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Ajax (programming)

The Asynchronous JavaScript and XML, usually referred to as Ajax (or AJAX, ) is a set of web development techniques that uses various web technologies on the client-side to create asynchronous web applications. With Ajax, web applications can send and retrieve data from a server asynchronously (in the background) without interfering with the display and behaviour of the existing page. By decoupling the data interchange layer from the presentation layer, Ajax allows web pages and, by extension, web applications, to change content dynamically without the need to reload the entire page. In practice, modern implementations commonly utilize JSON instead of XML. Ajax is not a technology, but rather a programming pattern. HTML and CSS can be used in combination to mark up and style information. The webpage can be modified by JavaScript to dynamically display (and allow the user to interact with) the new information. The built-in XMLHttpRequest object is used to execute Ajax on webpages, allowing websites to load content onto the screen without refreshing the page. == History == In the early-to-mid 1990s, most Websites were based on complete HTML pages. Each user action required a complete new page to be loaded from the server. This process was inefficient, as reflected by the user experience: all page content disappeared, then the new page appeared. Each time the browser reloaded a page because of a partial change, all the content had to be re-sent, even though only some of the information had changed. This placed additional load on the server and made bandwidth a limiting factor in performance. The foundations of AJAX originate back in 1996 with the introduction of JavaScript 1. Developers quickly discovered that any HTML element which accepted a "src" attribute could be used to fetch remote data. By changing the src of a hidden frame, a developer could fetch remote data, process or display it without a page refresh. The remote data could be a string, JavaScript code, XML or a partial HTML page generated on the server. The same could be done with and tags, but many developers were alarmed at the concept of an executable GIF and preferred to use the hidden . This technique was used for both Netscape Navigator and Internet Explorer, the two main browsers at the time, until developers discovered the XMLHTTP server object (MSXML 1.0) was included in Internet Explorer 4. Browser detection was then used to either implement the hidden <iframe> in Netscape or use the XMLHTTP (MSXML 1.0) object in IE 4. In 1996, the iframe tag was introduced by Internet Explorer; like the object element, it can load a part of the web page asynchronously. In 1998, the Microsoft Outlook Web Access team developed the concept behind the XMLHttpRequest scripting object. It appeared as XMLHTTP in the second version of the MSXML library, which shipped with Internet Explorer 5.0 in March 1999. The functionality of the Windows XMLHTTP ActiveX control in IE 5 was later implemented by Mozilla Firefox, Safari, Opera, Google Chrome, and other browsers as the XMLHttpRequest JavaScript object. Microsoft adopted the native XMLHttpRequest model as of Internet Explorer 7. Support for the ActiveX version remained in Internet Explorer and on "Internet Explorer mode" in Microsoft Edge. The utility of these background HTTP requests and asynchronous Web technologies remained fairly obscure until it started appearing in large scale online applications such as Outlook Web Access (2000) and Oddpost (2002). Google made a wide deployment of standards-compliant, cross browser Ajax with Gmail (2004) and Google Maps (2005). In October 2004 Kayak.com's public beta release was among the first large-scale e-commerce uses of what their developers at that time called "the xml http thing". This increased interest in Ajax among web program developers. The term AJAX was publicly used on 18 February 2005 by Jesse James Garrett in an article titled Ajax: A New Approach to Web Applications, based on techniques used on Google pages. On 5 April 2006, the World Wide Web Consortium (W3C) released the first draft specification for the XMLHttpRequest object in an attempt to create an official Web standard. The latest draft of the XMLHttpRequest object was published on 6 October 2016, and the XMLHttpRequest specification is now a living standard. == Technologies == The term Ajax has come to represent a broad group of Web technologies that can be used to implement a Web application that communicates with a server in the background, without interfering with the current state of the page. In the article that coined the term Ajax, Jesse James Garrett explained that the following technologies are incorporated: HTML (or XHTML) and CSS for presentation The Document Object Model (DOM) for dynamic display of and interaction with data JSON or XML for the interchange of data, and XSLT for XML manipulation The XMLHttpRequest object for asynchronous communication JavaScript to bring these technologies together Since then, however, there have been a number of developments in the technologies used in an Ajax application, and in the definition of the term Ajax itself. XML is no longer required for data interchange and, therefore, XSLT is no longer required for the manipulation of data. JavaScript Object Notation (JSON) is often used as an alternative format for data interchange, although other formats such as preformatted HTML or plain text can also be used. A variety of popular JavaScript libraries, including jQuery, include abstractions to assist in executing Ajax requests. == Examples == === JavaScript example === An example of a simple Ajax request using the GET method, written in JavaScript. get-ajax-data.js: send-ajax-data.php: === Fetch example === Fetch is a native JavaScript API. According to Google Developers Documentation, "Fetch makes it easier to make web requests and handle responses than with the older XMLHttpRequest." ==== ES7 async/await example ==== Fetch relies on JavaScript promises. The fetch specification differs from Ajax in the following significant ways: The Promise returned from fetch() won't reject on HTTP error status even if the response is an HTTP 404 or 500. Instead, as soon as the server responds with headers, the Promise will resolve normally (with the ok property of the response set to false if the response isn't in the range 200–299), and it will only reject on network failure or if anything prevented the request from completing. fetch() won't