{"text": "What's new in the Microsoft FluentUI library for Blazor versions 1.3 and 1.4\nIn this post I'll give you an overview of what's new and changed in versions 1.3 and 1.4 of the Microsoft Fluent UI for Blazor library. Me and the team were so busy with adding exciting new features that I didn't have time to blog about them earlier. I'll describe the features both from an end-user as from a code perspective.\nIn short, the two big end-user additions (besides some bug fixes) are:\n- Fluent UI System Icons support\n- Design Token support\nAnd the repository and code changes:\n- Add missing xml comments\n- Add\nFocusAsyncmethods to\nFluent UI System Icons support\nThe Fluent UI System Icons are a (still growing) collection of familiar, friendly and modern icons from Microsoft. At the moment there are more than 2020 distinct icons available in both filled and outlined versions and in various sizes. In total the collections consists of well over 11k icons in SVG format. All of them have been added to the library in an easy to use way by addition of the\n component. Just putting this in your .razor page:\n\nWill give you this:\nCouple of things to unwrap here on the parameters used:\nNameis a string. To make it easier to select an icon, all names have been added as constants. IntelliSense will help you find the right one. It is also using the new .NET 6\nEditorRequiredfeature. If you don't pass a value for the\nName, Visual Studio will point that out to you in design time and raise a compile error when building.\nSizeis using an\nenumthat holds all the possible valid sizes. Note the not all sizes are available for all icons. If you get an error at run-time, supply a different size or remove the parameter to fall back to the default size (\nFilledis a bool to choose a filled (true) or a regular/outlined (false) version of an icon\nOther parameters (not shown in the example above) for this component are:\nUseAccentColor (bool). This parameter defaults to\ntrueand determines if the accent color is used for the fill or the outline when rendering the icon. When setting this to false, the icon will be rendered in black.\nNeutralCultureName (string). Some icons offer alternative versions for specific languages. By supplying the two letter neutral language code, you can indicate that you would like to use that specific version of an icon. If there is no language specific version, the component will fall back to rendering the original version. Example:\nNeutral @FluentIcons.TextBold iconsFilled:Regular:French @FluentIcons.TextBold icons (\nSlot (string). With the slot parameter you can indicate where an icon needs to be rendered in the context of another component. For example when combining a with a , you can use the slot to put the icon in font of the button text:\nSearch(note that the icon component is inserted after the button text) . This will render:\nThe temporary demo site has a page to search through all the available icons and sizes.\nIn earlier and other libraries you will often find icons being included by means of fonts. This comes with the disadvantage that the whole font needs to be downloaded even if you are only using 1 icon. I therefore stepped away from using that method in this library and opted for taking the SVG route. Because the icons are SVG files that are stored in the\nwwwroot folder in a RCL (Razor Class Library), they are being treated like ordinary static files on the server. They don’t get downloaded until requested and only the icons you are actually using will be downloaded. Sounds like a win-win to me!\nDesign Token support\nThe Fluent UI Web Components are built on FAST's Adaptive UI technology, which enables design customization and personalization, while automatically maintaining accessibility. This is accomplished through setting various \"Design Tokens\". In previous versions of this library, the only way to manipulate the design tokens was through using the\n component. This Blazor component (and it's underlying Web Component) exposed a little over 60 variables that could be used to change things like typography, color, sizes, UI spacing, etc. FAST has been extended a while ago and now has a much more granular way of working with individual design tokens instead of just through a design system provider model. See https://docs.microsoft.com/en-us/fluent-ui/web-components/design-system/design-tokens for more information on how Design Tokens work.\nIn total there are now over 160 distinct tokens defined in the Adaptive UI model and as of version 1.4 of this library you can use all these in Blazor as well! The implementation has been in the works for multiple months but I think the end result is quite flexible. It allows for usage both from code as in a declarative way in your .razor pages. The two ways of working with design tokens are described below (taken from the repository readme):\nOption 1: Using Design Tokens from C# code\nGiven the following .razor page fragment:\nA button Another button And one more Last button\nYou can use Design Tokens to manipulate the styles from C# code as follows:\n[Inject] private BaseLayerLuminance BaseLayerLuminance { get; set; } = default!; [Inject] private AccentBaseColor AccentBaseColor { get; set; } = default!; [Inject] private BodyFont BodyFont { get; set; } = default!; [Inject] private StrokeWidth StrokeWidth { get; set; } = default!; [Inject] private ControlCornerRadius ControlCornerRadius { get; set; } = default!; private FluentButton? ref1; private FluentButton? ref2; private FluentButton? ref3; private FluentButton? ref4; protected override async Task OnAfterRenderAsync(bool firstRender) { if (firstRender) { //Set to dark mode await BaseLayerLuminance.SetValueFor(ref1!.Element, (float)0.15); //Set to Excel color await AccentBaseColor.SetValueFor(ref2!.Element, \"#185ABD\".ToSwatch()); //Set the font await BodyFont.SetValueFor(ref3!.Element, \"Comic Sans MS\"); //Set 'border' width for ref4 await StrokeWidth.SetValueFor(ref4!.Element, 7); //And change conrner radius as well await ControlCornerRadius.SetValueFor(ref4!.Element, 15); StateHasChanged(); } } public async Task OnClick() { //Remove the wide border await StrokeWidth.DeleteValueFor(ref4!.Element); }\nAs can be seen in the code above (with the ref4.Element), it is posible to apply multiple tokens to the same component.\nFor Design Tokens that work with a color value, you must call the ToSwatch() extension method on a string value or use one of the Swatch constructors. This makes sure the color is using a format that Design Tokens can handle. A Swatch has a lot of commonality with the System.Drawing.Color struct. Instead of the values of the components being between 0 and 255, in a Swatch they are expressed as a value between 0 and 1.\nThe Design Tokens are manipulated through JavaScript interop working with an ElementReference. There is no JavaScript element until after the component is rendered. This means you can only work with the Design Tokens from code after the component has been rendered in OnAfterRenderAsync and not in any earlier lifecycle methods.\nOption 2: Using Design Tokens as components\nThe Design Tokens can also be used as components in a .razor page directely. It looks like this:\n
Dark Accent Stealth Outline Lightweight
\nTo make this work, a link needs to be created between the Design Token component and its child components. This is done with the BackReference=\"@context\" construct.\nOnly one Design Token component at a time can be used this way. If you need to set more tokens, use the code approach as described in Option 1 above.\nBesides these two new options, the original\n component is still there and can be used as always. There are no plans to remove this anytime soon.\nXML Comments\nAll components and all component parameters now have xml comments. This means that tools who support this, like Visual Studio IntelliSense, will show you information about methods and parameters when editing your razor pages and code, making it a bit easier to discover and understand functionallity:\nFocusAsync to FluentInputBase\nIt was not possible before to programmatically set focus to an\n derived component like the\n or\n. The base class\n has now been extended to expose this method.", "meta": {"lang": "en", "lang_score": 0.8278772234916687, "url": "http://baaijte.net/blog/microsoft-fast-components-fluentui-1.4/", "timestamp": "2023-01-26T21:28:43Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.013624321937681342], [3, 0.005676800807367226], [4, 0.006307556452630251]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.01006550163121823], [6, 0.006917204437133578], [7, 0.004486008356999439], [8, 0.0022173651366847224], [9, 0.0], [10, 0.0]], "fraction_of_words_corrected_in_lines": 0.004379562043795621, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0625, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 1364, "mean_word_length": 5.81158357771261, "num_of_sentences": 68, "symbol_to_word_ratio": 0.0021994134897360706, "fraction_of_words_with_alpha_character": 0.9648093841642229, "num_of_stop_words": 187, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "We firmly believe that the internet should be available and accessible to anyone, and are committed to providing a website that is accessible to the widest possible audience, regardless of circumstance and ability.\nTo fulfill this, we aim to adhere as strictly as possible to the World Wide Web Consortium’s (W3C) Web Content Accessibility Guidelines 2.1 (WCAG 2.1) at the AA level. These guidelines explain how to make web content accessible to people with a wide array of disabilities. Complying with those guidelines helps us ensure that the website is accessible to all people: blind people, people with motor impairments, visual impairment, cognitive disabilities, and more.\nThis website utilizes various technologies that are meant to make it as accessible as possible at all times. We utilize an accessibility interface that allows persons with specific disabilities to adjust the website’s UI (user interface) and design it to their personal needs.\nAdditionally, the website utilizes an AI-based application that runs in the background and optimizes its accessibility level constantly. This application remediates the website’s HTML, adapts Its functionality and behavior for screen-readers used by the blind users, and for keyboard functions used by individuals with motor impairments.\nIf you’ve found a malfunction or have ideas for improvement, we’ll be happy to hear from you. You can reach out to the website’s operators by using the following email info@atasteofky.com\nOur website implements the ARIA attributes (Accessible Rich Internet Applications) technique, alongside various different behavioral changes, to ensure blind users visiting with screen-readers are able to read, comprehend, and enjoy the website’s functions. As soon as a user with a screen-reader enters your site, they immediately receive a prompt to enter the Screen-Reader Profile so they can browse and operate your site effectively. Here’s how our website covers some of the most important screen-reader requirements, alongside console screenshots of code examples:\nScreen-reader optimization: we run a background process that learns the website’s components from top to bottom, to ensure ongoing compliance even when updating the website. In this process, we provide screen-readers with meaningful data using the ARIA set of attributes. For example, we provide accurate form labels; descriptions for actionable icons (social media icons, search icons, cart icons, etc.); validation guidance for form inputs; element roles such as buttons, menus, modal dialogues (popups), and others. Additionally, the background process scans all of the website’s images and provides an accurate and meaningful image-object-recognition-based description as an ALT (alternate text) tag for images that are not described. It will also extract texts that are embedded within the image, using an OCR (optical character recognition) technology. To turn on screen-reader adjustments at any time, users need only to press the Alt+1 keyboard combination. Screen-reader users also get automatic announcements to turn the Screen-reader mode on as soon as they enter the website.\nThese adjustments are compatible with all popular screen readers, including JAWS and NVDA.\nKeyboard navigation optimization: The background process also adjusts the website’s HTML, and adds various behaviors using JavaScript code to make the website operable by the keyboard. This includes the ability to navigate the website using the Tab and Shift+Tab keys, operate dropdowns with the arrow keys, close them with Esc, trigger buttons and links using the Enter key, navigate between radio and checkbox elements using the arrow keys, and fill them in with the Spacebar or Enter key.Additionally, keyboard users will find quick-navigation and content-skip menus, available at any time by clicking Alt+1, or as the first elements of the site while navigating with the keyboard. The background process also handles triggered popups by moving the keyboard focus towards them as soon as they appear, and not allow the focus drift outside of it.\nUsers can also use shortcuts such as “M” (menus), “H” (headings), “F” (forms), “B” (buttons), and “G” (graphics) to jump to specific elements.\nWe aim to support the widest array of browsers and assistive technologies as possible, so our users can choose the best fitting tools for them, with as few limitations as possible. Therefore, we have worked very hard to be able to support all major systems that comprise over 95% of the user market share including Google Chrome, Mozilla Firefox, Apple Safari, Opera and Microsoft Edge, JAWS and NVDA (screen readers), both for Windows and for MAC users.\nDespite our very best efforts to allow anybody to adjust the website to their needs, there may still be pages or sections that are not fully accessible, are in the process of becoming accessible, or are lacking an adequate technological solution to make them accessible. Still, we are continually improving our accessibility, adding, updating and improving its options and features, and developing and adopting new technologies. All this is meant to reach the optimal level of accessibility, following technological advancements. For any assistance, please reach out to info@atasteofky.com", "meta": {"lang": "en", "lang_score": 0.9140966534614563, "url": "https://atasteofkentucky.com/option/case-of-12/?wc_view_mode=list", "timestamp": "2023-01-26T21:31:14Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.018796151264264937], [3, 0.006265383754754978], [4, 0.005370328932647125]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.0], [6, 0.0], [7, 0.0], [8, 0.0], [9, 0.0], [10, 0.0]], "fraction_of_words_corrected_in_lines": 0.00620347394540943, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 801, "mean_word_length": 5.579275905118601, "num_of_sentences": 30, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9962546816479401, "num_of_stop_words": 152, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "Automate the exchange of data between NDJSON and cloud applications, databases and files on Windows, MacOS and Linux\nFast, reliable and background exchange of high volumes of NDJSON data between over 75 data sources.\nwe serve over 20000 companies\nExchange Data\nExchange business data in an automated and reliable way within and across applications for optimal data integration\nNDJSON is a file format based upon JavaScript. A NDJSON file consists of one record in JSON-format per line. No array grouping or record separator is used.\nAn integrated, scaleable and reliable lights-out NDJSON data exchange solution\n- Synchronize and copy data within and across platforms using a single SQL-language.\n- Invantive Data Hub runs NDJSON background jobs from the task scheduler of choice such as Windows Task Scheduler or the Linux cron daemon.\n- Combine data from dozens of cloud data sources and choose from the industry-largest number of connected tables.\n- High performance by parallel data streaming and integrated incremental and synchronization NDJSON loading strategies.\n- Available for Windows, MacOS and Linux running a single or dozens of CPU-cores.\n- Personal support and extensive community from Dutch market leader.\nThe NDJSON driver for Invantive Data Hub has advanced optimizations for great real-time NDJSON data performance.\nOffice for Entrepreneurs€ 59 /mo\n- Fixed low rate for up to 100 companies, each on any (cloud)platform from 75 available.\n- You pay as low as € 0.59 per company and platform. Also therefore: Guaranteed Lowest Prices!\n- Includes NDJSON connector for Power BI, Power Query and Azure Data Factory.\n- Includes Invantive Cloud for Power BI, Power Query, Tableau and Azure Data Factory.\n- Includes also Excel and Word add-in.\n- Includes also Get My Report.\n- No Power BI, Power Query, Tableau and Azure Data Factory user limit.\n- At most 2 interactive users on Invantive's interactive products.\n- Upgrade to 10 users on Invantive interactive products: € 119.\n- No use? No invoice.\n- Terminable at any time.\nAll Invantive subscriptions include online forum support and interactive contact such as chat and phone. For each company, a free 1-hour introduction is available and recommended for quick results. Specific conditions, acceptance criteria and fair use rules apply. Service only available in selected countries, including all EU members, the United Kingdom, the United States, Canada, Vietnam and Taiwan.", "meta": {"lang": "en", "lang_score": 0.8640507459640503, "url": "https://cloud.invantive.com/en/ndjson/data-hub", "timestamp": "2023-01-26T23:21:11Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.017518248175182483], [3, 0.01897810218978102], [4, 0.020437956204379562]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.0291395944083481], [6, 0.019248169778728303], [7, 0.00947465177119423], [8, 0.004714640198511167], [9, 0.0], [10, 0.0]], "fraction_of_words_corrected_in_lines": 0.0025906735751295338, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.6071428571428571, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 385, "mean_word_length": 5.337662337662338, "num_of_sentences": 28, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9272727272727272, "num_of_stop_words": 40, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "Any fool can write code that a computer can understand. Good programmers write code that humans can understand. Martin Fowler\nComplex code is hard to understand code because classes and methods do so many different things it’s impossible to understand how it works without stepping through the code to understand exactly what is going on. – Hosk\nWhen writing code you need to keep in mind – Will I be able to understand this code 6 months later when I have forgotten the business logic – Hosk\nThis started out as a small blog post, which seems to have kept growing and growing, so be prepared for a long read. I have a few CRM developer articles which you can find in the section Hosk’s CRM Developer Articles. It has an article on code readability and why experience is important in CRM development which I recommend you to read.