggerating when I tell you I handed at least CVs out But all I needed was one yes and eventually I got it Working in the TV StudiosI had the most amazing job in the world and I got up every morning excited to go to work Some of my tasks were simply asking producers and directors what they wanted for lunch and going to restaurants to collect it or making them tea or coffee I was a runner but we all have to start somewhere But I was ambitious and I got promoted I got to work in post production Some of my tasks were watching Britney Spears MTV videos to make sure there were no digital flaws before it got released on TV or working the rack to record copies of a movie to be sent to a airlines and my favourite of all was the Cannes Advertising Awards where I got to create one recording from the many video tapes and add manually record a few seconds of black between each add as well as record the name of the add and the country This is how we did things before the digital world existed I had an amazing year living in London earning £ a year working hours a week and on top of that training and flying to Scotland to get my black belt in Taekwondo Back then to grade for black belt the entry requirement was to break a brick before the day grading began Crazy to think that I flew on a plane with a brick in my hand so that I could break it and get a black belt However I was struggling to survive financially and I was doing too much and I knew I couldn t keep it up Making it as an editor in post production was no easy task and I could not survive another year of working so many hours And so I left London and the TV world behind But I don t consider it a failure I consider it as the best year of my life I achieved so much I was amazing Seeing failure rather than SuccessNow years later and I have achieved so much in tech and yet for some reason I look at the failures more than success What on earth happened Sometimes I put it down to life experiences Things that didn t work out for me made then made me less invincible Who knows I had been let go of many companies I had failed to get a job that lasted more than a year I really believed that I was bad luck and that any start up that hired me was going to be a failure because of me My CV was full of companies that did not exist anymore No trace of them Was I just making it up Sure looked that way to potential employers My freelance work started with knocking on restaurant doors asking for work to create their website their menus whatever And I created some amazing sites in Flash a technology that now no longer exists can t put that on the CV At the point of giving upI was at the point of just giving up in tech And so I signed up with a University to get a degree online studying Spanish language so I could work in the Spanish schools as a real teacher rather than giving classes on Sunday mornings and working in language schools for € a month The uni degree actually taught me a lot It was during this degree that I learnt how to prepare and give presentations among other things I had never been to Uni before But during my first year I knew that this wasn t the path I wanted to go down and I wasn t happy in life in general Everything was going wrong and I felt like I was just in a big deep dark hole Give Tech one more chanceExactly years ago today I decided to give tech one more go I had plan B to be a teacher already in motion so now it was time to aim for plan A I gave up my job in the language school and used up all my savings to pay for my online Uni fees my online frontend tech degree and my online fullstack tech degree I studied and struggled to pay the bills for about months I had no idea if it would be worth it If I would get a job or be successful I just knew I had to give it one more go before I threw in the towel It was hard Learning JavaScript was hard is hard I had failed at it many times before and had convinced myself that I was not good enough to be a real programmer But I really wanted to make it As much as it was hard I really enjoyed it I was studying hours a day even while running on the running machine at the gym I needed to succeed I didn t want to go back to the life I had I didn t want to struggle anymore and have to work weekends to pay the bills I wanted to love my job and be challenged each day and coding gave me that If only I could learn JavaScript Both tech degrees I did were extremely challenging and come with real life projects I was building things constantly I was pair programming with others to solve problems together And I had a mentor who not just went over my code and showed me how I could improve it but was there for me to remind me of how well I was doing and that I was good enough that it isn t easy but that I can do it and I was going to learn JavaScript The No s are always hardI got many no s from interviews including one where I just wanted the ground to swallow me up I panicked The process was horrible and I was just terrified and my brain didn t work that day at all I couldn t even use the mouse and when they asked me to go to the white board to do a coding challenge I just refused Obviously I did not get that job But I walked out of there and said I am never going to be in that position again where I am given code that I have not seen before and panic And so I started peer reviewing other peoples code At least one peer review a day and became the student with the most peer reviews ever I got the jobThen in late October I got a job I had to do a coding challenge and I found the challenge pretty easy I had done very similar stuff in my tech degree so basically I was prepared I was ready And they were super impressed with how fast and well I did the challenge and how clean my code was And so I got my job as a real frontend programmer I was in shock I called my husband and said I think I just got a job Afraid I was going to get sackedAnd that is where the imposter syndrome began I went to work every day hoping not to get sacked I didn t know everything People kept asking me for help with JavaScript stuff This was my first JavaScript job I was freaking out I got moved into the architectural part of the company and tasked with solving frontend scaling problems which ended up with us creating a custom framework design system and component library At one point I sent a message to my boss asking him to please give me a warning before he sacked me so I could work harder and