send cross-origin cookies unless you set the credentials init option. (Since April 2018. The spec changed the default credentials policy to same-origin. Firefox changed since 61.0b13.) == Benefits == Ajax offers several benefits that can significantly enhance web application performance and user experience. By reducing server traffic and improving speed, Ajax plays a crucial role in modern web development. One key advantage of Ajax is its capacity to render web applications without requiring data retrieval, resulting in reduced server traffic. This optimization minimizes response times on both the server and client sides, eliminating the need for users to endure loading screens. Furthermore, Ajax facilitates asynchronous processing by simplifying the utilization of XmlHttpRequest, which enables efficient handling of requests for asynchronous data retrieval. Additionally, the dynamic loading of content enhances the application's performance significantly. Besides, Ajax enjoys broad support across all major web browsers, including Microsoft Internet Explorer versions 5 and above, Mozilla Firefox versions 1.0 and beyond, Opera versions 7.6 and above, and Apple Safari versions 1.2 and higher.</p> <a href="https://aizhi.co/html/323e999667.html" class="read-more" title="Ajax (programming)">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/219a999771.html" class="card-thumb-link" title="Deplatforming"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/a/a3/St_Kentigerns_Church_HDR_%288226826999%29.jpg/960px-St_Kentigerns_Church_HDR_%288226826999%29.jpg" alt="Deplatforming" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/219a999771.html" title="Deplatforming">Deplatforming</a></h2> <p class="article-excerpt">Deplatforming, also known as no-platforming, is a boycott on an individual or group by removing the platforms used to share their information or ideas. The term is commonly associated with social media. == History == === Deplatforming of invited speakers === In the United States, the banning of speakers on university campuses dates back to the 1940s. This was carried out by the policies of the universities themselves. The University of California had a policy known as the Speaker Ban, codified in university regulations under President Robert Gordon Sproul, that mostly, but not exclusively, targeted communists. One rule stated that "the University assumed the right to prevent exploitation of its prestige by unqualified persons or by those who would use it as a platform for propaganda." This rule was used in 1951 to block Max Shachtman, a socialist, from speaking at the University of California at Berkeley. In 1947, former U.S. Vice President Henry A. Wallace was banned from speaking at UCLA because of his views on U.S. Cold War policy, and in 1961, Malcolm X was prohibited from speaking at Berkeley as a religious leader. Controversial speakers invited to appear on college campuses have faced deplatforming attempts to disinvite them or to otherwise prevent them from speaking. The British National Union of Students established its No Platform policy as early as 1973. In the mid-1980s, visits by South African ambassador Glenn Babb to Canadian college campuses faced opposition from students opposed to apartheid. In the United States, recent examples include the March 2017 disruption by protestors of a public speech at Middlebury College by political scientist Charles Murray. In February 2018, students at the University of Central Oklahoma rescinded a speaking invitation to creationist Ken Ham, after pressure from an LGBT student group. In March 2018, a "small group of protesters" at Lewis & Clark Law School attempted to stop a speech by visiting lecturer Christina Hoff Sommers. In the 2019 film No Safe Spaces, Adam Carolla and Dennis Prager documented their own disinvitation along with others. As of February 2020, the Foundation for Individual Rights in Education, a speech advocacy group, documented 469 disinvitation or disruption attempts at American campuses since 2000, including both "unsuccessful disinvitation attempts" and "successful disinvitations"; the group defines the latter category as including three subcategories: formal disinvitation by the sponsor of the speaking engagement; the speaker's withdrawal "in the face of disinvitation demands"; and "heckler's vetoes" (situations when "students or faculty persistently disrupt or entirely prevent the speakers' ability to speak"). === Deplatforming in social media === Beginning in 2015, Reddit banned several communities on the site ("subreddits") for violating the site's anti-harassment policy. A 2017 study published in the journal Proceedings of the ACM on Human-Computer Interaction, examining "the causal effects of the ban on both participating users and affected communities," found that "the ban served a number of useful purposes for Reddit" and that "Users participating in the banned subreddits either left the site or (for those who remained) dramatically reduced their hate speech usage. Communities that inherited the displaced activity of these users did not suffer from an increase in hate speech." In June 2020 and January 2021, Reddit also issued bans to pro-Trump communities over violations of the website's content and harassment policies. On May 2, 2019, Facebook and the Facebook-owned platform Instagram announced a ban of "dangerous individuals and organizations" including Nation of Islam leader Louis Farrakhan, Milo Yiannopoulos, Alex Jones and his organization InfoWars, Paul Joseph Watson, Laura Loomer, and Paul Nehlen. In the wake of the 2021 storming of the US Capitol, Twitter banned then-president Donald Trump, as well as 70,000 other accounts linked to the event and the far-right movement QAnon. Some studies have found that the deplatforming of extremists reduced their audience, although other research has found that some content creators became more toxic following deplatforming and migration to alt-tech platform. ==== Twitter ==== On November 18, 2022, Elon Musk, as newly appointed CEO of Twitter, reopened previously banned Twitter accounts of high-profile users, including Kathy Griffin, Jordan Peterson, and The Babylon Bee as part of the new Twitter policy. As Musk exclaimed, "New Twitter policy is freedom of speech, but not freedom of reach". ==== Alex Jones ==== On August 6, 2018, Facebook, Apple, YouTube and Spotify removed all content by Jones and InfoWars for policy violations. YouTube removed channels associated with InfoWars, including The Alex Jones Channel. On Facebook, four