\nBefore reading the article below I would like you to remember coding is an art, which is one of the reasons it takes a time to learn. Seeing coding as an art helps to explain why there is no right or wrong way to write code and good code/bad code is open to interpretation. So the thoughts below are my thoughts on coding and the processes and standards I use, yours might be different but I would love to hear them so please leave a comment.\nComplex code\nMost developers have been in the situation where you get assigned to a new project and one your first tasks is to resolve a bug. project.\nThe first step usually when bug fixing is recreating the bug, so I will assume you have done that so now it’s time to look at the code to try to fix the bug.\n- scan the code\n- getting a rough idea of the structure of the code\n- work out the flow\n- understand the data sources\n- Work out what parts of the code are changing the data.\nThe code is so complex and confusing the most efficient way to understand it is to debug the code, stepping through it line by line, hoping to get some understanding what’s happening and trying to find the elusive cause of the bug.\nThe code is one big pile of spaghetti code which you are afraid to change, if you are good (and have time) you will do some code refactoring but most likely you will cautiously poke a change towards the code with a long stick, cross fingers it fixes it before slowly backing away hoping to never see the code again.\nWhy complex code created\nJunior developers create complex code for simple problemsSenior developers create simple code for complex problemsA rushed developer creates code to refactor later\nCommon reasons for complex code\n- Written by a junior developer who is learning\n- Quick bug fixes\n- Time constraints\n- Refactor Later\n- No Peer Reviews\nInexperienced/Junior Developer\nTime constraints\nWhen developers rush they create code and more code but they do not create better quality code. Rushed code creates what is called technical debt, which will give you problems later (e.g. when you have to debug or enhance the code). A note for project managers, pushing developers to extremely tight schedules creates more code\nQuick Bug Fixes\nWhen developers add quick bug fixes or bug fixes in general it’s easy to wedge in some code and increase the complexity by veering away from creating simple code.\nRefactor Later\nDevelopers know they should write better code/simpler code but they write some code which works and fixes the bug/provides the functionality needed and they promise to “Refactor later”. You already know how this story ends, the developer is too busy, something urgent pops up and the code is never refactored.\nNo Peer Reviews\nThe most effective way to reduce the amount of complex code or bad code is to have a senior developer check the code with a peer review (could also be known as a code review). The developer won’t let their standards drop and will produce better code when they know it is going to be inspected by another developer.\nPeer reviews will also find some bugs in the code and are a great way to guide junior developers into converting complex code into simple code with pointers from the senior developer.\nThe smells of complex code\n- Large methods – Monster methods\n- confusingly named classes, methods and variables\n- methods which do lots of things\n- not consistent\n- tight coupling\n- dependent code\n- poorly structured code\nLarge Monster methods\nI’m sure all developers have come across a project where there is one monster method that runs for lines and lines and lines. They are often full of bug fixes and usually one developers knows the method (the poor soul has had to debug it many times) and often all the bugs flow their way.\nPeople are scared of the monster methods and rightly so because no one can understand it and no one wants to change it.\nPlugins are a common breeding ground for monster methods. I have seen numerous plugins where all the code is directly inside one big method in a plugin.\nDevelopers should not be afraid of changing code\nBadly named classes, methods and variables\nMethods doing more than one thing\nNot consistent\nComplex code/poor code will be inconsistent, this can usually occur when a developer has copied the code from various different sources or you have a number of developers working on a project where there is no standards being applied.\nThe difficulty inconsistently structured code brings is it makes the code hard to understand because there is no common structure, the code has a different flow.\nCode and customizations are difficult to understand and not being consistent makes the job even harder.\nTightly coupled/dependant code\nTightly coupled code is code which can’t be reused because it is dependent on other code in the project. The cause is often because the methods are doing more than one thing and are really a number of methods (if they were refactored) squashed into one.\nDependant code often can’t be reused even within the same project.\nPoorly structured code\nCode should be structured and organised in a logical manner. A simple form of structuring is splitting the business logic and queries into separate methods.\nCode structuring makes the code easier to understand and splits into smaller logical areas, this will help in code reuse and bug fixing (because you are isolating the bug)\nCRM Customization smells\nGiant workflows\nThe CRM GUI for workflows can make it difficult to work with workflows but when you have a giant workflow it can be almost impossible. There is a limit of four nested if statements in CRM (it’s true for CRM 2011, I’m dangerously assuming it’s still the case in CRM2013/CRM2015 but I could be wrong) and when you have a workflow which is hitting this limit, it’s a sign the workflow is too complex\nRead more about four nested if statement limitation\nBig workflows are very difficult to maintain and making changes can be very challenging, if you have workflows which are very big you should consider breaking these down into child workflows.\nLots of different customizations overlapping\nCRM customizations allow you to provide functionality in lots of different ways.\n- Plugins\n- Custom Plugins\n- Javascript\n- Business rules\n- Workflows\n- WCF webservices\n- Console apps\nSome customizations are better suited to certain problems and best practices/experience will guide you as to which customization you should use.\nI have seen problems where developers have used business rules and Javascript together because business rules don’t trigger Javascript on change events. By using the different customizations together you are adding to the complexity of the solution and making it difficult for developers to understand the flow.\nYou can get similar problems when workflows and plugins are used in conjunction with workflows running after the plugin (because plugin is synchronous and workflow is asynchronous) and the workflow overwrites the plugin set value.\nI’m not saying using plugins and workflow is wrong and should never be used but care should be taken when they overlap it can create a solution which is difficult to understand and debugging can be puzzling.\nWhen deciding what customizations to use, some consideration of what customizations already exist should be taken into account. The simpler the solution the easier it will be to maintain and extend the solution later. When I mention solutions I am referring to all the customizations as a whole.\nJavascript files with duplicated methods\nThe most common method of structuring Javascript code is having one Javascript file for each entity, CRM pushes people into this model by making you choose a file to upload for the form. This isn’t incorrect because there will be Javascript methods only suitable for each form because they will be manipulating fields on the form.\nThis can cause people to copy methods from one entity Javascript file to another entity Javascript file.\nWhat happens later if a bug is found in one of these duplicated methods, usually it gets fixed on one form. Then you have duplicated code, some of which is fixed and some which isn’t.\nNo common Javascript files\nFollowing on from the point above, if there are common Javascript functions then put them in a common Javascript file rather than copying the same function many times.\nAll the code in the plugin\nMy personal view is you should have no code in a plugin, it should all be moved out to separate classes.\nThe first reason is you have created a big monster method, which is hard to understand, debug and enhance.\nTesting code in a plugin is difficult because you need to mock all the plugin code, if you remove the code from the plugin, you can test the code by just passing in a OrganisationService (e.g. a connection to CRM).\nYou cannot reuse any code inside a plugin\nCopy and paste code (plugins and Javascript)\nComplex code means people cannot reuse the code, so they often end up copying parts of tightly coupled code from one area in CRM to another. This can often lead to messy/poor code but can also allow bugs to slip in with code which isn’t relevant or needed.\nThe problems with complex code and customizations\nThe code is hard to read\nWhen writing code you need to keep in mind -Will I be able to understand this code 6 months later when I have forgotten the business logic.\nComplex code is hard to understand often because it’s not structured and modularized. Understanding code which is logically structured into separate classes and small focused methods is easy because the code does what you expect.\nComplex code has large methods which do many things, the classes and method names are confusing because it’s difficult to apply a name to a class/method which does many different actions.\nWell structured code is like a tidy room, with everything tidied away into draws, bookshelves and wardrobes. Easy to understand and use. Things are easy to find. If you add a new item to the tidy room, you can place it with the other similar items\nComplex code is like a messy student room, everything is on the floor. It’s hard to understand the where everything is or should be. Objects are to find because you are not sure where to look. If you add a new object to the messy room, where do you put it and will mess up the organisation of the room.\nSlightly improved code is where the messy student buys a big wardrobe and a chest of drawers and chucks groups of things. You know you need to look in the chest of drawers but if the socks are not in their own drawer it’s going to take you time to find them among the other clothes.\nThe code is hard to debug\nComplex code is hard to debug because it’s because it isn’t structured logically (because it’s in big methods) and the code isn’t easy to understand. Often the only way to understand what the code is doing is slowly stepping through it.\nThe code is hard to enhance\nComplex code creates complex bugs\nNo Reuse\nComplex code is tightly coupled and big methods are very difficult to reuse. It means developers have to write more code, which means more testing.\nMore code will increase the chance of more bugs.\nA lack of reuse in code will result in developers copying parts of code which can result in copy and paste bugs.\nDuplicate code will result in bugs where some of the duplicated code is bug fixed and other parts get forgotten about.\nEncourages more of the same\nJunior developers and developers in general will copy working code. The good developers will refactor the code, the poor developer will just leave it as it is.\nCopying complex code will create more complex code.\nIf developers see other people creating complex/bad code then they will too. It’s letting standards drop and everyone will pay for it later down the line when bug fixing takes twice as long\nJunior developers will copy it\nDevelopers should set high standards and great code for Junior developers to learn from.\nIf everyone is creating simple well-structured code, the junior developers will follow their lead.\nCreating complex code/quick code really causes problems for a project later. Finding and fixing bugs takes a lot longer because the code is harder to understand and fixing the bug is difficult because the code is in large methods and not well structured.\nThe difficulty in fixing large methods is they do many things and you have to make sure the method still does all those actions and changes.\nIf you compare this to fixing a small focused method, you only need to make sure it still does the one action.\nComplex code creates problems for the project later on where it will become harder to maintain the code whilst fixing bugs and enhancing. Complex code will mean people take longer to get up to speed on a project, whilst they learn how this individual project is setup and works.\nI’m sure lots of developers have worked on legacy projects with complex code and it’s not an enjoyable experience, so make sure you are not creating projects like that.", "meta": {"lang": "en", "lang_score": 0.9455145001411438, "url": "https://crmbusiness.wordpress.com/2015/01/22/the-problems-with-complex-code/", "timestamp": "2023-01-26T22:30:13Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.014767932489451477], [3, 0.004922644163150493], [4, 0.006329113924050633]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.018383841941221012], [6, 0.01162688276226548], [7, 0.009415911379657603], [8, 0.008021331452874678], [9, 0.006623295187333438], [10, 0.005239804874606353]], "fraction_of_words_corrected_in_lines": 0.00041511000415110004, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.2, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 2408, "mean_word_length": 4.724252491694352, "num_of_sentences": 93, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9871262458471761, "num_of_stop_words": 358, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "Web terminals (DEPRECATED) (FREE)\n- Deprecated in GitLab 14.5.\n- Disabled on self-managed in GitLab 15.0.\nWARNING: This feature was deprecated in GitLab 14.5.\nOn self-managed GitLab, by default this feature is not available. To make it available, ask an administrator to enable the feature flag named\n- Read more about the non-deprecated Web Terminals accessible through the Web IDE.\n- Read more about the non-deprecated Web Terminals accessible from a running CI job.\nWith the introduction of the Kubernetes integration, GitLab can store and use credentials for a Kubernetes cluster. GitLab uses these credentials to provide access to web terminals for environments.\nNOTE: Only users with at least the Maintainer role for the project access web terminals.\nHow it works\nA detailed overview of the architecture of web terminals and how they work can be found in this document. In brief:\n- GitLab relies on the user to provide their own Kubernetes credentials, and to appropriately label the pods they create when deploying.\n- When a user navigates to the terminal page for an environment, they are served a JavaScript application that opens a WebSocket connection back to GitLab.\n- The WebSocket is handled in Workhorse, rather than the Rails application server.\n- Workhorse queries Rails for connection details and user permissions. Rails queries Kubernetes for them in the background using Sidekiq.\n- Workhorse acts as a proxy server between the user's browser and the Kubernetes API, passing WebSocket frames between the two.\n- Workhorse regularly polls Rails, terminating the WebSocket connection if the user no longer has permission to access the terminal, or if the connection details have changed.\nGitLab and GitLab Runner take some precautions to keep interactive web terminal data encrypted between them, and everything protected with authorization guards. This is described in more detail below.\n- Interactive web terminals are completely disabled unless\n[session_server]is configured.\n- Every time the runner starts, it generates an\nx509certificate that is used for a\nwss(Web Socket Secure) connection.\n- For every created job, a random URL is generated which is discarded at the end of the job. This URL is used to establish a web socket connection. The URL for the session is in the format\n(IP|HOST):PORT/session/$SOME_HASH, where the\nPORTare the configured\n- Every session URL that is created has an authorization header that needs to be sent, to establish a\n- The session URL is not exposed to the users in any way. GitLab holds all the state internally and proxies accordingly.\nEnabling and disabling terminal support\nNOTE: AWS Classic Load Balancers do not support web sockets. If you want web terminals to work, use AWS Network Load Balancers. Read AWS Elastic Load Balancing Product Comparison for more information.\nAs web terminals use WebSockets, every HTTP/HTTPS reverse proxy in front of\nWorkhorse must be configured to pass the\nConnection and\nUpgrade headers\nto the next one in the chain. GitLab is configured by default to do so.\nHowever, if you run a load balancer in front of GitLab, you may need to make some changes to your configuration. These guides document the necessary steps for a selection of popular reverse proxies:\nWorkhorse doesn't let WebSocket requests through to non-WebSocket endpoints, so\nit's safe to enable support for these headers globally. If you prefer a\nnarrower set of rules, you can restrict it to URLs ending with\nThis approach may still result in a few false positives.\nIf you installed from source, or have made any configuration changes to your Omnibus installation before upgrading to 8.15, you may need to make some changes to your configuration. Read Upgrading Community Edition and Enterprise Edition from source for more details.\nTo disable web terminal support in GitLab, stop passing\nConnection and\nUpgrade hop-by-hop headers in the first HTTP reverse\nproxy in the chain. For most users, this is the NGINX server bundled with\nOmnibus GitLab, in which case, you need to:\n- Find the\nnginx['proxy_set_headers']section of your\n- Ensure the whole block is uncommented, and then comment out or remove the\nFor your own load balancer, just reverse the configuration changes recommended by the above guides.\nWhen these headers are not passed through, Workhorse returns a\n400 Bad Request response to users attempting to use a web terminal. In turn,\nthey receive a\nConnection failed message.\nLimiting WebSocket connection time\nBy default, terminal sessions do not expire. To limit the terminal session lifetime in your GitLab instance:\n- On the top bar, select Main menu > Admin.\n- Select Settings > Web terminal.\n- Set a\nmax session time.", "meta": {"lang": "en", "lang_score": 0.8702277541160583, "url": "https://git.coredump.ch/help/administration/integration/terminal.md", "timestamp": "2023-01-26T21:23:40Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.03333333333333333, "fraction_of_characters_in_duplicate_lines": 0.0071156289707750954, "fraction_of_characters_in_most_common_ngram": [[2, 0.015247776365946633], [3, 0.009911054637865312], [4, 0.0071156289707750954]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.02801922486961857], [6, 0.023119907861621807], [7, 0.017644690119705677], [8, 0.012508017960230917], [9, 0.007421362105383342], [10, 0.0024175711125970886]], "fraction_of_words_corrected_in_lines": 0.014304291287386216, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.28169014084507044, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 758, "mean_word_length": 5.191292875989446, "num_of_sentences": 43, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9643799472295514, "num_of_stop_words": 107, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "Please take some time to read John's Brilliant poem in response to Brenda's word prompt 'Writing'\nHere's the link to his beautiful hib: https://hubpages.com/literature/The-Art … anted-Pen.