投稿時間:2022-12-30 19:14:27 RSSフィード2022-12-30 19:00 分まとめ(16件)

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IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 日本障がい者サッカー連盟、パートナー企業との連携会議を発足　地域で成功事例を共有	https://www.itmedia.co.jp/business/articles/2212/30/news035.html	itmedia	2022-12-30 18:10:00
python	Pythonタグが付けられた新着投稿 - Qiita	python UnicodeDecodeError: 'ascii' codec can't decode byte xxxx in position 123: ordinal not in range(128)	https://qiita.com/aizwellenstan/items/6361091d857b4afaea8c	stdout	2022-12-30 18:58:31
python	Pythonタグが付けられた新着投稿 - Qiita	[Python]サーバーレスアプリ開発入門でハマったModuleNotFoundError	https://qiita.com/otamaninja/items/a628b69e557fa70b0795	modulenotfounderror	2022-12-30 18:37:39
Git	Gitタグが付けられた新着投稿 - Qiita	GitLab 修正、プッシュ、マージリクエストの流れ	https://qiita.com/kousueke/items/6975a4b5705ddb84134c	gitclone	2022-12-30 18:58:51
技術ブログ	Developers.IO	リソースベースポリシーの Principal に存在しないプリンシパルを指定すると Invalid principal in policy などのエラーが発生する	https://dev.classmethod.jp/articles/resource-base-policy-invalid-principal-error/	invalidprincipalinpolicy	2022-12-30 09:04:34
海外TECH	DEV Community	CI/CD pipelines with AWS Amplify	https://dev.to/this-is-learning/cicd-pipelines-with-aws-amplify-5a1b	CI CD pipelines with AWS AmplifyThe company I work for is an AWS partner and it is natural that many of the applications we build are based on the services offered by Amazon We re migrating our CI CD pipelines to AWS Amplify and I wanted to show you how we can achieve great results with just a few clicks The example is based on a Next js application hosted on GitHub To initialize the application we can use the command npx create next app latest typescriptOnce the starter is created we edit the filepages index tsxreplacing the boilerplate with this code An environment variable is used here We have to configure it in the Next js configuration filenext config jsconst nextConfig env PROJECT NAME process env PROJECT NAME module exports nextConfigWe can test the app locally by creating a env local file to set the environment variableAfter we sync the project with remote GitHub we re ready to move on to the deployment part AWS AmplifyOnce logged into the AWS console let s search for the Amplify service ConfigurationClick on Host web apphere we can connect our GitHub account and select the project we just createdClick on Next here we can configure the build and we can set our environment variable Build amp DeployThe build and the deployment will be performed automatically Final resultThis is the first article on AWS Amplify if you find the topic interesting give ️and I will write more about it Bye You can follow me on Twitter where I m posting or retweeting interesting articles Giorgio BoaFollow Giorgio Boa is a full stack developer and the front end ecosystem is his passion He is also international public speaker active in open source ecosystem he loves learn and studies new things	2022-12-30 09:54:59
海外TECH	DEV Community	Laptop Keyboard with awesome click effects.	https://dev.to/amiruweerathunga/laptop-keyboard-with-awesome-click-effects-40o2	awesome	2022-12-30 09:25:51
海外TECH	DEV Community	Divide and Conquer: A powerful strategy for solving problems	https://dev.to/anurag629/divide-and-conquer-a-powerful-strategy-for-solving-problems-e45	Divide and Conquer A powerful strategy for solving problemsDivide and conquer is a general algorithmic strategy that involves dividing a problem into smaller subproblems solving the subproblems and then combining the solutions to the subproblems to solve the original problem This strategy is often used to solve problems that are too large or complex to be solved directly One of the key benefits of divide and conquer is that it can lead to highly efficient algorithms as it allows you to take advantage of the fact that smaller problems are often easier to solve than larger ones By breaking a problem down into smaller pieces you can often solve it more quickly than you could by attempting to solve it all at once Divide and conquer algorithms are often implemented using recursive functions which divide the problem into smaller subproblems and then call themselves with the subproblems as arguments This allows the algorithm to keep dividing the problem until it reaches a small enough size that it can be solved directly Some common examples of divide and conquer algorithms include Merge sort A sorting algorithm that divides an array into smaller subarrays sorts the subarrays and then merges them back together to form a sorted array Quick sort Another sorting algorithm that uses divide and conquer to sort an array by selecting a pivot element and partitioning the array around it Binary search An algorithm that searches for a specific element in a sorted array by dividing the array in half and searching only in the half that is likely to contain the element Karatsuba multiplication An algorithm for multiplying large numbers that divides the numbers into smaller pieces and then uses recursive calls to multiply the pieces and combine the results Here is an example of a problem that can be solved using divide and conquer