pages associated with InfoWars and Alex Jones were removed over repeated policy violations. Apple removed all podcasts associated with Jones from iTunes. On August 13, 2018, Vimeo removed all of Jones's videos because of "prohibitions on discriminatory and hateful content". Facebook cited instances of dehumanizing immigrants, Muslims and transgender people, as well as glorification of violence, as examples of hate speech. After InfoWars was banned from Facebook, Jones used another of his websites, NewsWars, to circumvent the ban. Jones's accounts were also removed from Pinterest, Mailchimp and LinkedIn. As of early August 2018, Jones retained active accounts on Instagram, Google+ and Twitter. In September, Jones was permanently banned from Twitter and Periscope after berating CNN reporter Oliver Darcy. On September 7, 2018, the InfoWars app was removed from the Apple App Store for "objectionable content". He was banned from using PayPal for business transactions, having violated the company's policies by expressing "hate or discriminatory intolerance against certain communities and religions." After Elon Musk's purchase of Twitter several previously banned accounts were reinstated including Donald Trump, Andrew Tate and Ye resulting in questioning if Alex Jones will be unbanned as well. However Musk denied that Alex Jones will be unbanned criticizing Jones as a person that "would use the deaths of children for gain, politics or fame". InfoWars remained available on Roku devices in January 2019, a year after the channel's removal from multiple streaming services. Roku indicated that they do not "curate or censor based on viewpoint," and that it had policies against content that is "unlawful, incited illegal activities, or violates third-party rights," but that InfoWars was not in violation of these policies. Following a social media backlash, Roku removed InfoWars and stated "After the InfoWars channel became available, we heard from concerned parties and have determined that the channel should be removed from our platform." In March 2019, YouTube terminated the Resistance News channel due to its reuploading of live streams from InfoWars. On May 1, 2019, Jones was barred from using both Facebook and Instagram. Jones briefly moved to Dlive, but was suspended in April 2019 for violating community guidelines. In March 2020, the InfoWars app was removed from the Google Play store due to claims of Jones disseminating COVID-19 misinformation. A Google spokesperson stated that "combating misinformation on the Play Store is a top priority for the team" and apps that violate Play policy by "distributing misleading or harmful information" are removed from the store. ==== Donald Trump ==== On January 6, 2021, in a joint session of the United States Congress, the counting of the votes of the Electoral College was interrupted by a breach of the United States Capitol chambers. The rioters were supporters of President Donald Trump who hoped to delay and overturn the President's loss in the 2020 election. The event resulted in five deaths and at least 400 people being charged with crimes. The certification of the electoral votes was only completed in the early morning hours of January 7, 2021. In the wake of several Tweets by President Trump on January 7, 2021 Facebook, Instagram, YouTube, Reddit, and Twitter all deplatformed Trump to some extent. Twitter deactivated his personal account, which the company said could possibly be used to promote further violence. Trump subsequently tweeted similar messages from the President's official US Government account @POTUS, which resulted in him being permanently banned on January 8. Twitter then announced that Trump's ban from their platform would be permanent. Trump planned to rejoin on social media through the use of a new platform by May or June 2021, according to Jason Miller on a Fox News broadcast. The same week Musk announced Twitter's new freedom of speech policy, he tweeted a poll to ask whether to bring back Trump into the platform. The poll ended with 51.8% in favor of unbanning Trump's account. Twitter has since reinstated Trump's Twitter accou</p> <a href="https://aizhi.co/html/219a999771.html" class="read-more" title="Deplatforming">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/450b099549.html" class="card-thumb-link" title="Zé Delivery"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/5/56/BLW_Automated_postal_sorting_equipment_%281%29.jpg/960px-BLW_Automated_postal_sorting_equipment_%281%29.jpg" alt="Zé Delivery" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/450b099549.html" title="Zé Delivery">Zé Delivery</a></h2> <p class="article-excerpt">Zé Delivery is a startup developed by Brazilian drinks company AmBev which offers an app for delivering drinks. The app is available for Android and iOS. Created in 2016 by AmBev's ZX Ventures hub, the service has an international presence in Argentina, Paraguay, Bolivia, Panama and the Dominican Republic. It is also present in more than 300 Brazilian cities. Because it has an extensive category of alcoholic beverages, the service is only used by people over 18. It also offers soft drinks, juices, energy drinks and other non-alcoholic beverages.</p> <a href="https://aizhi.co/html/450b099549.html" class="read-more" title="Zé Delivery">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/44e999946.html" class="card-thumb-link" title="Single address space operating system"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/1/19/MagistoLogo.png" alt="Single address space operating system" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/44e999946.html" title="Single address space operating system">Single address space operating system</a></h2> <p class="article-excerpt">In computer science, a single address space operating system (or SASOS) is an operating system that provides only one globally shared address space for all processes. In a single address space operating system, numerically identical (virtual memory) logical addresses in different processes all refer to exactly the same byte of data. In a traditional OS with private per-process address space, memory protection is based on address space boundaries ("address space isolation"). Single address-space operating systems make translation and protection orthogonal, which in no way weakens protection. The core advantage is that pointers (i.e. memory references) have global validity, meaning their meaning is independent of the process using it. This allows sharing pointer-connected data structures