\nThank you so much, John, for sharing this lovely poem. I enjoyed reading it and found it very inspirational.\nHello John!\nExcellent response to the word prompt, Writing. As always, you have created a wonderful poem. I do agree with your message that writing is addictive. I enjoyed reading about Georgina’ s writing journey and eventual success.\nThank you for sharing.\nAnd thank you Misbah for sharing John’s response.\nFor some reason your link isn't working.\nGuess another glitch???\nHere it is again...\nhttps://hubpages.com/literature/The-Art … hanted-Pen\nYes, seems like some bug. Forums aren't letting me create hyperlinks as well. Don't know why. Thank you for sharing the link to John's work again. Much Gratitude!\nBlessings always!\nLet's hope they get this fixed quickly.\nOh no...quick isn't a word they know.\nYes, I had the same problem with the link but thought it was just me. Thanks for resharing it, Brenda.\nSsshh... They'll hear that we've found a solution to this difficulty. They don't like it when we communicate\nI wonder if they sent the cyber cookie monster.\nIf this trend continues, the day will come when that cyber cookie monster will devour the entire forum discussion.\nDon't worry Misbah...\nWe'll find a way to curb his hunger....\nMaybe John can use his magic pen.\nMisbah, thank you for sharing John's poem. If only I could purchase one of those pens on Amazon. John is so creative; I don't think he has ever been stumped, by Brenda or in his poems from the porch.\nLinda, I think those pens would sell out fast. Thank you for reading my work. I hope to bring back Poems From the Porch soon.\nLinda...got to say I agree.\nIt's hard to stump John...he can write on any topic.\nGreat talent. Maybe he has the only magic pen.\nAww..Misbah. Thank you so much for sharing and for your very kind words. I am so happy you found the poem inspirational.\nThanks Misbah for sharing John's post.\nJohn, this is a wonderful poem about a girl getting addicted to writing with the help of Higher Powers and eventually rising to fame. I loved it thoroughly. Thank you for the awesome share, which is a marvelous response to the word prompt, \"Writing.\"\nI really like the way you responded to this prompt. Writing Georgina's story in a poem is very clever, John. Well done!\nThanks for posting John's poem, Misbah.\nMaster strokes by a master writer. It is always a pleasure to read John's writings. He does it the way it's supposed to be done.\nI guess I hadn't thought about all those articles on writing.\nMy thought process...\nWe are writers ~ therefore we Know writing.\nYour poem ~ Georgina's Enchanted Pen\" you tells us how Georgiana begins when she's trying to satisfy that urge to write.\nShe picks up her pen, hoovering over the page, waiting for the words to flow.\nWhen an idea surfaces, her fingers cannot stop. Her muse is on a roll.\nShe forces herself to take a break but the words creep into her dreams.\nWhen she awakes she uses her enchanted pen to pick up where she left off.\nShe wrote until her pen ran out of ink then proofread her work seeing it wasn't bad.\nHer words soon get published & she rises to fame.\nIt was though a helping hand had guided that magical pen.\nGreat writing here!\nThere are times we get an idea & just can't stop until we're finished.\nI know what it's like to have those words follow me in my dreams.\nI'll post a link in the word prompt article.\nThanks for reading and analysing the poem, Brenda. I had no idea what I was going to write when I started, but my pen just flowed as though it was enchanted lol. Sometimes, I get an idea for something I am writing in a dream and have to jot it down straight away. Glad you enjoyed the poem, and thanks for putting the link on your word prompt article.\nJohn's is a masterful poem about the almost mystical drive of Georgina following her muse to publishing success and fame. A brilliant piece of writing! Thanks Brenda for sharing it!\nThanks for sharing and this is really a very interesting poem by John. Well done.\nSalam Misbah,\nThe link is not working.\nGreat work there John. I loved your poem. It only goes to prove passion leads to success. Georgina's story is awe inspiring. She really must have had some divine help to achieve fame and glory with her first book. Your creativity is admirable John. A very good response to this week's word prompt. thanks for sharing Misbah.\nVidya, it is always great to receive your comments. I am glad you found Georgina’s story to be inspiring even though it may be a little\nhard to believe that she would achieve success with her first book.\nYour poem was wonderful, John. It does happen at times, that once we get an idea and we start writing, the words and the story just seem to flow. I like both the optimism and the joy you express in your poem of being in the zone of creativity. I think that often we impose our own limitations instead of just writing for the joy of it and we talk ourselves out of this creative process. Children seem to be natural storytellers but most adults have a hard time with this process. Sometimes, we become our worst critics which inhibits our flow of thoughts and our abilities. Great job with this prompt and helping us to get out of the mental blocks of our own making.\nGreat response to the word prompt challenge, Jodah. And I agree that the most difficult part of writing is the beginning. Georgina's story is very inspiring.\nStay safe and healthy...\nThank you for reading this, Moon. It is good that you found the story inspiring. Stay well.\nby Rosina S Khan 2 weeks ago\nThis was lovely poetry in response to Brenda's prompt, \"Beginnings\" penned by John Hansen. Here is the link to his poetry:https://hubpages.com/literature/The-Lov … BeginningsI feel happy and hopeful that the man sought out a gipsy's love potion and spell to rekindle his love with...\nby Rosina S Khan 4 weeks ago\nIt is wonderful that John has dedicated a poem to his cats. Here is the link:https://hubpages.com/literature/The-Fel … About-CatsThis is a very lovely poetry about each of your cats. It was fun to read about their daily activities. It was indeed very enjoyable, John except that one deceased...\nby Gianella Labrador 10 months ago\nSharing John's Response for this Weekly Word Prompt on Puzzles.Here is the link:https://hubpages.com/literature/The-Jig … ut-PuzzlesHe dedicates the first two to Brenda and Ron.Great response John as always! Your muse never fail to amaze us. I hope it never disappoint you too from here...\nby Pamela Oglesby 4 hours ago\nJohn has published a very cute poem about pigs.https://hubpages.com/literature/My-Pigs … ket-A-Poem\nby John Hansen 13 days ago\nChitrangada gives us two wonderful poems that meet the prompt \"beginnings\" perfectly, I love the quotes as well.https://hubpages.com/literature/Beginni … Hopes-Poem\nby Ravi Rajan 3 days ago\nJohn, your interesting poem about the two preachers reminds me of an interesting quote on religion said by Aristotle\"Religion was invented when the first con man met the first fool.\"That said, we will have good and bad preachers as long we have people. We will always have charlatans who...\nCopyright © 2023 The Arena Media Brands, LLC and respective content providers on this website. HubPages® is a registered trademark of The Arena Platform, Inc. Other product and company names shown may be trademarks of their respective owners. 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(Privacy Policy)\n|Amazon Tracking Pixel\n|Some articles display amazon products as part of the Amazon Affiliate program, this pixel provides traffic statistics for those products (Privacy Policy)\n|This is a data management platform studying reader behavior (Privacy Policy)", "meta": {"lang": "en", "lang_score": 0.94142085313797, "url": "https://hubpages.com/literature/forum/353830/the-art-of-writing--georginas-enchanted-pen-by-john-hansen#post4218378", "timestamp": "2023-01-26T21:40:52Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.06766917293233082, "fraction_of_characters_in_duplicate_lines": 0.03549595740485111, "fraction_of_characters_in_most_common_ngram": [[2, 0.04289094853086176], [3, 0.011831985801617038], [4, 0.019719976336028396]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.0534514114019135], [6, 0.04066059037792758], [7, 0.03280750855172024], [8, 0.025716866948009356], [9, 0.019769502570255483], [10, 0.015542295263961304]], "fraction_of_words_corrected_in_lines": 0.02495201535508637, "fraction_of_lines_ending_with_ellipsis": 0.057692307692307696, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 1, "word_count": 2032, "mean_word_length": 4.991141732283465, "num_of_sentences": 154, "symbol_to_word_ratio": 0.00984251968503937, "fraction_of_words_with_alpha_character": 0.9896653543307087, "num_of_stop_words": 248, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "At 01:25 PM 10/23/00, you wrote: >Microsoft has a decent script debugger that handles Javascript and VB >Script, but it's a pain to use because if you turn it on, it will force >you to debug every JS error you run into while you surf. > >http://msdn.microsoft.com/jscript/ and go to \"Script Debugger\" in the >menu if you want to check it out. This has been relocated to http://msdn.microsoft.com/scripting/ on their site. Bill Mason data at data1701d.com Dateline: Starfleet http://www.data1701d.com http://profile.guru.com/billmason http://www.freeagent.com/billmason http://bmason.freelancers.net", "meta": {"lang": "en", "lang_score": 0.7998515367507935, "url": "https://lists.evolt.org/pipermail/thelist/Week-of-Mon-20001023/006150.html", "timestamp": "2023-01-26T22:17:25Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.019342359767891684], [3, 0.017408123791102514], [4, 0.03481624758220503]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.0], [6, 0.0], [7, 0.0], [8, 0.0], [9, 0.0], [10, 0.0]], "fraction_of_words_corrected_in_lines": 0.0, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 82, "mean_word_length": 6.304878048780488, "num_of_sentences": 4, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9634146341463414, "num_of_stop_words": 9, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "Inspired by strangers. Who muck things up.\nSo you've got a stranger in your world, interacting with your main character. Do they influence that world just by being there? Do they change things? Like really muck stuff up?\nIn Part I of our favourite inter-dimensional reporter's visit to Ilium, things seem to be going okay. With Vergil's help, she seems to have brought Neas out of his shell — even coaxed a few actual answers out of him for her interview. Smooth, yeah? In and out, right?\nNot so fast.\nWhen a stranger visits your world, it's a two way street. Their guide influences them, but they influence their guide too. They plant ideas, stir up memories, and maybe even impact where the story goes from there.\nThey are mucking with the laws of space, time, and fiction, after all.\nRule number one: tread carefully!\n“Goose-it! Get behind that column, pronto!”\nI jump! I just catch the buzz—like bees, wind, and my computer fan mixed together—before lights with riders roar by my hiding spot. Neas has disappeared in the fog.\nHe’s back before I can see where he hid. “Yikes,” he says. “You still itchin’? Perfect. See those two bogeys? The ones whizzin’ down the road? Those markin’s mean they work for that gooser I was tellin’ you ‘bout earlier. Gore. Yeah. And you hear that whizzin’ when they flew by? Soundin’ kinda like Vergil?”\n“Like me, Sir?”\n“Yeah… that’s my favorite sound. The whizzin’ a hoverboard makes when it boosts across the road. Always wanted to try ridin’ one… yet another thing Mentor won’t let me try. But they’re hard as heck to find, you know? And bikes ain’t the same, no matter what Acamas says. I can see it now… wind blowin’ through my hair, boosters flyin’ me higher and higher, then… BAM! All of Ilium right in front of me. The stars and the spires and everythin’ in-between. Yeah…”\n“That sounds pretty cool,” I smile. I can see it—shoot, I have seen it. But I won’t spoil the surprise for him. Aeneas, Ilium's future unwilling savior, doesn’t need pro-tips from a—uh—‘porter’ like me. “Yeah, that sounds really cool. Kind of brings me to my next question—what's your dream?”\n“Hmm… my… my dream?”\n“Like, what do you want most from your life?”\n“Oh! Okay, okay. Sorry, pal. Thought you were gettin’ all personal again, dang it.”\n“Oh! Okay, okay. Sorry, pal. Thought you were gettin’ all personal again, dang it.”\nI mean, I was, but he has a different idea of personal, I guess. He goes on.\n“Don’t tell Mentor this, but I’ve always dreamed of… of seein’ the world. The world outside the Wall, you get me? The mountains… the forests… the deserts… even the, um… the coats!”\n“I believe you mean ‘coasts’, Sir.”\n“Goose-it, Vergil! But, um, yeah. The coasts. The water, you know? Always wanted to try swimmin’. Feelin’ the cool water on my skin. With the sun all beamin’ down, kinda like Vergil’s spotlight… but… but bigger… and brighter! Yeah. Goin’ swimmin’… very pigeon.”\nI love it—his beaming face, the power behind his voice—that’s what I do intergalactic interviews for. It’s totally ‘pigeon.’ But the poor robot looks like it’s getting nervous with all this travel-talk. “We have water too, Sir,” it says. “Right by our home.”\n“Vergil… that’s not the same, buddy. Vergil’s talkin’ ‘bout the sewers… that’s where we live, you know. And yeah, sure… we got tons of water. But it ain’t exactly the swimmin’ type. Hey… hey porter… you want me to level with ya?”\nLevel with me—tell me something, true, right? “Yeah. I'm listening.”\n“I kinda. You know. Envy you or somethin’. Bein’ able to travel all over the world. Visitin’ people. Truth is… I’m tired of hidin’ down here. Tired of livin’ in the dark. My dream—you gettin’ this or what?—is to get my own ship… a pirate ship’d be perfect… and get outta this place. Get outta this place for good. And see the world…”\n“Sir… you would leave us? Leave our home?”\n“Vergil… c’mon!”\nVergil’s spotlight dims. It swivels away from Neas and looks off in the distance. I want to hug it.\n“I would miss you, Sir. My circuits are not meant for processing such…”\n“Stop itchin’ buddy! You’d be comin’ too of course! We’d all go. Me and you and the boys. We’d get outta this place and travel the world in our own pirate ship. Yeah. That’s my dream.”\n“That's an awesome dream,” I grin. “Hey, last question.” I pause this one to watch his face straight-on. “What's your biggest fear?”\n“That's an awesome dream,” I grin. “Hey, last question.” I pause this one to watch his face straight-on. “What's your biggest fear?”\nNeas bites his lip.\nIt’s not a fair question to ask a stranger. It’s a worse question to ask a stranger when you’ve read his life story before he’s lived it. I open my mouth—\n“Hey, no one’s gonna know—and—” But you can’t talk that kind of thing out of a person. I stop walking for a second, lean against a nearby column, and just wait with a soft smile. Next move’s his.\nNeas swallows hard.\n“Well, porter. With all those goosers I was goin’ on ‘bout before… Gore, the spooks, jukes, and even those bogeys in the towers… might think I got a lot to be afraid of. But… truth is… I really just don’t wanna be alone, you get me? Mentor, Acamas, Byron and the others… I may make fun of’em and everythin’, but…those guys’re like my brothers, you know? Like family. Only family I’ve ever had. Don’t know what I’d do without’em.”\n“…you do have me, Sir. I will never leave you.”\n“I know, buddy. I know.”\nI glance away at my feet. It’s strange, bringing fears and dreams to the light, and then standing over them as they hit you, full-blast, with all their scents and graspings and feelings. It’s worse that I already know his fears will come true. I croak: “Hey, thanks for sharing. You’re a good interviewee.”\n“Yeah, yeah.”\nHe’s shrugged and sealed it all off again—he doesn’t ‘give a goose.’ But I’m feeling queasy—and it’s not because of the scent, a bit like blood and old burger, that’s rising from the narrow alleyway we’re squeezing into. I’m hearing screams, laughs, the clinking of glasses and raucous music from the gaudy building on the right.\n“Well. There it is.”\nWe’re in the back alley behind Gore’s pub, about two yards away from the dumpster—\nFrom the dumpster where Neas gets caught. And beaten. And today is his—\nI know this scene. My eyes widen—I’m trying to open my mouth to warn him. We’re literally minutes away from the beginning of his story—\nDangit! His family!\n“Go home, right now!” I cry. “Go home, save your family!”\nBut the words I hear, in my voice, are, “Oh, shoot, I gotta get home. I’ve got a family interview in ten minutes.” No I don’t!\n“Sure you don’t wanna stay for dinner?\" Neas asks. \"Heard that melonhead’s plannin’ a big performance tonight… gonna be tons of food left for us to…”\n“No, you need to get out of here right now!” becomes “No, I gotta jet right now.” Jet? Whodahell says that?\n“Oh. Um… yeah, okay. Stay, don’t stay… don’t really give a goose. Just more for me anyways.”\nI’m stomping, cursing. I’m trying to make signs or something to warn him. But I see my reflection in a murky puddle of I-don’t-wanna-know besides us, and in that reflection I’ve got a reassuring, apologetic smile, and I’m waving as I step away. It’s a rule about interdimensional interviews: I can’t change the story. It’s a rule I’ve never tried to break before, but this poor kid, on his birthday—! My gut’s twisting; I’d have clenched teeth and hot, frustrated tears if the forces of this reality would let me.\nI’m almost out of the alleyway—I stop, shoulders sagging, when he calls to me.\n“Hey porter? You, um… you won’t forget ‘bout me or anythin’, will ya? You know… when you’re out there, portin’ in some other gooser’s city?”\n“No. You’re a pretty unforgettable character,” I sigh. He can’t see the sad smile. “Hey, Neas?”\n“Happy—happy birthday.”\nHe grins that smirky, friendly grin. The last I’m going to see of him as the rules take me around the corner and leave him to his fate.\n“Well, c’mon buddy! Let’s goose-it while we still can. I’m hungry!”\nHis voice fades, and I’m gone as his story begins.\nLastly, an inter-dimensional message from your favourite inter-dimensional reporter, Petre Pan:\nI'd love to help your book get more 'chatter' around the internet by interviewing one of your characters. E-mail me - petrepan(at)gmail(dot)com - with the \"place\" your character wants to meet me, and I'll send you a few questions to answer in your character's voice. This fun collaboration gives you writing practice, and hopefully generates you a little extra readership. For unpublished authors, this is also a great way to deepen your character!