try to improve cause I really loved my job and didn t want to lose it My boss was amazing He told me why on earth would we even consider sacking you You are incredible he said and everyone is so impressed with you And then he sent me some articles on imposter syndrome and every now and again he would send me interviews or short videos to help me overcome it and to show me I was not alone Feeling the ImposterYou would think that it just goes away but it doesn t When I got awarded Google Developer Expert I really thought that they had made a mistake I was waiting for the email to say it was a mistake Seriously I was no expert That s a big word that carries a lot of weight I now mentor for the Google Developer Expert program and remind other women that the word expert does not mean you have to be an expert in everything You are an expert in one area perhaps it s CSS animations perhaps it s performance but not everything None of us are experts in everything I then got my MVP Award and again I thought wow is this for real I had been referred by others for both of these award programs and in the space of a a few months I was a GDE and an MVP and it was just insane I never thought to look back on all the work I had been doing in the community All the posts I had written talks I had given projects I had created that were open source mentoring I was doing for both programs I had graduated from All I saw was what I had not yet learnt and there was so much When I got my GitHub star I was in shock People had voted for me They thought I was a star They knew I existed Wow Now I was freaking out even more I am not a star I know way less than anyone else Everyone else is way more clever than me They are going to soon find out and kick me out of the program I am sure of it Overcoming Imposter SyndromeThe best way to get over imposter syndrome is to talk about it And so I did But the feelings are had to control When it came to the GitHub Nova conference I reached out and said I really want to give a talk but I am terrified of giving a talk in front of so many GitHub stars To me they were the stars I was the imposter But I got reminded of all the work I had done for the community how skilled I am and why I was in the program and that yes I was a star I have all my awards behind me in my office They are my reminder that I got this I am amazing Sometimes I need more reminders I wear my GitHub stars t shirt way too often It s my favourite In the entrance of my apartment I have two walls full of signs that remind me I am awesome to not give up to keep dreaming to do more of what makes me happy and to believe in myself Sometimes before an interview or a talk I literally read through them all some of them twice and then I say come on Debbie you can do this And the best thing I ever did was program Alexa to tell me I am amazing She never fails Comparing yourself to othersAs we get more successful in tech we become even more imposters If I compare myself to my family I am an expert a star everything If I compare myself to my tech idols I am no where near an expert But this is such an unfair comparison It is like comparing a Taekwondo black belt to a white belt The black belt is the expert here But anyone who does martial arts will know that once you get your black belt you then start comparing yourself to the nd degrees rd degrees masters and all of a sudden you start to feel almost like a white belt again This is the great thing about martial arts and the great thing about tech There is so much to learn that you will never know it all never perfect it all You can t get your black belt just by training for a year no matter how good you are at your kicks for example It takes time A lot of hard work and time To go from rd degree to th degree I had to wait years I had to train hard study practice and then grade My grading was hours long I flew to London to grade with one of the Grand Masters a th degree and one of the best in the world He told us that we would go through everything from patterns to breaking with flying kicks sparring theory etc and that he was going to push us so hard that we will want to give up That he said is when the grading really begins And he was not joking The last half hour after almost hours of grading we had sparring and not just on but against The goal here was not to win not to show off your amazing spinning kicks it was to show that you could continue when your body wanted to give up It was to show that if you put your mind to it you really can achieve anything And I did I got my th degree years ago But more importantly was the lesson I learnt that day Never give up no matter how hard it gets You really can do anything if you put your mind to it And if you fail it doesn t mean you are a failure it just means you lack preparation It means work on your weak areas improve and then try again The Journey takes timeWhen it comes to tech it s the same It s a journey and it takes time It takes time to learn it takes time to master and it takes time to get to the next stage whatever that stage might be And above all it takes a lot of hard work and determination But just like anyone can get a black belt in Taekwondo if they work hard enough anyone can learn to code and get a job in tech if they work hard enough And remember the majority of us in tech suffer from imposter syndrome so you are not alone The best advice I can give you is to talk about it Be open and honest with others about it especially your boss or colleagues at work My DM s are always open if you ever need someone to talk to You got this	2022-03-27 11:09:28