across processes, and making them persistent, i.e. storing them on backup store. Some processor architectures have direct support for protection independent of translation. On such architectures, a SASOS may be able to perform context switches faster than a traditional OS. Such architectures include Itanium, and Version 5 of the Arm architecture, as well as capability architectures such as CHERI. A SASOS should not be confused with a flat memory model, which provides no address translation and generally no memory protection. In contrast, a SASOS makes protection orthogonal to translation: it may be possible to name a data item (i.e. know its virtual address) while not being able to access it. SASOS projects using hardware-based protection include the following: Angel IBM i (formerly called OS/400) Iguana at NICTA, Australia Mungi at NICTA, Australia Nemesis Opal Scout Sombrero Related are OSes that provide protection through language-level type safety: Br1X Genera JX a research Java OS Phantom OS Singularity Theseus OS Torsion</p> <a href="https://aizhi.co/html/44e999946.html" class="read-more" title="Single address space operating system">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/296b999694.html" class="card-thumb-link" title="Groundswell (book)"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/f/fe/Welcome_to_the_Simulated_Universe_%28Ideogram_3.0%29.webp" alt="Groundswell (book)" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/296b999694.html" title="Groundswell (book)">Groundswell (book)</a></h2> <p class="article-excerpt">Groundswell is a book by Forrester Research executives Charlene Li and Josh Bernoff that focuses on how companies can take advantage of emerging social technologies. It was published in 2008 by Harvard Business Press. A revised edition was published in 2011. The book attempts to explain a shift in the relationship between customers and companies, in which companies are no longer able to control customers' attitudes through market research, customer service, and advertising. Instead, customers are controlling the conversation by using new media to communicate about products and companies. == Synopsis == The groundswell is characterized by several tactics that guide companies into using social technologies strategically and effectively. Listening: Businesses should listen to their customers to understand what the market is looking for in their products. In order to do this, a company needs to find out if their customers are using social technologies and how they are using them. Talking: Instead of advertising to customers, marketing departments should find creative ways to connect with users about their experience with a product and their feelings about the brand. One common method is participation in social networks. Energizing: Enthusiastic customers are part of the groundswell, and companies can recognize and appreciate these customers by creating online communities and social platforms where they can connect with the brand and provide reviews. Supporting: Businesses can harness the support of their own employees by creating internal social applications for them to connect with the brand, also known as enterprise social software. == Groundswell in action == === Examples === Some companies distinguish their product through the use of social technologies. Tom Dickson successfully marketed his Blendtec line of blenders through the viral marketing campaign Will It Blend? The groundswell spread marketing messages through Digg and YouTube with a small budget and little marketing experience. Other companies have been able to listen to and talk with the groundswell by building their own online communities. Procter & Gamble created beinggirl.com Archived 2016-04-10 at the Wayback Machine to introduce girls to P&G feminine care products. The community approach worked because the company could reach girls with information that might seem embarrassing or sensitive in a traditional marketing campaign. === Risks === Features of particular industries or companies can make direct customer engagement more difficult. For instance, some companies must work within industry regulations, national or multinational corporations must balance corporate and local engagement, and other companies must find ways to engage with customers on time-sensitive issues. == Reception == Kevin Allison of the Financial Times praised the book for its focus on Web analytics: "[Groundswell] is not so much a manifesto or a dissection of online culture as it is a how-to manual for executives and mid-level managers trying to navigate this fast-changing and often confusing environment." The book won the American Marketing Association Foundation’s Berry-AMA Book Prize for best marketing book of 2009. It was also listed by: Amazon, as one of the Top 10 Business & Investing Books of 2008 CIO Insight, as one of the Top 10 Business-Tech Books of 2008 and one of 10 Insightful Web 2.0 Books Fortune as Magazine as one of the 3 best Web books of 2008 Advertising Age as number 3 of 10 Books You Should Have Read BusinessWeek as one of the Best Innovation & Design Books of 2008 "strategy+business" as one of the Best Business Books 2008 and “Top Shelf” in Marketing</p> <a href="https://aizhi.co/html/296b999694.html" class="read-more" title="Groundswell (book)">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/488a999502.html" class="card-thumb-link" title="Interference (communication)"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/c/c0/Flok_official_logo.png/960px-Flok_official_logo.png" alt="Interference (communication)" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/488a999502.html" title="Interference (communication)">Interference (communication)</a></h2> <p class="article-excerpt">In telecommunications, an interference is that which modifies a signal in a disruptive manner, as it travels along a communication channel between its source and receiver. The term is often used to refer to the addition of unwanted signals to a useful signal. Common examples include: Electromagnetic interference (EMI) Co-channel interference (CCI), also known as crosstalk Adjacent-channel interference (ACI) Intersymbol interference (ISI) Inter-carrier interference (ICI), caused by doppler shift in OFDM modulation (multitone modulation). Common-mode interference (CMI) Conducted interference Noise is a form of interference but not all interference is noise. Radio resource management aims at reducing and controlling the co-channel and adjacent-channel interference. == Interference