\nDon't forget to check out the Blog Hop, and join in, too!\n\n\n", "meta": {"lang": "en", "lang_score": 0.9223644137382507, "url": "https://www.johnkrissilas.com/2013/03/thursdays-children-stranger-in-strange_10.html", "timestamp": "2023-01-26T21:31:47Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.06060606060606061, "fraction_of_characters_in_duplicate_lines": 0.05943331029716655, "fraction_of_characters_in_most_common_ngram": [[2, 0.0034554250172771253], [3, 0.002902557014512785], [4, 0.00469937802349689]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.038545797398851944], [6, 0.035473949540966165], [7, 0.03238930676563399], [8, 0.029584769064773243], [9, 0.026903049838829657], [10, 0.0240273800377174]], "fraction_of_words_corrected_in_lines": 0.006459948320413436, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 1538, "mean_word_length": 4.704161248374512, "num_of_sentences": 155, "symbol_to_word_ratio": 0.026657997399219768, "fraction_of_words_with_alpha_character": 0.9954486345903771, "num_of_stop_words": 168, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "Awesome list of datasets in 100+ categories\nWith an estimated 44 zettabytes of data in existence in our digital world today and approximately 2.5 quintillion bytes of new data generated daily, there is a lot of data out there you could tap into for your data science projects. It's pretty hard to curate through such a massive universe of data, but this collection is a great start. Here, you can find data from cancer genomes to UFO reports, as well as years of air quality data to 200,000 jokes. Dive into this ocean of data to explore as you learn how to apply data science techniques or leverage your expertise to discover something new.\nBy Etienne D. Noumen, Senior Software Engineer.\nData science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.\nIn this blog, we provide links to popular open-source and public data sets, data visualizations, data analytics resources, and data lakes.\nTable of Contents\n- Latest complete Netflix movie dataset\n- Common Crawl\n- Dataset on protein prices\n- CPOST dataset on suicide attacks over four decades\n- Credit Card Dataset – Survey of Consumer Finances (SCF) Combined Extract Data 1989-2019\n- Drone imagery with annotations for small object detection and tracking dataset\n- NOAA High-Resolution Rapid Refresh (HRRR) Model\n- Registry of Open Data on AWS\n- Textbook Question Answering (TQA)\n- Harmonized Cancer Datasets: Genomic Data Commons Data Portal\n- The Cancer Genome Atlas\n- Therapeutically Applicable Research to Generate Effective Treatments (TARGET)\n- Genome Aggregation Database (gnomAD)\n- SQuAD (Stanford Question Answering Dataset)\n- PubMed Diabetes Dataset\n- Drug-Target Interaction Dataset\n- Pharmacogenomics Datasets\n- Pancreatic Cancer Organoid Profiling\n- Africa Soil Information Service (AfSIS) Soil Chemistry\n- Dataset for Affective States in E-Environments\n- NatureServe Explorer Dataset\n- Flight Records in the US\n- Worldwide flight data\n- 2019 Crime statistics in the USA\n- Yahoo Answers DataSets\n- History of America 1400-2021\n- Persian words phonetics dataset\n- Historical Air Quality Dataset\n- Stack Exchange Dataset\n- Awesome Public Datasets\n- Agriculture Datasets\n- Biology Datasets\n- Climate and Weather Datasets\n- Complex Network Datasets\n- Computer Network Datasets\n- CyberSecurity Datasets\n- Data Challenges Datasets\n- Earth Science Datasets\n- Economics Datasets\n- Education Datasets\n- Energy Datasets\n- Entertainment Datasets\n- Finance Datasets\n- GIS Datasets\n- Government Datasets\n- Healthcare Datasets\n- Image Processing Datasets\n- Machine Learning Datasets\n- Museums Datasets\n- Natural Language Datasets\n- Neuroscience Datasets\n- Physics Datasets\n- Prostate Cancer Datasets\n- Psychology and Cognition Datasets\n- Public Domains Datasets\n- Search Engines Datasets\n- Social Networks Datasets\n- Social Sciences Datasets\n- Software Datasets\n- Sports Datasets\n- Time Series Datasets\n- Transportation Datasets\n- eSports Datasets\n- Complementary Collections\n- Categorized list of public datasets: Sindre Sorhus /awesome List\n- Platforms\n- Programming Languages\n- Front-End Development\n- Back-End Development\n- Computer Science\n- Big Data\n- Theory\n- Books\n- Editors\n- Gaming\n- Development Environment\n- Entertainment\n- Databases\n- Media\n- Learn\n- Security\n- Content Management Systems\n- Hardware\n- Business\n- Work\n- Networking\n- Decentralized Systems\n- Higher Education\n- Events\n- Testing\n- Miscellaneous\n- Related\n- US Department of Education CRDC Dataset\n- Nasa Dataset: sequencing data from bacteria before and after being taken to space\n- All Trump’s twitter insults from 2015 to 2021 in CSV.\n- Data is plural\n- Global terrorism database\n- The dolphin social network\n- Dataset of 200,000 jokes\n- The Million Song Dataset\n- Cornell University’s eBird dataset\n- UFO Report Dataset\n- CDC’s Trend Drug Data\n- Health and Retirement study: Public Survey data\nThis is a huge list, so here are here are 100+ more categories\nLatest complete Netflix movie dataset\nCreated from 4 APIs. 11K+ rows and 30+ attributes of Netflix (Ratings, earnings, actors, language, availability, movie trailers, and many more)\nExplore this dataset using FlixGem.com (this dataset is powering this webapp)\nCommon Crawl\nA corpus of web crawl data composed of over 50 billion web pages. The Common Crawl corpus contains petabytes of data collected since 2008. It contains raw web page data, extracted metadata and text extractions.\nAWS CLI Access (No AWS account required)\naws s3 ls s3://commoncrawl/ --no-sign-request\nDataset on protein prices\nData on Primary Commodity Prices are updated monthly based on the IMF’s Primary Commodity Price System.\nCPOST dataset on suicide attacks over four decades\nThe University of Chicago Project on Security and Threats presents the updated and expanded Database on Suicide Attacks (DSAT), which now links to Uppsala Conflict Data Program data on armed conflicts and includes a new dataset measuring the alliance and rivalry relationships among militant groups with connections to suicide attack groups. Access it here.\nCredit Card Dataset – Survey of Consumer Finances (SCF) Combined Extract Data 1989-2019\nYou can do a lot of aggregated analysis in a pretty straightforward way there.\nDrone imagery with annotations for small object detection and tracking dataset\n11 TB dataset of drone imagery with annotations for small object detection and tracking\nDownload and more information are available here\nDataset License: CDLA-Sharing-1.0\nHelper scripts for accessing the dataset: DATASET.md\nDataset Exploration: Colab\nNOAA High-Resolution Rapid Refresh (HRRR) Model\nThe HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh.\nRegistry of Open Data on AWS\nThis registry exists to help people discover and share datasets that are available via AWS resources. Learn more about sharing data on AWS.\nSee all usage examples for datasets listed in this registry.\nSee datasets from Digital Earth Africa, Facebook Data for Good, NASA Space Act Agreement, NIH STRIDES, NOAA Big Data Program, Space Telescope Science Institute, and Amazon Sustainability Data Initiative.\nTextbook Question Answering (TQA)\n1,076 textbook lessons, 26,260 questions, 6229 images\nDocumentation: https://allenai.org/data/tqa\nHarmonized Cancer Datasets: Genomic Data Commons Data Portal\nThe GDC Data Portal is a robust data-driven platform that allows cancer researchers and bioinformaticians to search and download cancer data for analysis.\nGenomic Data Commons Data Portal\nThe Cancer Genome Atlas\nThe Cancer Genome Atlas (TCGA), a collaboration between the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI), aims to generate comprehensive, multi-dimensional maps of the key genomic changes in major types and subtypes of cancer.\nAWS CLI Access (No AWS account required)\naws s3 ls s3://tcga-2-open/ --no-sign-request\nTherapeutically Applicable Research to Generate Effective Treatments (TARGET)\nThe Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program applies a comprehensive genomic approach to determine molecular changes that drive childhood cancers. The goal of the program is to use data to guide the development of effective, less toxic therapies. TARGET is organized into a collaborative network of disease-specific project teams. TARGET projects provide comprehensive molecular characterization to determine the genetic changes that drive the initiation and progression of childhood cancers. The dataset contains open Clinical Supplement, Biospecimen Supplement, RNA-Seq Gene Expression Quantification, miRNA-Seq Isoform Expression Quantification, miRNA-Seq miRNA Expression Quantification data from Genomic Data Commons (GDC), and open data from GDC Legacy Archive. Access it here.\nGenome Aggregation Database (gnomAD)\nThe Genome Aggregation Database (gnomAD) is a resource developed by an international coalition of investigators that aggregates and harmonizes both exome and genome data from a wide range of large-scale human sequencing projects. The summary data provided here are released for the benefit of the wider scientific community without restriction on use. Downloads\nSQuAD (Stanford Question Answering Dataset)\nStanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. Access it here.\nPubMed Diabetes Dataset\nThe Pubmed Diabetes dataset consists of 19717 scientific publications from PubMed database pertaining to diabetes classified into one of three classes. The citation network consists of 44338 links. Each publication in the dataset is described by a TF/IDF weighted word vector from a dictionary which consists of 500 unique words. The README file in the dataset provides more details.\nDrug-Target Interaction Dataset\nThis dataset contains interactions between drugs and targets collected from DrugBank, KEGG Drug, DCDB, and Matador. It was originally collected by Perlman et al. It contains 315 drugs, 250 targets, 1,306 drug-target interactions, 5 types of drug-drug similarities, and 3 types of target-target similarities. Drug-drug similarities include Chemical-based, Ligand-based, Expression-based, Side-effect-based, and Annotation-based similarities. Target-target similarities include Sequence-based, Protein-protein interaction network-based, and Gene Ontology-based similarities. The original task on the dataset is to predict new interactions between drugs and targets based on different types of similarities in the network. Download link\nPharmacogenomics Datasets\nPharmGKB data and knowledge is available as downloads. It is often critical to check with their curators at feedback@pharmgkb.org before embarking on a large project using these data, to be sure that the files and data they make available are being interpreted correctly. PharmGKB generally does NOT need to be a co-author on such analyses; They just want to make sure that there is a correct understanding of our data before lots of resources are spent.\nPancreatic Cancer Organoid Profiling\nThe dataset contains open RNA-Seq Gene Expression Quantification data and controlled WGS/WXS/RNA-Seq Aligned Reads, WXS Annotated Somatic Mutation, WXS Raw Somatic Mutation, and RNA-Seq Splice Junction Quantification. Documentation\nAWS CLI Access (No AWS account required)\naws s3 ls s3://gdc-organoid-pancreatic-phs001611-2-open/ --no-sign-request\nAfrica Soil Information Service (AfSIS) Soil Chemistry\nThis dataset contains soil infrared spectral data and paired soil property reference measurements for georeferenced soil samples that were collected through the Africa Soil Information Service (AfSIS) project, which lasted from 2009 through 2018. Documentation\nAWS CLI Access (No AWS account required)\naws s3 ls s3://afsis/ --no-sign-request\nDataset for Affective States in E-Environments\nDAiSEE is the first multi-label video classification dataset comprising of 9068 video snippets captured from 112 users for recognizing the user affective states of boredom, confusion, engagement, and frustration “in the wild”. The dataset has four levels of labels namely – very low, low, high, and very high for each of the affective states, which are crowd annotated and correlated with a gold standard annotation created using a team of expert psychologists. Download it here.\nNatureServe Explorer Dataset\nNatureServe Explorer provides conservation status, taxonomy, distribution, and life history information for more than 95,000 plants and animals in the United States and Canada, and more than 10,000 vegetation communities and ecological systems in the Western Hemisphere.\nThe data available through NatureServe Explorer represents data managed in the NatureServe Central Databases. These databases are dynamic, being continually enhanced and refined through the input of hundreds of natural heritage program scientists and other collaborators. NatureServe Explorer is updated from these central databases to reflect information from new field surveys, the latest taxonomic treatments and other scientific publications, and new conservation status assessments. Explore Data here\nFlight Records in the US\nAirline On-Time Performance and Causes of Flight Delays – On_Time Data.\nThis database contains scheduled and actual departure and arrival times, reason of delay. reported by certified U.S. air carriers that account for at least one percent of domestic scheduled passenger revenues. The data is collected by the Office of Airline Information, Bureau of Transportation Statistics (BTS).\nFlightAware.com has data but you need to pay for a full dataset.\nanyflights package supplies a set of functions to generate air travel data (and data packages!) similar to\nnycflights13. With a user-defined year and airport, the\nanyflights function will grab data on:\nflights: all flights that departed a given airport in a given year and month\nweather: hourly meterological data for a given airport in a given year and month\nairports: airport names, FAA codes, and locations\nairlines: translation between two letter carrier (airline) codes and names\nplanes: construction information about each plane found in\nAirline On-Time Statistics and Delay Causes\nThe U.S. Department of Transportation’s (DOT) Bureau of Transportation Statistics (BTS) tracks the on-time performance of domestic flights operated by large air carriers. Summary information on the number of on-time, delayed, canceled and diverted flights appears in DOT’s monthly Air Travel Consumer Report, published about 30 days after the month’s end, as well as in summary tables posted on this website. BTS began collecting details on the causes of flight delays in June 2003. Summary statistics and raw data are made available to the public at the time the Air Travel Consumer Report is released. Access it here\nWorldwide flight data\nOpen flights: As of January 2017, the OpenFlights Airports Database contains over 10,000 airports, train stations and ferry terminals spanning the globe\nDownload: airports.dat (Airports only, high quality)\nDownload: airports-extended.dat (Airports, train stations and ferry terminals, including user contributions)\nFlightera.net seems to have a lot of good data for free. It has in-depth data on flights and doesn’t seem limited by date. I can’t speak on the validity of the data though.\nflightradar24.com has lots of data, also historically, they might be willing to help you get it in a nice format.\n2019 Crime statistics in the USA\nDataset with arrest in US by race and separate states. Download Excel here\nYahoo Answers DataSets\nYahoo is shutting down in 2021. This is Yahoo Answers datasets (300MB gzip) that is fairly extensive from 2015 with about 1.4m rows. This dataset has the best questions answers, I mean all the answers, including the most insane awful answers and the worst questions people put together. Download it here.\nAnother option here: According to the tracker, there are 77M done, 20M out(?), and 40M to go:\nHistory of America 1400-2021\nPersian words phonetics dataset\nThis is a dataset of about 55K Persian words with their phonetics. Each word is in a line and separated from its phonetic by a tab.\nHistorical Air Quality Dataset\nAir Quality Data Collected at Outdoor Monitors Across the US. This is a BigQuery Dataset. There are no files to download, but you can query it through Kernels using the BigQuery API. The AQS Data Mart is a database containing all of the information from AQS. It has every measured value the EPA has collected via the national ambient air monitoring program. It also includes the associated aggregate values calculated by EPA (8-hour, daily, annual, etc.). The AQS Data Mart is a copy of AQS made once per week and made accessible to the public through web-based applications. The intended users of the Data Mart are air quality data analysts in the regulatory, academic, and health research communities. It is intended for those who need to download large volumes of detailed technical data stored at EPA and does not provide any interactive analytical tools. It serves as the back-end database for several Agency interactive tools that could not fully function without it: AirData, AirCompare, The Remote Sensing Information Gateway, the Map Monitoring Sites KML page, etc.\nStack Exchange Dataset\nAwesome Public Datasets\nThis list of a topic-centric public data sources in high quality. They are collected and tidied from blogs, answers, and user responses. Most of the data sets listed below are free, however, some are not.