Suppose you are given an array of integers and you want to find the maximum sum of any contiguous subarray of the array One way to solve this problem is to use a divide and conquer approach The first step is to divide the array into two smaller subarrays You can do this by finding the midpoint of the array and splitting it into two halves Next you can solve the problem for each of the two subarrays by finding the maximum sum of a contiguous subarray in each of them To do this you can use the same divide and conquer approach dividing each subarray into smaller subarrays and continuing until you reach a subarray of size Finally you can combine the solutions to the subproblems to solve the original problem In this case you can do this by considering three different cases The maximum sum of a contiguous subarray includes the element at the midpoint of the array In this case you need to find the maximum sum of a contiguous subarray that includes both the element at the midpoint and some elements from one of the two subarrays The maximum sum of a contiguous subarray lies entirely within one of the two subarrays In this case the solution is simply the maximum sum of a contiguous subarray that you found for that subarray The maximum sum of a contiguous subarray lies entirely within the other subarray In this case the solution is simply the maximum sum of a contiguous subarray that you found for the other subarray By combining the solutions to the subproblems in this way you can find the maximum sum of a contiguous subarray for the entire array Here is a Python function that uses divide and conquer to find the maximum sum of a contiguous subarray of an array def maximum subarray sum arr start end base case if the array has only one element the maximum sum is the element itself if start end return arr start divide the array into two subarrays mid start end find the maximum sum of a contiguous subarray in the left subarray left sum maximum subarray sum arr start mid find the maximum sum of a contiguous subarray in the right subarray right sum maximum subarray sum arr mid end find the maximum sum of a contiguous subarray that includes the element at the midpoint of the array cross sum find maximum crossing subarray arr start mid end return the maximum of the three sums return max left sum right sum cross sum def find maximum crossing subarray arr start mid end find the maximum sum of a contiguous subarray that includes the element at the midpoint of the array and some elements from the left subarray left sum float inf current sum for i in range mid start current sum arr i left sum max left sum current sum find the maximum sum of a contiguous subarray that includes the element at the midpoint of the array and some elements from the right subarray right sum float inf current sum for i in range mid end current sum arr i right sum max right sum current sum return the sum of the two subarrays return left sum right sumTo use this function you can simply call maximum subarray sum arr len arr where arr is the array of integers that you want to find the maximum sum of a contiguous subarray for The function will return the maximum sum of a contiguous subarray of the array Below is the explanation of the above code maximum subarray sum arr start end is a recursive function that uses divide and conquer to find the maximum sum of a contiguous subarray of the array arr from index start to index end The function works as follows If the array has only one element i e start and end are both equal to the same index the maximum sum is the element itself so the function returns the element If the array has more than one element the function divides the array into two subarrays by finding the midpoint mid of the array and setting mid to be the end of the left subarray and the start of the right subarray The function then calls itself with the left subarray as its argument and assigns the result to left sum This will find the maximum sum of a contiguous subarray in the left subarray The function then calls itself with the right subarray as its argument and assigns the result to right sum This will find the maximum sum of a contiguous subarray in the right subarray The function then calls the helper function find maximum crossing subarray arr start mid end to find the maximum sum of a contiguous subarray that includes the element at the midpoint of the array and some elements from both the left and right subarrays This value is assigned to cross sum Finally the function returns the maximum of the three sums left sum right sum and cross sum which will be the maximum sum of a contiguous subarray of the entire array find maximum crossing subarray arr start mid end is a helper function that finds the maximum sum of a contiguous subarray of the array arr from index start to index end that includes the element at index mid which is the midpoint of the array The function works as follows The function initializes the variable left sum to be the smallest possible value and the variable current sum to be It then iterates over the elements of the left subarray