alignment == A solution to interference problems in wireless communication networks is interference alignment, which was crystallized by Syed Ali Jafar at the University of California, Irvine. A specialized application was previously studied by Yitzhak Birk and Tomer Kol for an index coding problem in 1998. For interference management in wireless communication, interference alignment was originally introduced by Mohammad Ali Maddah-Ali, Abolfazl S. Motahari, and Amir Keyvan Khandani, at the University of Waterloo, for communication over wireless X channels. Interference alignment was eventually established as a general principle by Jafar and Viveck R. Cadambe in 2008, when they introduced "a mechanism to align an arbitrarily large number of interferers, leading to the surprising conclusion that wireless networks are not essentially interference limited." This led to the adoption of interference alignment in the design of wireless networks. Jafar explained: My research group crystallized the concept of interference alignment and showed that through interference alignment, it is possible for everyone to access half of the total bandwidth free from interference. Initially this result was shown under a number of idealized assumptions that are typical in theoretical studies. We have since continued to work on peeling off these idealizations one at a time, to bring the theory closer to practice. Along the way we have made numerous discoveries through the lens of interference alignment, which reveal new and powerful signaling schemes. According to New York University senior researcher Paul Horn: Syed Jafar revolutionized our understanding of the capacity limits of wireless networks. He demonstrated the astounding result that each user in a wireless network can access half of the spectrum without interference from other users, regardless of how many users are sharing the spectrum. This is a truly remarkable result that has a tremendous impact on both information theory and the design of wireless networks.</p> <a href="https://aizhi.co/html/488a999502.html" class="read-more" title="Interference (communication)">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/135f299862.html" class="card-thumb-link" title="NumPy"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/2/26/Windows_10_Calculator.png" alt="NumPy" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/135f299862.html" title="NumPy">NumPy</a></h2> <p class="article-excerpt">NumPy (pronounced NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications. NumPy is open-source software and has many contributors. NumPy is fiscally sponsored by NumFOCUS. == History == === matrix-sig === The Python programming language was not originally designed for numerical computing, but attracted the attention of the scientific and engineering community early on. In 1995 the special interest group (SIG) matrix-sig was founded with the aim of defining an array computing package; among its members was Python designer and maintainer Guido van Rossum, who extended Python's syntax (in particular the indexing syntax) to make array computing easier. === Numeric === An implementation of a matrix package was completed by Jim Fulton, then expanded to support multi-dimensional arrays by Jim Hugunin and called Numeric (also variously known as the "Numerical Python extensions" or "NumPy"), with influences from the APL family of languages, Basis, MATLAB, FORTRAN, S and S+, and others. Hugunin, a graduate student at the Massachusetts Institute of Technology (MIT), joined the Corporation for National Research Initiatives (CNRI) in 1997 to work on JPython, leaving Paul Dubois of Lawrence Livermore National Laboratory (LLNL) to take over as maintainer. Other early contributors include David Ascher, Konrad Hinsen and Travis Oliphant. === Numarray === A new package called Numarray was written as a more flexible replacement for Numeric. Like Numeric, it too is now deprecated. Numarray had faster operations for large arrays, but was slower than Numeric on small ones, so for a time both packages were used in parallel for different use cases. The last version of Numeric (v24.2) was released on 11 November 2005, while the last version of numarray (v1.5.2) was released on 24 August 2006. There was a desire to get Numeric into the Python standard library, but Guido van Rossum decided that the code was not maintainable in its state then. === NumPy === In early 2005, NumPy developer Travis Oliphant wanted to unify the community around a single array package and ported Numarray's features to Numeric, releasing the result as NumPy 1.0 in 2006. This new project was part of SciPy. To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0. In 2011, PyPy started development on an implementation of the NumPy API for PyPy. As of 2023, it is not yet fully compatible with NumPy. == Features == NumPy targets the CPython reference implementation of Python, which is a non-optimizing bytecode interpreter. Mathematical algorithms written for this version of Python often run much slower than compiled equivalents due to the absence of compiler optimization. NumPy addresses the slowness problem partly by providing multidimensional arrays and functions and operators that operate efficiently on arrays; using these requires rewriting some code, mostly inner loops, using NumPy. Using NumPy in Python gives functionality comparable to MATLAB since they are both interpreted, and they both allow the user to write fast programs as long as most operations work on arrays or matrices instead of scalars. In comparison, MATLAB boasts a large number of additional toolboxes, notably Simulink, whereas NumPy is intrinsically integrated with Python, a more modern and complete programming language. Moreover, complementary Python packages are available; SciPy is a library that adds more MATLAB-like functionality and Matplotlib is a plotting package that provides MATLAB-like plotting functionality. Although MATLAB can perform sparse matrix operations, NumPy alone cannot perform such operations and requires the use of the scipy.sparse library. Internally, both MATLAB and NumPy rely on BLAS and LAPACK for efficient linear algebra computations. Python bindings of the widely used computer vision library OpenCV utilize NumPy arrays to store and operate on data. Since images with multiple channels are simply represented as three-dimensional arrays, indexing, slicing or masking with other arrays are very efficient ways to access specific pixels of an image. The NumPy array as universal data