\n- The global dataset of historical yields for major crops 1981–2016 – The […]\n- Hyperspectral benchmark dataset on soil moisture – This dataset was […]\n- Lemons quality control dataset – Lemon dataset has been prepared to […]\n- Optimized Soil Adjusted Vegetation Index – The IDB is a tool for working […]\n- U.S. Department of Agriculture’s Nutrient Database\n- U.S. Department of Agriculture’s PLANTS Database – The Complete PLANTS […]\n- 1000 Genomes – The 1000 Genomes Project ran between 2008 and 2015, […]\n- American Gut (Microbiome Project) – The American Gut project is the […]\n- Broad Bioimage Benchmark Collection (BBBC) – The Broad Bioimage Benchmark […]\n- Broad Cancer Cell Line Encyclopedia (CCLE)\n- Cell Image Library – This library is a public and easily accessible […]\n- Complete Genomics Public Data – A diverse data set of whole human genomes […]\n- EBI ArrayExpress – ArrayExpress Archive of Functional Genomics Data […]\n- EBI Protein Data Bank in Europe – The Electron Microscopy Data Bank […]\n- ENCODE project – The Encyclopedia of DNA Elements (ENCODE) Consortium is […]\n- Electron Microscopy Pilot Image Archive (EMPIAR) – EMPIAR, the Electron […]\n- Ensembl Genomes\n- Gene Expression Omnibus (GEO) – GEO is a public functional genomics data […]\n- Gene Ontology (GO) – GO annotation files\n- Global Biotic Interactions (GloBI)\n- Harvard Medical School (HMS) LINCS Project – The Harvard Medical School […]\n- Human Genome Diversity Project – A group of scientists at Stanford […]\n- Human Microbiome Project (HMP) – The HMP sequenced over 2000 reference […]\n- ICOS PSP Benchmark – The ICOS PSP benchmarks repository contains an […]\n- International HapMap Project\n- Journal of Cell Biology DataViewer [fixme]\n- KEGG – KEGG is a database resource for understanding high-level functions […]\n- MIT Cancer Genomics Data\n- NCBI Proteins\n- NCBI Taxonomy – The NCBI Taxonomy database is a curated set of names and […]\n- NCI Genomic Data Commons – The GDC Data Portal is a robust data-driven […]\n- OpenSNP genotypes data – openSNP allows customers of direct-to-customer […]\n- Palmer Penguins – The goal of palmerpenguins is to provide a great […]\n- Pathguid – Protein-Protein Interactions Catalog\n- Protein Data Bank – This resource is powered by the Protein Data Bank […]\n- Psychiatric Genomics Consortium – The purpose of the Psychiatric Genomics […]\n- PubChem Project – PubChem is the world’s largest collection of freely […]\n- PubGene (now Coremine Medical) – COREMINE™ is a family of tools developed […]\n- Sanger Catalogue of Somatic Mutations in Cancer (COSMIC) – COSMIC, the […]\n- Sanger Genomics of Drug Sensitivity in Cancer Project (GDSC)\n- Sequence Read Archive(SRA) – The Sequence Read Archive (SRA) stores raw […]\n- Stanford Microarray Data\n- Stowers Institute Original Data Repository\n- Systems Science of Biological Dynamics (SSBD) Database – Systems Science […]\n- The Cancer Genome Atlas (TCGA), available via Broad GDAC\n- The Catalogue of Life – The Catalogue of Life is a quality-assured […]\n- The Personal Genome Project – The Personal Genome Project, initiated in […]\n- UCSC Public Data\n- UniGene\n- Universal Protein Resource (UnitProt) – The Universal Protein Resource […]\n- Rfam – The Rfam database is a collection of RNA families, each […]\nClimate and Climate and Weather\n- Actuaries Climate Index\n- Australian Weather\n- Aviation Weather Center – Consistent, timely and accurate weather […]\n- Brazilian Weather – Historical data (In Portuguese) – Data related to […]\n- Canadian Meteorological Centre\n- Climate Data from UEA (updated monthly)\n- Dutch Weather – The KNMI Data Center (KDC) portal provides access to KNMI […]\n- European Climate Assessment & Dataset\n- German Climate Data Center\n- Global Climate Data Since 1929\n- Charting The Global Climate Change News Narrative 2009-2020 – These four […]\n- NASA Global Imagery Browse Services\n- NOAA Bering Sea Climate [fixme]\n- NOAA Climate Datasets\n- NOAA Realtime Weather Models\n- NOAA SURFRAD Meteorology and Radiation Datasets\n- The World Bank Open Data Resources for Climate Change\n- UEA Climatic Research Unit\n- WU Historical Weather Worldwide\n- Wahington Post Climate Change – To analyze warming temperatures in the […]\n- WorldClim – Global Climate Data\nComplex Complex Network\n- AMiner Citation Network Dataset\n- CrossRef DOI URLs\n- DBLP Citation dataset\n- DIMACS Road Networks Collection\n- NBER Patent Citations\n- NIST complex networks data collection\n- Network Repository with Interactive Exploratory Analysis Tools [fixme]\n- Protein-protein interaction network\n- PyPI and Maven Dependency Network\n- Scopus Citation Database\n- Small Network Data\n- Stanford GraphBase\n- Stanford Large Network Dataset Collection\n- Stanford Longitudinal Network Data Sources [fixme]\n- The Koblenz Network Collection\n- The Laboratory for Web Algorithmics (UNIMI)\n- UCI Network Data Repository\n- UFL sparse matrix collection\n- WSU Graph Database [fixme]\n- Community Resource for Archiving Wireless Data At Dartmouth – Contains […]\nComputer Network\n- 3.5B Web Pages from CommonCrawl 2012\n- 53.5B Web clicks of 100K users in Indiana Univ.\n- CAIDA Internet Datasets\n- CRAWDAD Wireless datasets from Dartmouth Univ. [fixme]\n- ClueWeb09 – 1B web pages\n- ClueWeb12 – 733M web pages\n- CommonCrawl Web Data over 7 years\n- Criteo click-through data\n- Internet-Wide Scan Data Repository\n- MIRAGE-2019 – MIRAGE-2019 is a human-generated dataset for mobile traffic […]\n- OONI: Open Observatory of Network Interference – Internet censorship data\n- Open Mobile Data by MobiPerf\n- The Peer-to-Peer Trace Archive – Real-world measurements play a key role […]\n- Rapid7 Sonar Internet Scans\n- UCSD Network Telescope, IPv4 /8 net\n- CCCS-CIC-AndMal-2020 – The dataset includes 200K benign and 200K malware […]\n- Traffic and Log Data Captured During a Cyber Defense Exercise – This […]\nData Challenges\n- Bruteforce Database\n- Challenges in Machine Learning\n- CrowdANALYTIX dataX [fixme]\n- D4D Challenge of Orange [fixme]\n- DrivenData Competitions for Social Good\n- ICWSM Data Challenge (since 2009)\n- KDD Cup by Tencent 2012\n- Kaggle Competition Data\n- Localytics Data Visualization Challenge\n- Netflix Prize\n- Space Apps Challenge\n- Telecom Italia Big Data Challenge [fixme]\n- TravisTorrent Dataset – MSR’2017 Mining Challenge\n- TunedIT – Data mining & machine learning data sets, algorithms, challenges [fixme]\n- Yelp Dataset Challenge [fixme]\nEarth Science Datasets\n- 38-Cloud (Cloud Detection) – Contains 38 Landsat 8 scene images and their […]\n- AQUASTAT – Global water resources and uses\n- BODC – marine data of ~22K vars\n- EOSDIS – NASA’s earth observing system data\n- Earth Models [fixme]\n- Global Wind Atlas – The Global Wind Atlas is a free, web-based […]\n- Integrated Marine Observing System (IMOS) – roughly 30TB of ocean measurements\n- Marinexplore – Open Oceanographic Data\n- Alabama Real-Time Coastal Observing System\n- National Estuarine Research Reserves System-Wide Monitoring Program – […]\n- Oil and Gas Authority Open Data – The dataset covers 12,500 offshore […]\n- Smithsonian Institution Global Volcano and Eruption Database\n- USGS Earthquake Archives\nEconomics Datasets\n- American Economic Association (AEA)\n- EconData from UMD\n- Economic Freedom of the World Data\n- Historical MacroEconomic Statistics\n- INFORUM – Interindustry Forecasting at the University of Maryland\n- DBnomics – the world’s economic database – Aggregates hundreds of […]\n- International Trade Statistics\n- Internet Product Code Database\n- Joint External Debt Data Hub\n- Jon Haveman International Trade Data Links\n- Long-Term Productivity Database – The Long-Term Productivity database was […]\n- OpenCorporates Database of Companies in the World\n- Our World in Data\n- SciencesPo World Trade Gravity Datasets [fixme]\n- The Atlas of Economic Complexity\n- The Center for International Data\n- The Observatory of Economic Complexity [fixme]\n- UN Commodity Trade Statistics\n- UN Human Development Reports\nEducation Datasets\n- College Scorecard Data\n- New York State Education Department Data – The New York State Education […]\n- Student Data from Free Code Camp\nEnergy Datasets\n- AMPds – The Almanac of Minutely Power dataset\n- BLUEd – Building-Level fully labeled Electricity Disaggregation dataset\n- DBFC – Direct Borohydride Fuel Cell (DBFC) Dataset\n- DEL – Domestic Electrical Load study datasets for South Africa (1994 – 2014)\n- ECO – The ECO data set is a comprehensive data set for non-intrusive load […]\n- Global Power Plant Database – The Global Power Plant Database is a […]\n- HES – Household Electricity Study, UK\n- PEM1 – Proton Exchange Membrane (PEM) Fuel Cell Dataset\n- PLAID – The Plug Load Appliance Identification Dataset [fixme]\n- The Public Utility Data Liberation Project (PUDL) – PUDL makes US energy […]\n- SYND – A synthetic energy dataset for non-intrusive load monitoring – […]\n- Smart Meter Data Portal – The Smart Meter Data Portal is part of the […]\n- Tracebase\n- Ukraine Energy Centre Datasets\n- UK-DALE – UK Domestic Appliance-Level Electricity\n- iAWE\nEntertainment Datasets\nFinance Datasets\n- BIS Statistics – BIS statistics, compiled in cooperation with central […]\n- Blockmodo Coin Registry – A registry of JSON formatted information files […]\n- CBOE Futures Exchange\n- Complete FAANG Stock data – This data set contains all the stock data of […]\n- Google Finance\n- Google Trends\n- NASDAQ [fixme]\n- OSU Financial data [fixme]\n- Quandl\n- St Louis Federal\n- Yahoo Finance\nGIS Datasets\n- Awesome 3D Semantic City Models – Collection of open 3D semantic city and […]\n- ArcGIS Open Data portal\n- Cambridge, MA, US, GIS data on GitHub\n- Database of all continents, countries, States/Subdivisions/Provinces and […]\n- Factual Global Location Data\n- IEEE Geoscience and Remote Sensing Society DASE Website\n- Geo Maps – High Quality GeoJSON maps programmatically generated\n- Geo Spatial Data from ASU\n- Geo Wiki Project – Citizen-driven Environmental Monitoring\n- GeoFabrik – OSM data extracted to a variety of formats and areas\n- GeoNames Worldwide\n- Global Administrative Areas Database (GADM) – Geospatial data organized […]\n- Homeland Infrastructure Foundation-Level Data\n- Landsat 8 on AWS\n- List of all countries in all languages\n- National Weather Service GIS Data Portal\n- Natural Earth – vectors and rasters of the world [fixme]\n- OpenAddresses\n- OpenStreetMap (OSM)\n- Pleiades – Gazetteer and graph of ancient places\n- Reverse Geocoder using OSM data\n- Robin Wilson – Free GIS Datasets\n- TIGER/Line – U.S. boundaries and roads\n- TZ Timezones shapefile\n- TwoFishes – Foursquare’s coarse geocoder\n- UN Environmental Data\n- World boundaries from the U.S. Department of State\n- World countries in multiple formats\nGovernment Datasets\n- Alberta, Province of Canada\n- Antwerp, Belgium\n- Argentina (non official) [fixme]\n- Datos Argentina – Portal de datos abiertos de la República Argentina. […]\n- Austin, TX, US\n- Australia (abs.gov.au)\n- Australia (data.gov.au)\n- Austria (data.gv.at)\n- Baton Rouge, LA, US\n- Beersheba, Israel – Open Data Portal (Smart7 OpenData)\n- Belgium\n- City of Berkeley Open Data\n- Brazil\n- Buenos Aires, Argentina\n- Calgary, AB, Canada\n- Cambridge, MA, US\n- Canada\n- Chicago\n- Chile\n- China [fixme]\n- Dallas Open Data\n- DataBC – data from the Province of British Columbia\n- Debt to the Penny – The Debt to the Penny dataset provides information […]\n- Denver Open Data\n- Durham, NC Open Data\n- Edmonton, AB, Canada\n- England LGInform\n- EuroStat\n- EveryPolitician – Ongoing project collating and sharing data on every […]\n- Federal Committee on Statistical Methodology (FCSM) (formerly FedStats)\n- Finland\n- France\n- Fredericton, NB, Canada\n- Gatineau, QC, Canada\n- Germany\n- Ghent, Belgium\n- Glasgow, Scotland, UK [fixme]\n- Greece\n- Guardian world governments\n- Halifax, NS, Canada\n- Helsinki Region, Finland\n- Hong Kong, China\n- Houston, TX, US [fixme]\n- Indian Government Data\n- Indonesian Data Portal\n- Iowa – Welcome to the State of Iowa’s data portal. Please explore data […]\n- Ireland’s Open Data Portal\n- Israel’s Open Data Portal\n- Istanbul Municipality Open Data Portal\n- Italy – Il Portale dati.gov.it è il catalogo nazionale dei metadati […]\n- Jail deaths in America – The U.S. government does not release jail by […]\n- Japan\n- Laval, QC, Canada\n- Lexington, KY\n- London Datastore, UK\n- London, ON, Canada [fixme]\n- Los Angeles Open Data\n- Luxembourg – Luxembourgish Open Data Portal\n- MassGIS, Massachusetts, U.S.\n- Metropolitan Transportation Commission (MTC), California, US\n- Mexico [fixme]\n- Mississauga, ON, Canada\n- Moldova\n- Moncton, NB, Canada\n- Montreal, QC, Canada\n- Mountain View, California, US (GIS)\n- NYC Open Data [fixme]\n- NYC betanyc\n- Netherlands\n- New York Department of Sanitation Monthly Tonnage – DSNY Monthly Tonnage […]\n- New Zealand\n- Oakland, California, US [fixme]\n- Oklahoma\n- Open Data for Africa\n- Open Government Data (OGD) Platform India\n- OpenDataSoft’s list of 1,600 open data\n- Oregon\n- Ottawa, ON, Canada\n- Palo Alto, California, US\n- OpenDataPhilly – OpenDataPhilly is a catalog of open data in the […]\n- Portland, Oregon\n- Portugal – Pordata organization\n- Puerto Rico Government\n- Quebec City, QC, Canada [fixme]\n- Quebec Province of Canada\n- Regina SK, Canada\n- Rio de Janeiro, Brazil\n- Romania\n- Russia [fixme]\n- San Diego, CA\n- San Antonio, TX – Community Information Now – CI:Now is a nonprofit […] [fixme]\n- San Francisco Data sets\n- San Jose, California, US\n- San Mateo County, California, US\n- Saskatchewan, Province of Canada\n- Seattle\n- Singapore Government Data\n- South Africa Trade Statistics\n- South Africa\n- State of Utah, US\n- Switzerland\n- Taiwan gov\n- Taiwan\n- Tel-Aviv Open Data\n- Texas Open Data\n- The World Bank [fixme]\n- Toronto, ON, Canada [fixme]\n- Tunisia [fixme]\n- U.K. Government Data\n- U.S. American Community Survey\n- U.S. CDC Public Health datasets\n- U.S. Census Bureau\n- U.S. Department of Housing and Urban Development (HUD)\n- U.S. Federal Government Agencies\n- U.S. Federal Government Data Catalog\n- U.S. Food and Drug Administration (FDA)\n- U.S. National Center for Education Statistics (NCES)\n- U.S. Open Government\n- UK 2011 Census Open Atlas Project\n- US Counties – This is a repository of various data, broken down by US […]\n- U.S. Patent and Trademark Office (USPTO) Bulk Data Products\n- Uganda Bureau of Statistics [fixme]\n- Ukraine\n- United Nations\n- Uruguay\n- Valley Transportation Authority (VTA), California, US\n- Vancouver, BC Open Data Catalog [fixme]\n- Victoria, BC, Canada\n- Vienna, Austria\n- Statistics from the General Statistics Office of Vietnam – Data in […] [fixme]\n- U.S. Congressional Research Service (CRS) Reports\nHealthcare Datasets\n- AWS COVID-19 Datasets – We’re working with organizations who make […]\n- COVID-19 Case Surveillance Public Use Data – The COVID-19 case […]\n- 2019 Novel Coronavirus COVID-19 Data Repository by Johns Hopkins CSSE – […]\n- Coronavirus (Covid-19) Data in the United States – The New York Times is […]\n- COVID-19 Reported Patient Impact and Hospital Capacity by Facility – The […]\n- Composition of Foods Raw, Processed, Prepared USDA National Nutrient Database for Standard […]\n- The COVID Tracking Project – The COVID Tracking Project collects and […]\n- EHDP Large Health Data Sets\n- GDC – GDC supports several cancer genome programs for CCG, TCGA, TARGET etc.\n- Gapminder World demographic databases\n- MeSH, the vocabulary thesaurus used for indexing articles for PubMed\n- MeDAL – A large medical text dataset curated for abbreviation […]\n- Medicare Coverage Database (MCD), U.S.\n- Medicare Data Engine of medicare.gov Data\n- Medicare Data File\n- Number of Ebola Cases and Deaths in Affected Countries (2014)\n- Open-ODS (structure of the UK NHS)\n- OpenPaymentsData, Healthcare financial relationship data\n- PhysioBank Databases – A large and growing archive of physiological data.\n- The Cancer Imaging Archive (TCIA)\n- The Cancer Genome Atlas project (TCGA)\n- World Health Organization Global Health Observatory\n- Yahoo Knowledge Graph COVID-19 Datasets – The Yahoo Knowledge Graph team […]\n- Informatics for Integrating Biology & the Bedside [fixme]\nImage Processing Datasets\n- 10k US Adult Faces Database\n- 2GB of Photos of Cats\n- Audience Unfiltered faces for gender and age classification\n- Affective Image Classification\n- Animals with attributes\n- CADDY Underwater Stereo-Vision Dataset of divers’ hand gestures – […]\n- Cytology Dataset – CCAgT: Images of Cervical Cells with AgNOR Stain […]\n- Caltech Pedestrian Detection Benchmark\n- Chars74K dataset – Character Recognition in Natural Images (both English […]\n- Cube++ – 4890 raw 18-megapixel images, each containing a SpyderCube color […]\n- Danbooru Tagged Anime Illustration Dataset – A large-scale anime image […]\n- DukeMTMC Data Set – DukeMTMC aims to accelerate advances in multi-target […] [fixme]\n- ETH Entomological Collection (ETHEC) Fine Grained Butterfly (Lepidoptra) Images\n- Face Recognition Benchmark\n- Flickr: 32 Class Brand Logos [fixme]\n- GDXray – X-ray images for X-ray testing and Computer Vision\n- HumanEva Dataset – The HumanEva-I dataset contains 7 calibrated video […]\n- ImageNet (in WordNet hierarchy)\n- Indoor Scene Recognition\n- International Affective Picture System, UFL\n- KITTI Vision Benchmark Suite\n- Labeled Information Library of Alexandria – Biology and Conservation – […]\n- MNIST database of handwritten digits, near 1 million examples [fixme]\n- Multi-View Region of Interest Prediction Dataset for Autonomous Driving – […]\n- Massive Visual Memory Stimuli, MIT\n- Newspaper Navigator – This dataset consists of extracted visual content […]\n- Open Images From Google – Pictures with segmentation masks for 2.8 […]\n- RuFa – Contains images of text written in one of two Arabic fonts (Ruqaa […]\n- SUN database, MIT\n- SVIRO Synthetic Vehicle Interior Rear Seat Occupancy – 25.000 synthetic […]\n- Several Shape-from-Silhouette Datasets [fixme]\n- Stanford Dogs Dataset\n- The Action Similarity Labeling (ASLAN) Challenge\n- The Oxford-IIIT Pet Dataset\n- Violent-Flows – Crowd Violence / Non-violence Database and benchmark\n- Visual genome\n- YouTube Faces Database\nMachine Learning Datasets\n- All-Age-Faces Dataset – Contains 13’322 Asian face images distributed […]\n- Audi Autonomous Driving Dataset – We have published the Audi Autonomous […]\n- Context-aware data sets from five domains\n- Delve Datasets for classification and regression\n- Discogs Monthly Data\n- Free Music Archive\n- IMDb Database\n- Iranis – A Large-scale Dataset of Farsi/Arabic License Plate Characters\n- Keel Repository for classification, regression and time series\n- Labeled Faces in the Wild (LFW)\n- Lending Club Loan Data\n- Machine Learning Data Set Repository [fixme]\n- Million Song Dataset\n- More Song Datasets\n- MovieLens Data Sets\n- New Yorker caption contest ratings\n- RDataMining – “R and Data Mining” ebook data\n- Registered Meteorites on Earth [fixme]\n- Restaurants Health Score Data in San Francisco\n- TikTok Dataset – More than 300 dance videos that capture a single person […]\n- UCI Machine Learning Repository\n- Yahoo! Ratings and Classification Data\n- YouTube-BoundingBoxes\n- Youtube 8m\n- eBay Online Auctions (2012)\nMuseums Datasets\n- Canada Science and Technology Museums Corporation’s Open Data\n- Cooper-Hewitt’s Collection Database\n- Metropolitan Museum of Art Collection API\n- Minneapolis Institute of Arts metadata\n- Natural History Museum (London) Data Portal\n- Rijksmuseum Historical Art Collection\n- Tate Collection metadata\n- The Getty vocabularies\nNatural Language Datasets\n- Automatic Keyphrase Extraction\n- The Big Bad NLP Database\n- Blizzard Challenge Speech – The speech + text data comes from […]\n- Blogger Corpus\n- CLiPS Stylometry Investigation Corpus [fixme]\n- ClueWeb09 FACC\n- ClueWeb12 FACC\n- DBpedia – 4.58M things with 583M facts\n- Dirty Words – With millions of images in our library and billions of […]\n- Flickr Personal Taxonomies\n- Freebase of people, places, and things [fixme]\n- German Political Speeches Corpus – Collection of political speeches from […]\n- Google Books Ngrams (2.2TB)\n- Google MC-AFP – Generated based on the public available Gigaword dataset […]\n- Google Web 5gram (1TB, 2006)\n- Gutenberg eBooks List [fixme]\n- Hansards text chunks of Canadian Parliament\n- LJ Speech – Speech dataset consisting of 13,100 short audio clips of a […]\n- M-AILabs Speech – The M-AILABS Speech Dataset is the first large dataset […] [fixme]\n- Microsoft MAchine Reading COmprehension Dataset (or MS MARCO)\n- Machine Comprehension Test (MCTest) of text from Microsoft