from index mid down to index start and adds each element to current sum It then updates left sum to be the maximum of left sum and current sum This will find the maximum sum of a contiguous subarray that includes the element at the midpoint of the array and some elements from the left subarray The function initializes the variable right sum to be the smallest possible value and the variable current sum to be It then iterates over the elements of the right subarray from index mid up to index end and adds each element to current sum It then updates right sum to be the maximum of right sum and current sum This will find the maximum sum of a contiguous subarray that includes the element at the midpoint of the array and some elements from the right subarray Finally the function returns the sum of left sum and right sum which will be the maximum sum of a contiguous subarray that includes the element at the midpoint of the array and some elements from both the left and right subarrays This value can be used by the maximum subarray sum function to find the maximum sum of a contiguous subarray of the entire array There are some common patterns of problems that are often solved using divide and conquer Some examples include Searching and sorting As mentioned earlier algorithms such as merge sort and binary search use divide and conquer to efficiently search for and sort elements Optimization problems Many optimization problems can be solved using divide and conquer as the strategy allows you to break the problem down into smaller subproblems and find the optimal solution for each subproblem Examples include finding the maximum sum of a contiguous subarray as mentioned earlier and finding the shortest path between two points in a graph Problems with overlapping subproblems Some problems involve computing the same subproblems multiple times which can be inefficient Divide and conquer algorithms can be used to store the results of each subproblem and reuse them when needed which can improve the efficiency of the algorithm Examples include the Fibonacci sequence and the shortest path between two points in a graph Problems with a recursive structure Some problems have a recursive structure that can be exploited using divide and conquer For example the problem of computing the nth term of the Fibonacci sequence can be solved using recursive calls to compute the previous two terms I hope this helps Let me know if you have any other questions about divide and conquer algorithms	2022-12-30 09:10:34
海外TECH	DEV Community	Vite or Webpack	https://dev.to/hshoja/vite-or-webpack-afd	Vite or Webpack WebpackIs a popular build tool for modern JavaScript applications that is designed to bundle and optimize static assets such as JavaScript CSS and images It has a wide range of features and is highly configurable which makes it a good choice for a variety of projects ViteAs an alternative on the other hand is a newer build tool that is designed to be fast and lightweight It uses native ES module imports to speed up development builds and it has a focus on simplicity and ease of use Vite or Webpack Vite is often a faster and more lightweight alternativeIt has a smaller feature set and is not as configurable as Webpack Webpack is a powerful and configurable build tool that is suitable for a wide range of projects Faster in what Vite is primarily designed to be fast in development builds and can be a significant advantage during development as it allows you to make changes to your code and see the results almost instantly In production the speed of the build tool is usually less of a concern as the build process is typically only run once before deploying the application In this case the main advantage of Vite is its simplicity and ease of use as it can be easier to set up and maintain than more complex build tools like Webpack Under the hoodAre you curios how they work differently under the hood let s watch these two videos SummaryOverall Vite is designed to be fast in development builds and easy to use in both development and production However it may not be the best choice for all projects as it has a smaller feature set and is less configurable than some other build tools Any thoughts All the bestHash	2022-12-30 09:08:29
ニュース	BBC News - Home	The high street shops thriving after a tough year	https://www.bbc.co.uk/news/business-63949370?at_medium=RSS&at_campaign=KARANGA	tough	2022-12-30 09:20:36
北海道	北海道新聞	暴力団に「みかじめ料」今なお　滝川で２０店発覚、道警は潜在化懸念	https://www.hokkaido-np.co.jp/article/782390/	暴力団員	2022-12-30 18:38:00
北海道	北海道新聞	東京円、１３２円台前半	https://www.hokkaido-np.co.jp/article/782389/	東京外国為替市場	2022-12-30 18:34:00
北海道	北海道新聞	中国、北朝鮮に党大会説明　コロナで首脳外交できず	https://www.hokkaido-np.co.jp/article/782388/	中国共産党	2022-12-30 18:33:00
北海道	北海道新聞	メッシ「安らかにお眠りください」　世界中の選手ら、ペレさんを追悼	https://www.hokkaido-np.co.jp/article/782387/	金字塔	2022-12-30 18:29:00
北海道	北海道新聞	ウマ娘カード、日高の飲食店でもらおう　ファン呼び込みへ町が初コラボ	https://www.hokkaido-np.co.jp/article/782377/	人気ゲーム	2022-12-30 18:30:08
北海道	北海道新聞	女子ゴルフ山下選手ら締めくくりの鐘　大阪取引所で大納会	https://www.hokkaido-np.co.jp/article/782380/	大阪取引所	2022-12-30 18:12:26