structure in OpenCV for images, extracted feature points, filter kernels and many more vastly simplifies the programming workflow and debugging. Importantly, many NumPy operations release the global interpreter lock, which allows for multithreaded processing. NumPy also provides a C API, which allows Python code to interoperate with external libraries written in low-level languages. === The ndarray data structure === The core functionality of NumPy is its "ndarray", for n-dimensional array, data structure. These arrays are strided views on memory. In contrast to Python's built-in list data structure, these arrays are homogeneously typed: all elements of a single array must be of the same type. Such arrays can also be views into memory buffers allocated by C/C++, Python, and Fortran extensions to the CPython interpreter without the need to copy data around, giving a degree of compatibility with existing numerical libraries. This functionality is exploited by the SciPy package, which wraps a number of such libraries (notably BLAS and LAPACK). NumPy has built-in support for memory-mapped ndarrays. === Limitations === Inserting or appending entries to an array is not as trivially possible as it is with Python's lists. The np.pad(...) routine to extend arrays actually creates new arrays of the desired shape and padding values, copies the given array into the new one and returns it. NumPy's np.concatenate([a1,a2]) operation does not actually link the two arrays but returns a new one, filled with the entries from both given arrays in sequence. Reshaping the dimensionality of an array with np.reshape(...) is only possible as long as the number of elements in the array does not change. These circumstances originate from the fact that NumPy's arrays must be views on contiguous memory buffers. Algorithms that are not expressible as a vectorized operation will typically run slowly because they must be implemented in "pure Python", while vectorization may increase memory complexity of some operations from constant to linear, because temporary arrays must be created that are as large as the inputs. Runtime compilation of numerical code has been implemented by several groups to avoid these problems; open source solutions that interoperate with NumPy include numexpr and Numba. Cython and Pythran are static-compiling alternatives to these. Many modern large-scale scientific computing applications have requirements that exceed the capabilities of the NumPy arrays. For example, NumPy arrays are usually loaded into a computer's memory, which might have insufficient capacity for the analysis of large datasets. Further, NumPy operations are executed on a single CPU. However, many linear algebra operations can be accelerated by executing them on clusters of CPUs or of specialized hardware, such as GPUs and TPUs, which many deep learning applications rely on. As a result, several alternative array implementations have arisen in the scientific python ecosystem over the recent years, such as Dask for distributed arrays and TensorFlow or JAX for computations on GPUs. Because of its popularity, these often implement a subset of NumPy's API or mimic it, so that users can change their array implementation with minimal changes to their code required. A library named CuPy, accelerated by Nvidia's CUDA framework, has also shown potential for faster computing, being a 'drop-in replacement' of NumPy. == Examples == NumPy is conventionally imported as np. === Basic operations === === Universal functions === === Linear algebra === === Multidimensional arrays === === Incorporation with OpenCV === === Nearest-neighbor search === Functional Python and vectorized NumPy version. === F2PY === Quickly wrap native code for faster scripts.</p> <a href="https://aizhi.co/html/135f299862.html" class="read-more" title="NumPy">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/202d999788.html" class="card-thumb-link" title="Extremely online"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/c/cf/Aufnahmeraum.jpeg/960px-Aufnahmeraum.jpeg" alt="Extremely online" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/202d999788.html" title="Extremely online">Extremely online</a></h2> <p class="article-excerpt">An extremely online (often capitalized), terminally online, or chronically online person is someone who is closely engaged with Internet culture. People said to be extremely online often believe that online posts are very important. Events and phenomena can themselves be extremely online; while often used as a descriptive term, the phenomenon of extreme online usage has been described as "both a reformation of the delivery of ideas – shared through words and videos and memes and GIFs and copypasta – and the ideas themselves". Here, "online" is used to describe "a way of doing things, not [simply] the place they are done". == Criteria == While the term was in use as early as 2014, it gained popularity over the latter half of the 2010s in conjunction with the increasing prevalence and notability of Internet phenomena in all areas of life. Extremely online people, according to The Daily Dot, are interested in topics "no normal, healthy person could possibly care about", and have been analogized to "pop culture fandoms, just without the pop". Extremely online phenomena such as fan culture and reaction GIFs have been described as "swallowing democracy" by journalists such as Amanda Hess in The New York Times, who claimed that a "great convergence between politics and culture, values and aesthetics, citizenship and commercialism" had become "a dominant mode of experiencing politics". Vulture – formerly the pop culture section of New York magazine, now a stand-alone website – has a section for articles tagged "extremely online". == Historical background == In the 2010s, many categories and labels came into wide use from media outlets to describe Internet-mediated cultural trends, such as the alt-right, the dirtbag left, and doomerism. These ideological categories are often defined by their close association with online discourse. For example, the term "alt-right" was added to the Associated Press' stylebook in 2016 to describe the "digital presence" of far-right ideologies, the dirtbag left refers to a group of "underemployed and overly online millennials" who "have no time for the pieties of traditional political discourse", and the doomer's "blackpilled despair" is combined with spending "too much time on message boards in high school" to produce an eclectic "anti-socialism". Extreme onlineness transcends