Research\n- Machine Translation of European languages\n- Making Sense of Microposts 2013 – Concept Extraction [fixme]\n- Making Sense of Microposts 2016 – Named Entity rEcognition and Linking\n- Multi-Domain Sentiment Dataset (version 2.0)\n- Noisy speech database for training speech enhancement algorithms and TTS […] [fixme]\n- Open Multilingual Wordnet\n- POS/NER/Chunk annotated data\n- Personae Corpus [fixme]\n- SMS Spam Collection in English\n- SaudiNewsNet Collection of Saudi Newspaper Articles (Arabic, 30K articles)\n- Stanford Question Answering Dataset (SQuAD)\n- USENET postings corpus of 2005~2011\n- Universal Dependencies\n- Webhose – News/Blogs in multiple languages\n- Wikidata – Wikipedia databases\n- Wikipedia Links data – 40 Million Entities in Context\n- WordNet databases and tools\n- WorldTree Corpus of Explanation Graphs for Elementary Science Questions – […]\nNeuroscience Datasets\n- Allen Institute Datasets\n- Brain Catalogue\n- Brainomics\n- CodeNeuro Datasets [fixme]\n- Collaborative Research in Computational Neuroscience (CRCNS)\n- Human Connectome Project\n- NIMH Data Archive\n- NeuroData\n- NeuroMorpho – NeuroMorpho.Org is a centrally curated inventory of […]\n- Neuroelectro\n- OpenNEURO\n- OpenfMRI\n- Study Forrest\nPhysics Datasets\n- CERN Open Data Portal\n- Crystallography Open Database\n- IceCube – South Pole Neutrino Observatory\n- Ligo Open Science Center (LOSC) – Gravitational wave data from the LIGO […]\n- NASA Exoplanet Archive\n- NSSDC (NASA) data of 550 space spacecraft\n- Sloan Digital Sky Survey (SDSS) – Mapping the Universe\nProstate Cancer Datasets\n- EOPC-DE-Early-Onset-Prostate-Cancer-Germany – Early Onset Prostate Cancer […]\n- GENIE – Data from the Genomics Evidence Neoplasia Information Exchange […]\n- Genomic-Hallmarks-Prostate-Adenocarcinoma-CPC-GENE – Comprehensive […]\n- MSK-IMPACT-Clinical-Sequencing-Cohort-MSKCC-Prostate-Cancer – Targeted […]\n- Metastatic-Prostate-Adenocarcinoma-MCTP – Comprehensive profiling of 61 […]\n- Metastatic-Prostate-Cancer-SU2CPCF-Dream-Team – Comprehensive analysis of […]\n- NPCR-2001-2015 – Database from CDC’s National Program of Cancer […]\n- NPCR-2005-2015 – Database from CDC’s National Program of Cancer […]\n- NaF-Prostate – NaF Prostate is a collection of F-18 NaF positron emission […]\n- Neuroendocrine-Prostate-Cancer – Whole exome and RNA Seq data of […]\n- PLCO-Prostate-Diagnostic-Procedures – The Prostate Diagnostic Procedures […]\n- PLCO-Prostate-Medical-Complications – The Prostate Medical Complications […]\n- PLCO-Prostate-Screening-Abnormalities – The Prostate Screening […]\n- PLCO-Prostate-Screening – The Prostate Screening dataset (177,315 […]\n- PLCO-Prostate-Treatments – The Prostate Treatments dataset (13,409 […]\n- PLCO-Prostate – The Prostate dataset is a comprehensive dataset that […]\n- PRAD-CA-Prostate-Adenocarcinoma-Canada – Prostate Adenocarcinoma – […]\n- PRAD-FR-Prostate-Adenocarcinoma-France – Prostate Adenocarcinoma – […]\n- PRAD-UK-Prostate-Adenocarcinoma-United-Kingdom – Prostate Adenocarcinoma […]\n- PROSTATEx-Challenge – Retrospective set of prostate MR studies. All […]\n- Prostate-3T – The Prostate-3T project provided imaging data to TCIA as […]\n- Prostate-Adenocarcinoma-Broad-Cornell-2012 – Comprehensive profiling of […]\n- Prostate-Adenocarcinoma-Broad-Cornell-2013 – Comprehensive profiling of […]\n- Prostate-Adenocarcinoma-CNA-study-MSKCC – Copy-number profiling of 103 […]\n- Prostate-Adenocarcinoma-Fred-Hutchinson-CRC – Comprehensive profiling of […]\n- Prostate Adenocarcinoma (MSKCC/DFCI) – Whole Exome Sequencing of 1013 […]\n- Prostate-Adenocarcinoma-MSKCC – MSKCC Prostate Oncogenome Project. 181 […]\n- Prostate-Adenocarcinoma-Organoids-MSKCC – Exome profiling of prostate […]\n- Prostate-Adenocarcinoma-Sun-Lab – Whole-genome and Transcriptome […]\n- Prostate-Adenocarcinoma-TCGA-PanCancer-Atlas – Comprehensive TCGA […]\n- Prostate-Adenocarcinoma-TCGA – Integrated profiling of 333 primary […]\n- Prostate-Diagnosis – PCa T1- and T2-weighted magnetic resonance images […]\n- Prostate-Fused-MRI-Pathology – The Prostate Fused-MRI-Pathology […]\n- Prostate-MRI – The Prostate-MRI collection of prostate Magnetic Resonance […]\n- Prostate-R – The R package ‘ElemStatLearn’ contains a prostate cancer […]\n- QIN-PROSTATE-Repeatability – The QIN-PROSTATE-Repeatability dataset is a […]\n- QIN-PROSTATE – The QIN PROSTATE collection of the Quantitative Imaging […]\n- SEER-YR1973_2015.SEER9 – The SEER November 2017 Research Data files from […]\n- SEER-YR1992_2015.SJ_LA_RG_AK – The SEER November 2017 Research Data files […]\n- SEER-YR2000_2015.CA_KY_LO_NJ_GA – The SEER November 2017 Research Data […]\n- SEER-YR2000_2015.CA_KY_LO_NJ_GA – The July – December 2005 diagnoses for […]\n- TCGA-PRAD-US – TCGA Prostate Adenocarcinoma (499 samples).\nPsychology and Cognition Datasets\nPublic Domains Datasets\n- Ably Open Realtime Data\n- Amazon\n- Archive.org Datasets\n- Archive-it from Internet Archive\n- CMU JASA data archive\n- CMU StatLab collections\n- Data.World\n- Data360 [fixme]\n- Enigma Public\n- Grand Comics Database – The Grand Comics Database (GCD) is a nonprofit, […]\n- Infochimps [fixme]\n- KDNuggets Data Collections\n- Microsoft Azure Data Market Free DataSets [fixme]\n- Microsoft Data Science for Research\n- Microsoft Research Open Data\n- Open Library Data Dumps\n- Reddit Datasets\n- RevolutionAnalytics Collection [fixme]\n- Sample R data sets\n- StatSci.org\n- Stats4Stem R data sets (archived)\n- The Washington Post List\n- UCLA SOCR data collection\n- UFO Reports\n- Wikileaks 911 pager intercepts\n- Yahoo Webscope\nSearch Engines Datasets\n- Academic Torrents of data sharing from UMB\n- Datahub.io\n- Domains Project – Sorted list of Internet domains\n- Harvard Dataverse Network of scientific data\n- Institute of Education Sciences\n- National Technical Reports Library\n- Open Data Certificates (beta)\n- OpenDataNetwork – A search engine of all Socrata powered data portals\n- Statista.com – statistics and Studies\n- Zenodo – An open dependable home for the long-tail of science\nSocial Networks Datasets\n- 2021 Portuguese Elections Twitter Dataset – 57M+ tweets, 1M+ users – This […]\n- 72 hours #gamergate Twitter Scrape\n- CMU Enron Email of 150 users\n- Cheng-Caverlee-Lee September 2009 – January 2010 Twitter Scrape\n- China Biographical Database – The China Biographical Database is a freely […]\n- A Twitter Dataset of 40+ million tweets related to COVID-19 – Due to the […]\n- 43k+ Donald Trump Twitter Screenshots – This archive contains screenshots […]\n- EDRM Enron EMail of 151 users, hosted on S3\n- Facebook Data Scrape (2005)\n- Facebook Social Connectedness Index – We use an anonymized snapshot of […]\n- Facebook Social Networks from LAW (since 2007)\n- Foursquare from UMN/Sarwat (2013)\n- GitHub Collaboration Archive\n- Google Scholar citation relations\n- High-Resolution Contact Networks from Wearable Sensors\n- Indie Map: social graph and crawl of top IndieWeb sites\n- Mobile Social Networks from UMASS\n- Network Twitter Data\n- Reddit Comments\n- Skytrax’ Air Travel Reviews Dataset\n- Social Twitter Data\n- SourceForge.net Research Data\n- Twitch Top Streamer’s Data\n- Twitter Data for Online Reputation Management\n- Twitter Data for Sentiment Analysis\n- Twitter Graph of entire Twitter site\n- Twitter Scrape Calufa May 2011 [fixme]\n- UNIMI/LAW Social Network Datasets\n- United States Congress Twitter Data – Daily datasets with tweets of 1100+ […]\n- Yahoo! Graph and Social Data\n- Youtube Video Social Graph in 2007,2008\nSocial Sciences Datasets\n- ACLED (Armed Conflict Location & Event Data Project)\n- Authoritarian Ruling Elites Database – The Authoritarian Ruling Elites […]\n- Canadian Legal Information Institute\n- Center for Systemic Peace Datasets – Conflict Trends, Polities, State Fragility, etc [fixme]\n- Correlates of War Project\n- Cryptome Conspiracy Theory Items\n- Datacards [fixme]\n- European Social Survey\n- FBI Hate Crime 2013 – aggregated data\n- Fragile States Index [fixme]\n- GDELT Global Events Database\n- General Social Survey (GSS) since 1972\n- German Social Survey\n- Global Religious Futures Project\n- Gun Violence Data – A comprehensive, accessible database that contains […]\n- Humanitarian Data Exchange\n- INFORM Index for Risk Management\n- Institute for Demographic Studies\n- International Networks Archive\n- International Social Survey Program ISSP\n- International Studies Compendium Project\n- James McGuire Cross National Data\n- MIT Reality Mining Dataset\n- MacroData Guide by Norsk samfunnsvitenskapelig datatjeneste\n- Mass Mobilization Data Project – The Mass Mobilization (MM) data are an […]\n- Microsoft Academic Knowledge Graph – The Microsoft Academic Knowledge […]\n- Minnesota Population Center\n- Notre Dame Global Adaptation Index (ND-GAIN)\n- Open Crime and Policing Data in England, Wales and Northern Ireland\n- OpenSanctions – A global database of persons and companies of political, […]\n- Paul Hensel General International Data Page\n- PewResearch Internet Survey Project\n- PewResearch Society Data Collection\n- Political Polarity Data [fixme]\n- StackExchange Data Explorer\n- Terrorism Research and Analysis Consortium\n- Texas Inmates Executed Since 1984\n- Titanic Survival Data Set\n- UCB’s Archive of Social Science Data (D-Lab) [fixme]\n- UCLA Social Sciences Data Archive\n- UN Civil Society Database\n- UPJOHN for Labor Employment Research\n- Universities Worldwide\n- Uppsala Conflict Data Program\n- World Bank Open Data\n- World Inequality Database – The World Inequality Database (WID.world) […]\n- WorldPop project – Worldwide human population distributions\nSoftware Datasets\n- FLOSSmole data about free, libre, and open source software development\n- GHTorrent – Scalable, queryable, offline mirror of data offered through […]\n- Libraries.io Open Source Repository and Dependency Metadata\n- Public Git Archive – a Big Code dataset for all – dataset of 182,014 top- […]\n- Code duplicates – 2k Java file and 600 Java function pairs labeled as […]\n- Commit messages – 1.3 billion GitHub commit messages till March 2019\n- Pull Request review comments – 25.3 million GitHub PR review comments […]\n- Source Code Identifiers – 41.7 million distinct splittable identifiers […]\nSports Datasets\n- American Ninja Warrior Obstacles – Contains every obstacle in the history […]\n- Betfair Historical Exchange Data\n- Cricsheet Matches (cricket)\n- Equity in Athletics – The Equity in Athletics Data Analysis Cutting Tool […]\n- Ergast Formula 1, from 1950 up to date (API)\n- Football/Soccer resources (data and APIs)\n- Lahman’s Baseball Database\n- NFL play-by-play data – NFL play-by-play data sourced from: […]\n- Pinhooker: Thoroughbred Bloodstock Sale Data\n- Pro Kabadi season 1 to 7 – Pro Kabadi League is a professional-level […]\n- Retrosheet Baseball Statistics\n- Tennis database of rankings, results, and stats for ATP\n- Tennis database of rankings, results, and stats for WTA\n- USA Soccer Teams and Locations – USA soccer teams and locations. MLS, […]\nTime Series Datasets\n- 3W dataset – To the best of its authors’ knowledge, this is the first […]\n- Databanks International Cross National Time Series Data Archive\n- Hard Drive Failure Rates\n- Heart Rate Time Series from MIT\n- Time Series Data Library (TSDL) from MU\n- Turing Change Point Dataset – Contains 42 annotated time series collected […]\n- UC Riverside Time Series Dataset\n- Airlines OD Data 1987-2008\n- Ford GoBike Data (formerly Bay Area Bike Share Data) [fixme]\n- Bike Share Systems (BSS) collection\n- Dutch Traffic Information\n- GeoLife GPS Trajectory from Microsoft Research\n- German train system by Deutsche Bahn\n- Hubway Million Rides in MA [fixme]\n- Montreal BIXI Bike Share\n- NYC Taxi Trip Data 2009-\n- NYC Taxi Trip Data 2013 (FOIA/FOILed)\n- NYC Uber trip data April 2014 to September 2014\n- Open Traffic collection\n- OpenFlights – airport, airline and route data\n- Philadelphia Bike Share Stations (JSON)\n- Plane Crash Database, since 1920\n- RITA Airline On-Time Performance data [fixme]\n- RITA/BTS transport data collection (TranStat) [fixme]\n- Renfe (Spanish National Railway Network) dataset\n- Toronto Bike Share Stations (JSON and GBFS files)\n- Transport for London (TFL)\n- Travel Tracker Survey (TTS) for Chicago [fixme]\n- U.S. Bureau of Transportation Statistics (BTS)\n- U.S. Domestic Flights 1990 to 2009\n- U.S. Freight Analysis Framework since 2007\neSports Datasets\n- CS:GO Competitive Matchmaking Data – In this data set we have data about […]\n- FIFA-2021 Complete Player Dataset\n- OpenDota data dump\nComplementary Collections\n- Data Packaged Core Datasets\n- Database of Scientific Code Contributions\n- A growing collection of public datasets: CoolDatasets.\n- DataWrangling: Some Datasets Available on the Web\n- Inside-r: Finding Data on the Internet\n- OpenDataMonitor: An overview of available open data resources in Europe\n- Quora: Where can I find large datasets open to the public?\n- RS.io: 100+ Interesting Data Sets for Statistics\n- StaTrek: Leveraging open data to understand urban lives\n- CV Papers: CV Datasets on the web\n- CVonline: Image Databases\nCategorized list of public datasets: Sindre Sorhus /awesome List\n- Node.js – Async non-blocking event-driven JavaScript runtime built on Chrome’s V8 JavaScript engine.\n- Cross-Platform – Writing cross-platform code on Node.js.\n- Frontend Development\n- iOS – Mobile operating system for Apple phones and tablets.\n- Android – Mobile operating system developed by Google.\n- IoT & Hybrid Apps\n- Electron – Cross-platform native desktop apps using JavaScript/HTML/CSS.\n- Cordova – JavaScript API for hybrid apps.\n- React Native – JavaScript framework for writing natively rendering mobile apps for iOS and Android.\n- Xamarin – Mobile app development IDE, testing, and distribution.\n- Linux\n- Containers\n- eBPF – Virtual machine that allows you to write more efficient and powerful tracing and monitoring for Linux systems.\n- Arch-based Projects – Linux distributions and projects based on Arch Linux.\n- macOS – Operating system for Apple’s Mac computers.\n- watchOS – Operating system for the Apple Watch.\n- Salesforce\n- Amazon Web Services\n- Windows\n- IPFS – P2P hypermedia protocol.\n- Fuse – Mobile development tools.\n- Heroku – Cloud platform as a service.\n- Raspberry Pi – Credit card-sized computer aimed at teaching kids programming, but capable of a lot more.\n- Qt – Cross-platform GUI app framework.\n- WebExtensions – Cross-browser extension system.\n- RubyMotion – Write cross-platform native apps for iOS, Android, macOS, tvOS, and watchOS in Ruby.\n- Smart TV – Create apps for different TV platforms.\n- GNOME – Simple and distraction-free desktop environment for Linux.\n- KDE – A free software community dedicated to creating an open and user-friendly computing experience.\n- Amazon Alexa – Virtual home assistant.\n- DigitalOcean – Cloud computing platform designed for developers.\n- Flutter – Google’s mobile SDK for building native iOS and Android apps from a single codebase written in Dart.\n- Home Assistant – Open source home automation that puts local control and privacy first.\n- IBM Cloud – Cloud platform for developers and companies.\n- Firebase – App development platform built on Google Cloud Platform.\n- Robot Operating System 2.0 – Set of software libraries and tools that help you build robot apps.\n- Adafruit IO – Visualize and store data from any device.\n- Cloudflare – CDN, DNS, DDoS protection, and security for your site.\n- Actions on Google – Developer platform for Google Assistant.\n- ESP – Low-cost microcontrollers with WiFi and broad IoT applications.\n- Deno – A secure runtime for JavaScript and TypeScript that uses V8 and is built in Rust.\n- DOS – Operating system for x86-based personal computers that was popular during the 1980s and early 1990s.\n- Nix – Package manager for Linux and other Unix systems that makes package management reliable and reproducible.\nProgramming Languages\n- JavaScript\n- Promises\n- Standard Style – Style guide and linter.\n- Must Watch Talks\n- Tips\n- Network Layer\n- Micro npm Packages\n- Mad Science npm Packages – Impossible sounding projects that exist.\n- Maintenance Modules – For npm packages.\n- npm – Package manager.\n- AVA – Test runner.\n- ESLint – Linter.\n- Functional Programming\n- Observables\n- npm scripts – Task runner.\n- 30 Seconds of Code – Code snippets you can understand in 30 seconds.\n- Ponyfills – Like polyfills but without overriding native APIs.\n- Swift – Apple’s compiled programming language that is secure, modern, programmer-friendly, and fast.\n- Python – General-purpose programming language designed for readability.\n- Asyncio – Asynchronous I/O in Python 3.\n- Scientific Audio – Scientific research in audio/music.\n- CircuitPython – A version of Python for microcontrollers.\n- Data Science – Data analysis and machine learning.\n- Typing – Optional static typing for Python.\n- MicroPython – A lean and efficient implementation of Python 3 for microcontrollers.\n- Rust\n- Haskell\n- PureScript\n- Go\n- Scala\n- Scala Native – Optimizing ahead-of-time compiler for Scala based on LLVM.\n- Ruby\n- Clojure\n- ClojureScript\n- Elixir\n- Elm\n- Erlang\n- Julia – High-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science.\n- Lua\n- C/C++ – General-purpose language with a bias toward system programming and embedded, resource-constrained software.\n- R – Functional programming language and environment for statistical computing and graphics.\n- Common Lisp – Powerful dynamic multiparadigm language that facilitates iterative and interactive development.\n- Perl\n- Groovy\n- Dart\n- Java – Popular secure object-oriented language designed for flexibility to “write once, run anywhere”.\n- Kotlin\n- OCaml\n- ColdFusion\n- Fortran\n- PHP – Server-side scripting language.\n- Composer – Package manager.\n- Pascal\n- AutoHotkey\n- AutoIt\n- Crystal\n- Frege – Haskell for the JVM.\n- CMake – Build, test, and package software.\n- ActionScript 3 – Object-oriented language targeting Adobe AIR.\n- Eta – Functional programming language for the JVM.\n- Idris – General purpose pure functional programming language with dependent types influenced by Haskell and ML.\n- Ada/SPARK – Modern programming language designed for large, long-lived apps where reliability and efficiency are essential.\n- Q# – Domain-specific programming language used for expressing quantum algorithms.\n- Imba – Programming language inspired by Ruby and Python and compiles to performant JavaScript.\n- Vala – Programming language designed to take full advantage of the GLib and GNOME ecosystems, while preserving the speed of C code.\n- Coq – Formal language and environment for programming and specification which facilitates interactive development of machine-checked proofs.\n- V – Simple, fast, safe, compiled language for developing maintainable software.\nFront-End Development\n- ES6 Tools\n- Web Performance Optimization\n- Web Tools\n- CSS – Style sheet language that specifies how HTML elements are displayed on screen.\n- React – App framework.\n- Relay – Framework for building data-driven React apps.\n- React Hooks – A new feature that lets you use state and other React features without writing a class.