海外TECH	DEV Community	Understanding password storage	https://dev.to/_mohanmurali/understanding-password-storage-195e	Understanding password storageStoring passwords can be a challenging and painful task With this post I hope to highlight some of the challenges Keep in mind that managing password by yourself is never a good idea and it s always best to hand it over to a security expert by making use of one of the several auth providers out there Storing Passwords in plain textSo what s the deal with storing the passwords Can t they just be stored as it is like other things in DB Well we can but we should not do that due to the following reasonsAnyone who has access to the database can then easily see and use the password Sure they might not do it but nothing is stopping them from not doing it If your table is compromised by someway by a hacker they can easily get access to the login details of your user They just have to get access to the one table in the database This might cause serious data breach and even legal problems Now we know that we should not store passwords as plain text Lets look at some of the way data can be stored safely Encryption Vs HashingEncryption is a mathematical algorithm that converts some text to something completely different by using an encryption key Anyone who has access to the key can decrypt the encrypted data If the encryption key is compromised the passwords are likely compromised as well Since we can find out the original password using an encryption key it is not safe to use encryption for storing passwords Hashing is another kind of cryptographic mathematical function that converts a string into a completely random combination of characters of a fixed length Unlike encryption it is not possible to find the original string easily once hashed Due to this reason hashing is the preferred way of storing passwords Some common hashing algorithms are MD SHA and SHA family algorithms Hashing works well for storing the password for the below reasonIt is impossible to know the length of the original password by looking into the hashed password It is close to impossible to reverse the hash Even a small change in input will produce a dramatically different hash input passwordhash edadefdcddaabbddaefddinput Passwordhash ecfeffcafcfeaebeebbdeca Just by changing p to caps produces totally different hashSo if we don t know the original password how will we validate if the password entered by the user is correct We will validate it by hashing the password entered by the user and comparing it with the stored hash in the table We will get the same hash for the same input Hence if the hashed password matches that means the user has entered the right password This is also the reason why it is not possible to retrieve your password once you have lost it but still you can validate it with previously stored hashed passwords by comparing the hashed values So now even if your database is compromised all the attacker will see is a collection of hashed passwords Great that means our client s data is safe right Well hashing protects data to an extent but it s not completely safe Let s put on our hacker s cap and try to see what we can do with the hashed password list Limitations of HashingNow we have a list of hashed passwords You go through the list and find that there are a few identical hashes That probably means that the password is a commonly used word As a hacker you can then just use the commonly used passwords as input and see if you can crack it Most probably you would That s the reason it s always advised to use a complicated password But not all users are going to use it And if you lose the user s data it s going to be your responsibility There is also a list of commonly used passwords and there hashes available that get updated with every data breach These are called the rainbow table which the hackers can use to figure out the password So how can we overcome it Seasoning with SaltAs storing the password with hashing alone might not be enough we have to combine the password with a randomly generated string which we call as the salt and then hash them together Since we generate the salt randomly we will get different hash even from the same passwords So hashing makes it much more secure to save the password The salt is then stored usually in a different database input passwordunsalted hash edadefdcddaabbddaefddsalted input passwordm f F cZal salted hash decdcfebdbafcbeffecbaebbacbeinput passwordunsalted hash edadefdcddaabbddaefddsalted input passwordtJgeu nJSgvfsalted hash acddcaaedbbdebbdbcccdbcbcfbcdAs you can see with salt even for the same input we generate completely different hashes This makes salting passwords much better even for not so strong passwords To validate the user input we will have to get the salt stored for that user add the given password with the salt and hash it and see if it matches the hash stored in the database Spicing with pepperIt is not unheard of that even the database containing the salt of the user is compromised If you want to secure our passwords further we have to use a random string that we add to all passwords along with the password and salt This random string is called pepper and it s usually stored right inside the source code Just make sure you don t push this into a publicly hosted repository Using pepper might not be necessary all the time And it might cause an issue if you compromise the value in the pepper cause you have hashed all the passwords with this single value and it is not easy to change So keep that in mind	2022-03-27 11:02:04
Apple	AppleInsider - Frontpage News	Mac Studio deals are here: save $200 to $400 on retail configurations	https://appleinsider.com/articles/22/03/16/mac-studio-deals-have-arrived-save-200-to-400-on-retail-configurations?utm_medium=rss	Mac Studio deals are here save to on retail configurationsAggressive Mac Studio discounts are going on now at Simply Mac with the Apple Premier Partner slashing retail M Max and M Ultra models by as much as Save up to instantly on Apple s new Mac Studio desktopDespite being announced only a week ago Simply Mac is knocking to off retail Mac Studio configurations Read more	2022-03-27 11:42:29
海外ニュース	Japan Times latest articles	Eagles use reinstated extra innings to beat Marines	https://www.japantimes.co.jp/sports/2022/03/27/baseball/japanese-baseball/eagles-marines-extra-innings/	Eagles use reinstated extra innings to beat MarinesThe Eagles overcame strikeouts from fire balling Lotte right hander Roki Sasaki who threw the fastest pitch of his pro career but also allowed three runs	2022-03-27 20:02:27
ニュース	BBC News - Home	Simon Coveney: Man and woman arrested over Coveney security alert	https://www.bbc.co.uk/news/uk-northern-ireland-60891571?at_medium=RSS&at_campaign=KARANGA	belfast	2022-03-27 11:11:46
サブカルネタ	ラーブロ	旭川ラーメン アリーナ食堂 (大雪アリーナ) 醤油篇	http://ra-blog.net/modules/rssc/single_feed.php?fid=197629	旭川ラーメン	2022-03-27 12:22:24
北海道	北海道新聞	小林陵侑がＷ杯個人総合を制覇　ジャンプ、３季ぶり２度目	https://www.hokkaido-np.co.jp/article/661850/	個人総合	2022-03-27 20:10:24
北海道	北海道新聞	旭川中２死亡　第三者委が６項目で、いじめ認定	https://www.hokkaido-np.co.jp/article/661852/	旭川市内	2022-03-27 20:06:41
北海道	北海道新聞	春場所、若隆景が３度目の技能賞　高安、琴ノ若が敢闘賞	https://www.hokkaido-np.co.jp/article/661853/	大相撲春場所	2022-03-27 20:04:00