ideological boundaries. For example, right-wing figures like Alex Jones and Laura Loomer have been described as "extremely online", but so have those on the left like Alexandria Ocasio-Cortez and fans of the Chapo Trap House podcast. Extremely online phenomena can range from acts of offline violence (such as the 2019 Christchurch shootings) to "[going] on NPR to explain the anti-capitalist irony inherent in kids eating Tide Pods". United States President Donald Trump's posts on social media have been frequently cited as extremely online, during both his presidency and his 2020 presidential campaign; Vox claimed his approach to re-election veered into being "Too Online", and Reason questioned whether the final presidential debate was "incomprehensible to normies". While individual people are often given the description, being extremely online has also been posited as an overall cultural phenomenon, applying to trends like lifestyle movements suffixed with "-wave" and "-core" based heavily on Internet media, as well as an increasing expectation for digital social researchers to have an "online presence" to advance in their careers. == Participants and media coverage == One example of a phenomenon considered to be extremely online is the "wife guy" (a guy who posts about his wife); despite being a "stupid online thing" which spent several years as a piece of Internet slang, in 2019 it became the subject of five articles in leading U.S. media outlets. Like many extremely online phrases and phenomena, the "wife guy" has been attributed in part to the in-character Twitter account dril. The account frequently parodies how people behave on the Internet, and has been widely cited as influential on online culture. In one tweet, his character refuses to stop using the Internet, even when someone shouts outside his house that he should log off. Many of dril's other coinages have become ubiquitous parts of Internet slang. Throughout the 2010s, posters such as dril inspired commonly used terms like "corncobbing" (referring to someone losing an argument and failing to admit it); while originally a piece of obscure Internet slang used on sites like Twitter, use of the term (and controversy over its misinterpretation) became a subject of reporting from traditional publications, with some noting that keeping up with the rapid turnover of inside jokes, memes, and quotes online required daily attention to avoid embarrassment. Twitch has been described as "talk radio for the extremely online". Another example of an event cited as extremely online is No Nut November. Increasingly, researchers are expected to have more of an online presence, to advance in their careers, as networking and portfolios continue to transition to the digital world. In November 2020, an article in The Washington Post criticized the filter bubble theory of online discourse on the basis that it "overgeneralized" based on a "small subset of extremely online people". The 2021 storming of the United States Capitol was described as extremely online, with "pro-Trump internet personalities", such as Baked Alaska, and fans livestreaming and taking selfies. People who have been described as extremely online include Chrissy Teigen, Jon Ossoff, and Andrew Yang. In contrast, Joe Biden has been cited as the antithesis of extremely online—The New York Times wrote in 2019 that he had "zero meme energy".</p> <a href="https://aizhi.co/html/202d999788.html" class="read-more" title="Extremely online">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/217f999773.html" class="card-thumb-link" title="Duck face"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/a/a5/Resilience_Diagram.svg/960px-Resilience_Diagram.svg.png" alt="Duck face" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/217f999773.html" title="Duck face">Duck face</a></h2> <p class="article-excerpt">Duck face or duck lips is a photographic pose that is common on profile pictures in social networks. The lips are pressed together as in a pout and the cheeks are typically also sucked in. The pose is usually seen as an attempt to appear alluring, but it can be ironic or an attempt to hide self-conscious embarrassment. == History == Fashion models frequently use exaggerated pouts, and self-portraits with a pouty face go back to Rembrandt. In the 1994 film Four Weddings and a Funeral, one of the lead characters, Henrietta, played by Anna Chancellor, is nicknamed Duckface for her pouty expressions. Ben Stiller mocked models' pouty expressions in 1996 comedy sketches and the 2001 feature film Zoolander. The silly expressions made by his narcissistic character have retroactively been identified as an example of duck face. As social networks became popular, young women frequently made exaggeratedly pouty expressions. This became a major fad by the 2010s, provoking a strong negative reaction among some viewers. OxfordDictionaries.com added "duck face" as a new word in 2014 to their list of current and modern words, but it has not been added to the Oxford English Dictionary. In an animal communication studies of capuchin monkeys, the "duck face" term has been used synonymously with "protruded lip face", which females exhibit in the proceptive phase before mating.</p> <a href="https://aizhi.co/html/217f999773.html" class="read-more" title="Duck face">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/494d999496.html" class="card-thumb-link" title="Deconfliction line"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/0/05/Hike_Messenger_logo.svg/960px-Hike_Messenger_logo.svg.png" alt="Deconfliction line" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/494d999496.html" title="Deconfliction line">Deconfliction line</a></h2> <p class="article-excerpt">A deconfliction line is an official line of communications established between militaries who are or could be hostile, to avoid dangerous misunderstandings and miscalculations based on ignorance. The ultimate aim is to avoid accidents and conflict escalation. In the 2010s and 2020s, the US and Russia set up deconfliction lines during the Syrian civil war and Russo-Ukrainian War. They were regularly tested by military staff, and used by air traffic controllers and senior military officers. They were used to avoid midair collisions between aircraft in the same or adjacent airspace, and sometimes to give warning of airstrikes. In April 2017, Russia severed the Syrian line in retaliation for a called strike.