\n- Web Components\n- Polymer – JavaScript library to develop Web Components.\n- Angular – App framework.\n- Backbone – App framework.\n- HTML5 – Markup language used for websites & web apps.\n- SVG – XML-based vector image format.\n- Canvas\n- KnockoutJS – JavaScript library.\n- Dojo Toolkit – JavaScript toolkit.\n- Inspiration\n- Ember – App framework.\n- Android UI\n- iOS UI\n- Meteor\n- Flexbox\n- Web Typography\n- Web Accessibility\n- Material Design\n- D3 – Library for producing dynamic, interactive data visualizations.\n- Emails\n- jQuery – Easy to use JavaScript library for DOM manipulation.\n- Web Audio\n- Offline-First\n- Static Website Services\n- Cycle.js – Functional and reactive JavaScript framework.\n- Text Editing\n- Motion UI Design\n- Vue.js – App framework.\n- Marionette.js – App framework.\n- Aurelia – App framework.\n- Charting\n- Ionic Framework 2\n- Chrome DevTools\n- PostCSS – CSS tool.\n- Draft.js – Rich text editor framework for React.\n- Service Workers\n- Progressive Web Apps\n- choo – App framework.\n- Redux – State container for JavaScript apps.\n- webpack – Module bundler.\n- Browserify – Module bundler.\n- Sass – CSS preprocessor.\n- Ant Design – Enterprise-class UI design language.\n- Less – CSS preprocessor.\n- WebGL – JavaScript API for rendering 3D graphics.\n- Preact – App framework.\n- Progressive Enhancement\n- Next.js – Framework for server-rendered React apps.\n- lit-html – HTML templating library for JavaScript.\n- JAMstack – Modern web development architecture based on client-side JavaScript, reusable APIs, and prebuilt markup.\n- WordPress-Gatsby – Web development technology stack with WordPress as a back end and Gatsby as a front end.\n- Mobile Web Development – Creating a great mobile web experience.\n- Storybook – Development environment for UI components.\n- Blazor – .NET web framework using C#/Razor and HTML that runs in the browser with WebAssembly.\n- PageSpeed Metrics – Metrics to help understand page speed and user experience.\n- Tailwind CSS – Utility-first CSS framework for rapid UI development.\n- Seed – Rust framework for creating web apps running in WebAssembly.\n- Web Performance Budget – Techniques to ensure certain performance metrics for a website.\n- Yew – Rust framework inspired by Elm and React for creating multi-threaded frontend web apps with WebAssembly.\n- Material-UI – Material Design React components for faster and easier web development.\n- Building Blocks for Web Apps – Standalone features to be integrated into web apps.\n- Svelte – App framework.\n- Design systems – Collection of reusable components, guided by rules that ensure consistency and speed.\nBack-End Development\n- Flask – Python framework.\n- Docker\n- Vagrant – Automation virtual machine environment.\n- Pyramid – Python framework.\n- Play1 Framework\n- CakePHP – PHP framework.\n- Symfony – PHP framework.\n- Laravel – PHP framework.\n- Education\n- TALL Stack – Full-stack development solution featuring libraries built by the Laravel community.\n- Rails – Web app framework for Ruby.\n- Gems – Packages.\n- Phalcon – PHP framework.\n- Useful\n- nginx – Web server.\n- Dropwizard – Java framework.\n- Kubernetes – Open-source platform that automates Linux container operations.\n- Lumen – PHP micro-framework.\n- Serverless Framework – Serverless computing and serverless architectures.\n- Apache Wicket – Java web app framework.\n- Vert.x – Toolkit for building reactive apps on the JVM.\n- Terraform – Tool for building, changing, and versioning infrastructure.\n- Vapor – Server-side development in Swift.\n- Dash – Python web app framework.\n- FastAPI – Python web app framework.\n- CDK – Open-source software development framework for defining cloud infrastructure in code.\n- IAM – User accounts, authentication and authorization.\n- Chalice – Python framework for serverless app development on AWS Lambda.\nComputer Science\n- University Courses\n- Data Science\n- Machine Learning\n- Tutorials\n- ML with Ruby – Learning, implementing, and applying Machine Learning using Ruby.\n- Core ML Models – Models for Apple’s machine learning framework.\n- H3O – Open source distributed machine learning platform written in Java with APIs in R, Python, and Scala.\n- Software Engineering for Machine Learning – From experiment to production-level machine learning.\n- AI in Finance – Solving problems in finance with machine learning.\n- JAX – Automatic differentiation and XLA compilation brought together for high-performance machine learning research.\n- Speech and Natural Language Processing\n- Spanish\n- NLP with Ruby\n- Question Answering – The science of asking and answering in natural language with a machine.\n- Natural Language Generation – Generation of text used in data to text, conversational agents, and narrative generation applications.\n- Linguistics\n- Cryptography\n- Papers – Theory basics for using cryptography by non-cryptographers.\n- Computer Vision\n- Deep Learning – Neural networks.\n- TensorFlow – Library for machine intelligence.\n- TensorFlow.js – WebGL-accelerated machine learning JavaScript library for training and deploying models.\n- TensorFlow Lite – Framework that optimizes TensorFlow models for on-device machine learning.\n- Papers – The most cited deep learning papers.\n- Education\n- Deep Vision\n- Open Source Society University\n- Functional Programming\n- Empirical Software Engineering – Evidence-based research on software systems.\n- Static Analysis & Code Quality\n- Information Retrieval – Learn to develop your own search engine.\n- Quantum Computing – Computing which utilizes quantum mechanics and qubits on quantum computers.\nBig Data\n- Big Data\n- Public Datasets\n- Hadoop – Framework for distributed storage and processing of very large data sets.\n- Data Engineering\n- Streaming\n- Apache Spark – Unified engine for large-scale data processing.\n- Qlik – Business intelligence platform for data visualization, analytics, and reporting apps.\n- Splunk – Platform for searching, monitoring, and analyzing structured and unstructured machine-generated big data in real-time.\n- Papers We Love\n- Talks\n- Algorithms\n- Education – Learning and practicing.\n- Algorithm Visualizations\n- Artificial Intelligence\n- Search Engine Optimization\n- Competitive Programming\n- Math\n- Recursion Schemes – Traversing nested data structures.\n- Sublime Text\n- Vim\n- Emacs\n- Atom – Open-source and hackable text editor.\n- Visual Studio Code – Cross-platform open-source text editor.\n- Game Development\n- Game Talks\n- Godot – Game engine.\n- Open Source Games\n- Unity – Game engine.\n- Chess\n- LÖVE – Game engine.\n- PICO-8 – Fantasy console.\n- Game Boy Development\n- Construct 2 – Game engine.\n- Gideros – Game engine.\n- Minecraft – Sandbox video game.\n- Game Datasets – Materials and datasets for Artificial Intelligence in games.\n- Haxe Game Development – A high-level strongly typed programming language used to produce cross-platform native code.\n- libGDX – Java game framework.\n- PlayCanvas – Game engine.\n- Game Remakes – Actively maintained open-source game remakes.\n- Flame – Game engine for Flutter.\n- Discord Communities – Chat with friends and communities.\n- CHIP-8 – Virtual computer game machine from the 70s.\n- Games of Coding – Learn a programming language by making games.\nDevelopment Environment\n- Quick Look Plugins – For macOS.\n- Dev Env\n- Dotfiles\n- Shell\n- Fish – User-friendly shell.\n- Command-Line Apps\n- ZSH Plugins\n- GitHub – Hosting service for Git repositories.\n- Browser Extensions\n- Cheat Sheet\n- Pinned Gists – Dynamic pinned gists for your GitHub profile.\n- Git Cheat Sheet & Git Flow\n- Git Tips\n- Git Add-ons – Enhance the\n- Git Hooks – Scripts for automating tasks during\n- FOSS for Developers\n- Hyper – Cross-platform terminal app built on web technologies.\n- PowerShell – Cross-platform object-oriented shell.\n- Alfred Workflows – Productivity app for macOS.\n- Terminals Are Sexy\n- GitHub Actions – Create tasks to automate your workflow and share them with others on GitHub.\n- Database\n- MySQL\n- SQLAlchemy\n- InfluxDB\n- Neo4j\n- MongoDB – NoSQL database.\n- RethinkDB\n- TinkerPop – Graph computing framework.\n- PostgreSQL – Object-relational database.\n- CouchDB – Document-oriented NoSQL database.\n- HBase – Distributed, scalable, big data store.\n- NoSQL Guides – Help on using non-relational, distributed, open-source, and horizontally scalable databases.\n- Contexture – Abstracts queries/filters and results/aggregations from different backing data stores like ElasticSearch and MongoDB.\n- Database Tools – Everything that makes working with databases easier.\n- Grakn – Logical database to organize large and complex networks of data as one body of knowledge.\n- Creative Commons Media\n- Fonts\n- Codeface – Text editor fonts.\n- Stock Resources\n- GIF – Image format known for animated images.\n- Music\n- Open Source Documents\n- Audio Visualization\n- Broadcasting\n- Pixel Art – Pixel-level digital art.\n- FFmpeg – Cross-platform solution to record, convert and stream audio and video.\n- Icons – Downloadable SVG/PNG/font icon projects.\n- Audiovisual – Lighting, audio and video in professional environments.\n- CLI Workshoppers – Interactive tutorials.\n- Learn to Program\n- Speaking\n- Tech Videos\n- Dive into Machine Learning\n- Computer History\n- Programming for Kids\n- Educational Games – Learn while playing.\n- JavaScript Learning\n- CSS Learning – Mainly about CSS – the language and the modules.\n- Product Management – Learn how to be a better product manager.\n- Roadmaps – Gives you a clear route to improve your knowledge and skills.\n- YouTubers – Watch video tutorials from YouTubers that teach you about technology.\n- Application Security\n- Security\n- CTF – Capture The Flag.\n- Malware Analysis\n- Android Security\n- Hacking\n- Honeypots – Deception trap, designed to entice an attacker into attempting to compromise the information systems in an organization.\n- Incident Response\n- Vehicle Security and Car Hacking\n- Web Security – Security of web apps & services.\n- Lockpicking – The art of unlocking a lock by manipulating its components without the key.\n- Cybersecurity Blue Team – Groups of individuals who identify security flaws in information technology systems.\n- Fuzzing – Automated software testing technique that involves feeding pseudo-randomly generated input data.\n- Embedded and IoT Security\n- GDPR – Regulation on data protection and privacy for all individuals within EU.\n- DevSecOps – Integration of security practices into DevOps.\nContent Management Systems\n- Umbraco\n- Refinery CMS – Ruby on Rails CMS.\n- Wagtail – Django CMS focused on flexibility and user experience.\n- Textpattern – Lightweight PHP-based CMS.\n- Drupal – Extensible PHP-based CMS.\n- Craft CMS – Content-first CMS.\n- Sitecore – .NET digital marketing platform that combines CMS with tools for managing multiple websites.\n- Silverstripe CMS – PHP MVC framework that serves as a classic or headless CMS.\n- Robotics\n- Internet of Things\n- Electronics – For electronic engineers and hobbyists.\n- Bluetooth Beacons\n- Electric Guitar Specifications – Checklist for building your own electric guitar.\n- Plotters – Computer-controlled drawing machines and other visual art robots.\n- Robotic Tooling – Free and open tools for professional robotic development.\n- LIDAR – Sensor for measuring distances by illuminating the target with laser light.\n- Open Companies\n- Places to Post Your Startup\n- OKR Methodology – Goal setting & communication best practices.\n- Leading and Managing – Leading people and being a manager in a technology company/environment.\n- Indie – Independent developer businesses.\n- Tools of the Trade – Tools used by companies on Hacker News.\n- Clean Tech – Fighting climate change with technology.\n- Wardley Maps – Provides high situational awareness to help improve strategic planning and decision making.\n- Social Enterprise – Building an organization primarily focused on social impact that is at least partially self-funded.\n- Engineering Team Management – How to transition from software development to engineering management.\n- Developer-First Products – Products that target developers as the user.\n- Slack – Team collaboration.\n- Remote Jobs\n- Productivity\n- Niche Job Boards\n- Programming Interviews\n- Code Review – Reviewing code.\n- Creative Technology – Businesses & groups that specialize in combining computing, design, art, and user experience.\n- Software-Defined Networking\n- Network Analysis\n- PCAPTools\n- Real-Time Communications – Network protocols for near simultaneous exchange of media and data.\nDecentralized Systems\n- Bitcoin – Bitcoin services and tools for software developers.\n- Ripple – Open source distributed settlement network.\n- Non-Financial Blockchain – Non-financial blockchain applications.\n- Mastodon – Open source decentralized microblogging network.\n- Ethereum – Distributed computing platform for smart contract development.\n- Blockchain AI – Blockchain projects for artificial intelligence and machine learning.\n- EOSIO – A decentralized operating system supporting industrial-scale apps.\n- Corda – Open source blockchain platform designed for business.\n- Waves – Open source blockchain platform and development toolset for Web 3.0 apps and decentralized solutions.\n- Substrate – Framework for writing scalable, upgradeable blockchains in Rust.\nHigher Education\n- Computational Neuroscience – A multidisciplinary science which uses computational approaches to study the nervous system.\n- Digital History – Computer-aided scientific investigation of history.\n- Scientific Writing – Distraction-free scientific writing with Markdown, reStructuredText and Jupyter notebooks.\n- Creative Tech Events – Events around the globe for creative coding, tech, design, music, arts and cool stuff.\n- Events in Italy – Tech-related events in Italy.\n- Events in the Netherlands – Tech-related events in the Netherlands.\n- Testing – Software testing.\n- Visual Regression Testing – Ensures changes did not break the functionality or style.\n- Selenium – Open-source browser automation framework and ecosystem.\n- Appium – Test automation tool for apps.\n- TAP – Test Anything Protocol.\n- JMeter – Load testing and performance measurement tool.\n- k6 – Open-source, developer-centric performance monitoring and load testing solution.\n- Playwright – Node.js library to automate Chromium, Firefox and WebKit with a single API.\n- Quality Assurance Roadmap – How to start & build a career in software testing.\n- JSON – Text based data interchange format.\n- CSV – A text file format that stores tabular data and uses a comma to separate values.\n- Discounts for Student Developers\n- Radio\n- Awesome – Recursion illustrated.\n- Analytics\n- Continuous Integration and Continuous Delivery\n- Services Engineering\n- Free for Developers\n- Answers – Stack Overflow, Quora, etc.\n- Sketch – Design app for macOS.\n- Boilerplate Projects\n- Readme\n- Design and Development Guides\n- Software Engineering Blogs\n- Self Hosted\n- FOSS Production Apps\n- Gulp – Task runner.\n- AMA – Ask Me Anything.\n- Open Source Photography\n- OpenGL – Cross-platform API for rendering 2D and 3D graphics.\n- GraphQL\n- Transit\n- Research Tools\n- Data Visualization\n- Social Media Share Links\n- Microservices\n- Unicode – Unicode standards, quirks, packages and resources.\n- Beginner-Friendly Projects\n- Katas\n- Tools for Activism\n- Citizen Science – For community-based and non-institutional scientists.\n- MQTT – “Internet of Things” connectivity protocol.\n- Hacking Spots\n- For Girls\n- Vorpal – Node.js CLI framework.\n- Vulkan – Low-overhead, cross-platform 3D graphics and compute API.\n- LaTeX – Typesetting language.\n- Economics – An economist’s starter kit.\n- Funny Markov Chains\n- Bioinformatics\n- Cheminformatics – Informatics techniques applied to problems in chemistry.\n- Colorful – Choose your next color scheme.\n- Steam – Digital distribution platform.\n- Bots – Building bots.\n- Site Reliability Engineering\n- Empathy in Engineering – Building and promoting more compassionate engineering cultures.\n- DTrace – Dynamic tracing framework.\n- Userscripts – Enhance your browsing experience.\n- Pokémon – Pokémon and Pokémon GO.\n- ChatOps – Managing technical and business operations through a chat.\n- Falsehood – Falsehoods programmers believe in.\n- Domain-Driven Design – Software development approach for complex needs by connecting the implementation to an evolving model.\n- Quantified Self – Self-tracking through technology.\n- SaltStack – Python-based config management system.\n- Web Design – For digital designers.\n- Creative Coding – Programming something expressive instead of something functional.\n- No-Login Web Apps – Web apps that work without login.\n- Free Software – Free as in freedom.\n- Framer – Prototyping interactive UI designs.\n- Markdown – Markup language.\n- Dev Fun – Funny developer projects.\n- Healthcare – Open source healthcare software for facilities, providers, developers, policy experts, and researchers.\n- Magento 2 – Open Source eCommerce built with PHP.\n- TikZ – Graph drawing packages for TeX/LaTeX/ConTeXt.\n- Neuroscience – Study of the nervous system and brain.\n- Ad-Free – Ad-free alternatives.\n- Esolangs – Programming languages designed for experimentation or as jokes rather than actual use.\n- Prometheus – Open-source monitoring system.\n- Homematic – Smart home devices.\n- Ledger – Double-entry accounting on the command-line.\n- Web Monetization – A free open web standard service that allows you to send money directly in your browser.\n- Uncopyright – Public domain works.\n- Crypto Currency Tools & Algorithms – Digital currency where encryption is used to regulate the generation of units and verify transfers.\n- Diversity – Creating a more inclusive and diverse tech community.\n- Open Source Supporters – Companies that offer their tools and services for free to open source projects.\n- Design Principles – Create better and more consistent designs and experiences.\n- Theravada – Teachings from the Theravada Buddhist tradition.\n- inspectIT – Open source Java app performance management tool.\n- Open Source Maintainers – The experience of being an open source maintainer.\n- Calculators – Calculators for every platform.\n- Captcha – A type of challenge–response test used in computing to determine whether or not the user is human.\n- Jupyter – Create and share documents that contain code, equations, visualizations and narrative text.\n- FIRST Robotics Competition – International high school robotics championship.\n- Humane Technology – Open source projects that help improve society.\n- Speakers – Conference and meetup speakers in the programming and design community.\n- Board Games – Table-top gaming fun for all.\n- Software Patreons – Fund individual programmers or the development of open source projects.\n- Parasite – Parasites and host-pathogen interactions.\n- Food – Food-related projects on GitHub.\n- Mental Health – Mental health awareness and self-care in the software industry.\n- Bitcoin Payment Processors – Start accepting Bitcoin.\n- Scientific Computing – Solving complex scientific problems using computers.\n- Amazon Sellers\n- Agriculture – Open source technology for farming and gardening.\n- Product Design – Design a product from the initial concept to production.\n- Prisma – Turn your database into a GraphQL API.\n- Software Architecture – The discipline of designing and building software.\n- Connectivity Data and Reports – Better understand who has access to telecommunication and internet infrastructure and on what terms.\n- Stacks – Tech stacks for building different apps and features.\n- Cytodata – Image-based profiling of biological phenotypes for computational biologists.\n- IRC – Open source messaging protocol.\n- Advertising – Advertising and programmatic media for websites.\n- Earth – Find ways to resolve the climate crisis.\n- Naming – Naming things in computer science done right.\n- Biomedical Information Extraction – How to extract information from unstructured biomedical data and text.\n- Web Archiving – An effort to preserve the Web for future generations.\n- WP-CLI – Command-line interface for WordPress.\n- Credit Modeling – Methods for classifying credit applicants into risk classes.\n- Ansible – A Python-based, open source IT configuration management and automation platform.\n- Biological Visualizations – Interactive visualization of biological data on the web.\n- QR Code – A type of matrix barcode that can be used to store and share a small amount of information.\n- Veganism – Making the plant-based lifestyle easy and accessible.\n- Translations – The transfer of the meaning of a text from one language to another.\n- All Awesome Lists – All the Awesome lists on GitHub.\n- Awesome Indexed – Search the Awesome dataset.\n- Awesome Search – Quick search for Awesome lists.\n- StumbleUponAwesome – Discover random pages from the Awesome dataset using a browser extension.\n- Awesome CLI – A simple command-line tool to dive into Awesome lists.\n- Awesome Viewer – A visualizer for all of the above Awesome lists.\nUS Department of Education CRDC Dataset\nThe US Department of Ed has a dataset called the CRDC that collects data from all the public schools in the US and has demographic, academic, financial and all sorts of other fun data points. They also have corollary datasets that use the same identifier—an expansion pack if you may. It comes out every 2-3 years. Access it here.\nNasa Dataset: sequencing data from bacteria before and after being taken to space\nNASA has some sequencing data from bacteria before and after being taken to space, to look at genetic differences caused by lack of gravity, radiation and others. Very fun if you want to try your hand at some bio data science. Access it here.\nAll Trump’s twitter insults from 2015 to 2021 in CSV.\nExtracted from the NYT story: here\nData is plural\nData is Plural is a really good newsletter published by Jeremy Singer-Vine. The datasets are very random, but super interesting. Access it here.\nGlobal terrorism database\nHuge list of terrorism incidents from inside the US and abroad. Each entry has date and location of the incident, motivations, whether people or property were lost, the size of the attack, type of attack, etc. Access it here.\nTerrorist Attacks Dataset: This dataset consists of 1293 terrorist attacks each assigned one of 6 labels indicating the type of the attack. Each attack is described by a 0/1-valued vector of attributes whose entries indicate the absence/presence of a feature. There are a total of 106 distinct features. The files in the dataset can be used to create two distinct graphs. The README file in the dataset provides more details. Download Link\nTerrorists: This dataset contains information about terrorists and their relationships. This dataset was designed for classification experiments aimed at classifying the relationships among terrorists. The dataset contains 851 relationships, each described by a 0/1-valued vector of attributes where each entry indicates the absence/presence of a feature. There are a total of 1224 distinct features. Each relationship can be assigned one or more labels out of a maximum of four labels making this dataset suitable for multi-label classification tasks. The README file provides more details. Download Link\nThe dolphin social network\nThis network dataset is in the category of Social Networks. A social network of bottlenose dolphins. The dataset contains a list of all of links, where a link represents frequent associations between dolphins. Access it here\nDataset of 200,000 jokes\nThere are about 208 000 jokes in this database scraped from three sources.\nThe Million Song Dataset\nThe Million Song Dataset is a freely-available collection of audio features and metadata for a million contemporary popular music tracks.\nIts purposes are:\n- To encourage research on algorithms that scale to commercial sizes\n- To provide a reference dataset for evaluating research\n- As a shortcut alternative to creating a large dataset with APIs (e.g. The Echo Nest’s)\n- To help new researchers get started in the MIR field\nCornell University’s eBird dataset\nDecades of observations of birds all around the world, truly an impressive way to leverage citizen science. Access it here.\nUFO Report Dataset\nNUFORC geolocated and time standardized ufo reports for close to a century of data. 80,000 plus reports. Access it here\nCDC’s Trend Drug Data\nThe CDC has a public database called NAMCS/NHAMCS that allows you to trend drug data. It has a lot of other data points so it can be used for a variety of other reasons. Access it here.\nHealth and Retirement study: Public Survey data\nA listing of publicly available biennial, off-year, and cross-year data products.\nExample: COVID-19 Data\n|2020 HRS COVID-19 Project\nOriginal. Reposted with permission.\n- Introducing The NLP Index\n- 8 Places for Data Professionals to Find Datasets\n- 3 Best Sites to Find Datasets for your Data Science Projects", "meta": {"lang": "en", "lang_score": 0.7693485021591187, "url": "https://www.kdnuggets.com/2021/05/awesome-list-datasets.html", "timestamp": "2023-01-26T23:10:45Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.007756948933419522, "fraction_of_characters_in_duplicate_lines": 0.0039302454219919064, "fraction_of_characters_in_most_common_ngram": [[2, 0.009607266587091327], [3, 0.00176133220763341], [4, 0.0021834696788843927]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.023697262160973634], [6, 0.016006426841285174], [7, 0.011061896271577148], [8, 0.007555317669248218], [9, 0.004589746868015647], [10, 0.0026656606104217134]], "fraction_of_words_corrected_in_lines": 0.006822234281727266, "fraction_of_lines_ending_with_ellipsis": 0.10660847880299251, "fraction_of_lines_starting_with_bullet_point": 0.8584788029925187, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 2, "word_count": 12811, "mean_word_length": 5.362422917805011, "num_of_sentences": 510, "symbol_to_word_ratio": 0.013972367496682538, "fraction_of_words_with_alpha_character": 0.8175005854343923, "num_of_stop_words": 959, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "For a list of all members of this type, see ConversionWhitePoint members\n|Overridden. Returns a meaningful name for this method.\nConversionWhitePoint Structure\nLeadtools.ColorConversion Namespace\nHelp Collections\nRaster .NET | C API | C++ Class Library | HTML5 JavaScript\nDocument .NET | C API | C++ Class Library | HTML5 JavaScript\nMedical .NET | C API | C++ Class Library | HTML5 JavaScript\nMedical Web Viewer .NET\nDirect Show .NET | C API | Filters\nMedia Foundation .NET | C API | Transforms\nSupported Platforms\n.NET, Java, Android, and iOS/macOS Assemblies\nImaging, Medical, and Document\nC API/C++ Class Libraries\nImaging, Medical, and Document\nHTML5 JavaScript Libraries\nImaging, Medical, and Document\nYour email has been sent to support! Someone should be in touch! If your matter is urgent please come back into chat.\nChat Hours:\nMonday - Friday, 8:30am to 6pm ET\nThank you for your feedback!\nPlease fill out the form again to start a new chat.\nAll agents are currently offline.\nChat Hours:\nMonday - Friday\nTo contact us please fill out this form and we will contact you via email.", "meta": {"lang": "en", "lang_score": 0.7477057576179504, "url": "https://www.leadtools.com/help/sdk/v22/dh/cc/conversionwhitepoint--methods.html", "timestamp": "2023-01-26T21:32:05Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.18518518518518517, "fraction_of_characters_in_duplicate_lines": 0.12334801762114538, "fraction_of_characters_in_most_common_ngram": [[2, 0.02753303964757709], [3, 0.03303964757709251], [4, 0.04955947136563876]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.11255314388006266], [6, 0.08050926792735442], [7, 0.06882656350741458], [8, 0.05692438402718777], [9, 0.04436299292214358], [10, 0.03313149777219239]], "fraction_of_words_corrected_in_lines": 0.042328042328042326, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 181, "mean_word_length": 5.016574585635359, "num_of_sentences": 9, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9171270718232044, "num_of_stop_words": 12, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "iPhone Touch API ... a way for OpenLayers\nPublished Aug 14, 2008 Updated Aug 28, 2008\nIt seems that with Apple’s web Touch API it is possible to create a website, which will behave same way as iPhone build in Google Maps application. You can react by Javascript on all touch events, so implement zooming by pinching for example, or flicking to another page etc.. This functionality would be really cool in the OpenLayers open-source project\nFor more info about the possibilities have a look at very nice description and example application of the Apple Touch API.uld be really cool in the OpenLayers open-source project\nFor more info about the possibilities have a look at very nice description and example application of the Apple Touch API.", "meta": {"lang": "en", "lang_score": 0.9088243246078491, "url": "https://www.maptiler.com/news/2008/08/openlayers-on-iphone-possible/", "timestamp": "2023-01-26T21:55:52Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.02593192868719611], [3, 0.03889789303079417], [4, 0.04538087520259319]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.42499164717674576], [6, 0.41197872935908203], [7, 0.39574776516066684], [8, 0.3782747603833866], [9, 0.35853379152348225], [10, 0.3412601978823121]], "fraction_of_words_corrected_in_lines": 0.0, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 126, "mean_word_length": 4.896825396825397, "num_of_sentences": 3, "symbol_to_word_ratio": 0.007936507936507936, "fraction_of_words_with_alpha_character": 0.9603174603174603, "num_of_stop_words": 18, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "About Us\nEstablished in 2001, MICES Technology Sdn Bhd is specialized in eCommerce solutions and system integration based on open source solutions, we helps SME/SMI to grow their business online, through the setup of shopping cart solution, and synchronize the information with WMS, POS System, Accounting software via API integration. Our works have been trusted by SenQ, OnKing, Sport Planets, Purplecane, CITE, etc.\nMICES Technology also helps customer on digital marketing especially on Facebook Ads and Google Adwords and Google Display Network. We also work with video marketing partner to help the customer on their products/campaign promotion on internet.\nMICES is 15 people’s team consists of young IT talents, which includes Project Manager, PHP+MySQL+Javascript full stack programmers, server Admin and graphic designer.\nOfficial Partners\nMDEC Certified TSP\nSIDEC Certified DSP\nShopify Partner.\nOpencart Partner\nOur Business Philosophy\nHigh Quality Services\nOur goal is to provide a complete and professional range of services. All our work is completed to the same high standard whether it is a single web page or a complete eCommerce solution. Together we will ensure that your business makes the most of the opportunities that the Internet offers.\nMake it Affordable\nWe manage our costs and capacity so that the savings can be passed on to you, our customer. You do not pay for idle time and costly overheads. All these benefits but NOT at the expense of quality service.\nFull Customer Support\nOur revolutionary concept pairs service with support to create the ideal platform to provide services to clients without necessarily having to worry about what’s happening “under the hood”.\nWe provide\nContact us to start your web business now!\nWrite to Us\nContact Us\nE-28-1, Jalan Multimedia 7/AG, I-City,\n40000 Shah Alam, Selangor.\nTel: +603-5888 8321\nEmail: [email protected]", "meta": {"lang": "en", "lang_score": 0.9013079404830933, "url": "https://www.mices.com.my/mices/", "timestamp": "2023-01-26T21:23:31Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.0, "fraction_of_characters_in_duplicate_lines": 0.0, "fraction_of_characters_in_most_common_ngram": [[2, 0.018844221105527637], [3, 0.011306532663316583], [4, 0.01256281407035176]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.0], [6, 0.0], [7, 0.0], [8, 0.0], [9, 0.0], [10, 0.0]], "fraction_of_words_corrected_in_lines": 0.003389830508474576, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 294, "mean_word_length": 5.414965986394558, "num_of_sentences": 16, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9829931972789115, "num_of_stop_words": 43, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}} {"text": "New Web Development and Design Trends To Pay Attention To\nTechnology is a key component to staying afloat in today’s digital marketplace. Therefore, web development and design trends are indispensable when it comes to online business growth. Your website’s lifeblood is wrapped in good coding and programming techniques. For that reason, keeping a close eye on the latest trends is a pre-requisite to a successful business.\nLet us dive into some of the latest trends to help you start out on a high note.\nOpenCart for E-commerce\nTo fit into today’s the fast-paced world; people have resorted to working faster and efficiently. From shopping and fitness to healthcare, individuals are banking on their devices to roundup their informative and retail needs. The online business is booming. Following on-point estimates, worldwide e-commerce will expectedly hit $4 trillion by 2020. Its developers are looking to OpenCart as a means to facilitate easy navigation and hosting. Essentially, OpenCart is an e-commerce platform that enables developers to customise and create extensions with ease.\nThe well-developed administrative dashboard presents easy-to-use menus which are mobile-friendly. As a user, you can toggle through the platform with your smartphone or tablet. Asides from the many options offered, it is well-furnished with multilingual content plastered all across the OpenCart forum. It has over 12,000 extensions as well as ready-to-use templates. Through the multi stores mode, you can manage the multiple stores from one admin panel. To monitor and boost SEO practices as a developer, you can add a Google Analytics extension.\nArtificial Intelligence\nIn the recent times, Artificial Intelligence (AI) systems that interact via text are speedily rising to prominence with regard to online customer services. Chatbots enable regular brand-customer interactions from social media platforms to social media applications. The close engagement helps boost brand loyalty and success. Likewise, Artificial Intelligence Systems aren’t lagging behind.\nBy sourcing detailed data on consumer behavior, they enable sites like Twitter, Facebook and Google to analyse large amounts of data to project the outcome of their business dealing. This development approach is called “deep learning” – and it’s a significant force to tremendous growth. According to analysts, the Internet of Things (IoT) that control household appliances or track crime is ineffective without the Artificial Intelligence Systems.\nImages in Motion\nThe long-awaited days of movable images have finally come. Since users prefer interactive and visually engaging content, developers have wheeled out videos; animations and graphical interchange formats (GIFs). Besides facilitating high-level interaction, the images in motion are good at story telling. Don’t be surprised when developers spice up the page with 360-degree videos and cinematography in the near future.\nJavaScript is a background, textual language that facilitates object-control in web design. Quite simply, it’s the technology behind interactive maps, artificial intelligence systems and animated graphics. Nowadays, a horde of developers vouch for JavaScript as a top programming language. However, with the upticks in design and AI systems alike, there is a growing need for a more efficient programming language. Therefore, expect spicy changes in JavaScript as it grows into one of the integral components of modern web design.\nOne Page Websites\nAnother highly transformative trend is the One Page Websites. Since a myriad of online users own mobile phones, one page websites works best for smart phones and tablets. This mobile-responsive trend not only de-clutters the screen but captivates and easily engages users. Their fewer tabs allow easy user navigation and ultimately improve their experience.\nGet A Free Project Quote\nStart Converting Visitors To Customers\nTell us what you need today.\nWe start every project with a simple conversation, getting to know you and your business, your requirements and your goals. If you would like to book a consultation, fill out the form below and we will be in touch to arrange a time.\nTell us what you need today.\nWe start every project with a simple conversation, getting to know you and your business, your requirements and your goals. If you would like to book a consultation, fill out the form below and we will be in touch to arrange a time.", "meta": {"lang": "en", "lang_score": 0.9133662581443787, "url": "https://www.triplewmedia.com/new-trends-to-pay-attention-to-in-the-world-of-web-development/", "timestamp": "2023-01-26T22:25:35Z", "cc-path": "crawl-data/CC-MAIN-2023-06/segments/1674764494826.88/warc/CC-MAIN-20230126210844-20230127000844-00000.warc.gz"}, "quality_signals": {"fraction_of_duplicate_lines": 0.2, "fraction_of_characters_in_duplicate_lines": 0.1384820239680426, "fraction_of_characters_in_most_common_ngram": [[2, 0.003195739014647137], [3, 0.007989347536617843], [4, 0.006924101198402131]], "fraction_of_characters_in_duplicate_ngrams": [[5, 0.10626003210272873], [6, 0.10437965980624135], [7, 0.10245210727969349], [8, 0.10074839748968017], [9, 0.09890405231881029], [10, 0.09707797449281602]], "fraction_of_words_corrected_in_lines": 0.0014705882352941176, "fraction_of_lines_ending_with_ellipsis": 0.0, "fraction_of_lines_starting_with_bullet_point": 0.0, "fraction_of_lines_with_toxic_words": 0.0, "num_of_lines_with_toxic_words": 0, "num_of_toxic_words": 0, "word_count": 679, "mean_word_length": 5.5301914580265095, "num_of_sentences": 43, "symbol_to_word_ratio": 0.0, "fraction_of_words_with_alpha_character": 0.9941089837997055, "num_of_stop_words": 99, "num_of_paragraphs": 0, "has_curly_bracket": false, "has_lorem_ipsum": false}}