</p> <a href="https://aizhi.co/html/494d999496.html" class="read-more" title="Deconfliction line">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/95d499900.html" class="card-thumb-link" title="Bayesian programming"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/3/3e/How_mobile_payment_tokenization_works.png/960px-How_mobile_payment_tokenization_works.png" alt="Bayesian programming" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/95d499900.html" title="Bayesian programming">Bayesian programming</a></h2> <p class="article-excerpt">Bayesian programming is a formalism and a methodology for having a technique to specify probabilistic models and solve problems when less than the necessary information is available. Edwin T. Jaynes proposed that probability could be considered as an alternative and an extension of logic for rational reasoning with incomplete and uncertain information. In his founding book Probability Theory: The Logic of Science he developed this theory and proposed what he called "the robot," which was not a physical device, but an inference engine to automate probabilistic reasoning—a kind of Prolog for probability instead of logic. Bayesian programming is a formal and concrete implementation of this "robot". Bayesian programming may also be seen as an algebraic formalism to specify graphical models such as, for instance, Bayesian networks, dynamic Bayesian networks, Kalman filters or hidden Markov models. Indeed, Bayesian programming is more general than Bayesian networks and has a power of expression equivalent to probabilistic factor graphs. == Formalism == A Bayesian program is a means of specifying a family of probability distributions. The constituent elements of a Bayesian program are presented below: Program { Description { Specification ( π ) { Variables Decomposition Forms Identification (based on δ ) Question {\displaystyle {\text{Program}}{\begin{cases}{\text{Description}}{\begin{cases}{\text{Specification}}(\pi ){\begin{cases}{\text{Variables}}\\{\text{Decomposition}}\\{\text{Forms}}\\\end{cases}}\\{\text{Identification (based on }}\delta )\end{cases}}\\{\text{Question}}\end{cases}}} A program is constructed from a description and a question. A description is constructed using some specification ( π {\displaystyle \pi } ) as given by the programmer and an identification or learning process for the parameters not completely specified by the specification, using a data set ( δ {\displaystyle \delta } ). A specification is constructed from a set of pertinent variables, a decomposition and a set of forms. Forms are either parametric forms or questions to other Bayesian programs. A question specifies which probability distribution has to be computed. === Description === The purpose of a description is to specify an effective method of computing a joint probability distribution on a set of variables { X 1 , X 2 , ⋯ , X N } {\displaystyle \left\{X_{1},X_{2},\cdots ,X_{N}\right\}} given a set of experimental data δ {\displaystyle \delta } and some specification π {\displaystyle \pi } . This joint distribution is denoted as: P ( X 1 ∧ X 2 ∧ ⋯ ∧ X N ∣ δ ∧ π ) {\displaystyle P\left(X_{1}\wedge X_{2}\wedge \cdots \wedge X_{N}\mid \delta \wedge \pi \right)} . To specify preliminary knowledge π {\displaystyle \pi } , the programmer must undertake the following: Define the set of relevant variables { X 1 , X 2 , ⋯ , X N } {\displaystyle \left\{X_{1},X_{2},\cdots ,X_{N}\right\}} on which the joint distribution is defined. Decompose the joint distribution (break it into relevant independent or conditional probabilities). Define the forms of each of the distributions (e.g., for each variable, one of the list of probability distributions). ==== Decomposition ==== Given a partition of { X 1 , X 2 , … , X N } {\displaystyle \left\{X_{1},X_{2},\ldots ,X_{N}\right\}} containing K {\displaystyle K} subsets, K {\displaystyle K} variables are defined L 1 , ⋯ , L K {\displaystyle L_{1},\cdots ,L_{K}} , each corresponding to one of these subsets. Each variable L k {\displaystyle L_{k}} is obtained as the conjunction of the variables { X k 1 , X k 2 , ⋯ } {\displaystyle \left\{X_{k_{1}},X_{k_{2}},\cdots \right\}} belonging to the k t h {\displaystyle k^{th}} subset. Recursive application of Bayes' theorem leads to: P ( X 1 ∧ X 2 ∧ ⋯ ∧ X N ∣ δ ∧ π ) = P ( L 1 ∧ ⋯ ∧ L K ∣ δ ∧ π ) = P ( L 1 ∣ δ ∧ π ) × P ( L 2 ∣ L 1 ∧ δ ∧ π ) × ⋯ × P ( L K ∣ L K − 1 ∧ ⋯ ∧ L 1 ∧ δ ∧ π ) {\displaystyle {\begin{aligned}&P\left(X_{1}\wedge X_{2}\wedge \cdots \wedge X_{N}\mid \delta \wedge \pi \right)\\={}&P\left(L_{1}\wedge \cdots \wedge L_{K}\mid \delta \wedge \pi \right)\\={}&P\left(L_{1}\mid \delta \wedge \pi \right)\times P\left(L_{2}\mid L_{1}\wedge \delta \wedge \pi \right)\times \cdots \times P\left(L_{K}\mid L_{K-1}\wedge \cdots \wedge L_{1}\wedge \delta \wedge \pi \right)\end{aligned}}} Conditional independence hypotheses then allow further simplifications. A conditional independence hypothesis for variable L k {\displaystyle L_{k}} is defined by choosing some variable X n {\displaystyle X_{n}} among the variables appearing in the conjunction L k − 1 ∧ ⋯ ∧ L 2 ∧ L 1 {\displaystyle L_{k-1}\wedge \cdots \wedge L_{2}\wedge L_{1}} , labelling R k {\displaystyle R_{k}} as the conjunction of these chosen variables and setting: P ( L k ∣ L k − 1 ∧ ⋯ ∧ L 1 ∧ δ ∧ π ) = P ( L k ∣ R k ∧ δ ∧ π ) {\displaystyle P\left(L_{k}\mid L_{k-1}\wedge \cdots \wedge L_{1}\wedge \delta \wedge \pi \right)=P\left(L_{k}\mid R_{k}\wedge \delta \wedge \pi \right)} We then obtain: P ( X 1 ∧ X 2 ∧ ⋯ ∧ X N ∣ δ ∧ π ) = P ( L 1 ∣ δ ∧ π ) × P ( L 2 ∣ R 2 ∧ δ ∧ π ) × ⋯ × P ( L K ∣ R K ∧ δ ∧ π ) {\displaystyle {\begin{aligned}&P\left(X_{1}\wedge X_{2}\wedge \cdots \wedge X_{N}\mid \delta \wedge \pi \right)\\={}&P\left(L_{1}\mid \delta \wedge \pi \right)\times P\left(L_{2}\mid R_{2}\wedge \delta \wedge \pi \right)\times \cdots \times P\left(L_{K}\mid R_{K}\wedge \delta \wedge \pi \right)\end{aligned}}} Such a simplification of the joint distribution as a product of simpler distributions is called a decomposition, derived using the chain rule. This ensures that each variable appears at the most once on the left of a conditioning bar, which is the necessary and sufficient condition to write mathematically valid decompositions. ==== Forms ==== Each distribution P ( L k ∣ R k ∧ δ ∧ π ) {\displaystyle P\left(L_{k}\mid R_{k}\wedge \delta \wedge \pi \right)} appearing in the product is then associated with either a parametric form (i.e., a function f μ ( L k ) {\displaystyle f_{\mu }\left(L_{k}\right)} ) or a question to another Bayesian program P ( L k ∣ R k ∧ δ ∧ π ) = P ( L ∣ R ∧ δ ^ ∧ π ^ ) {\displaystyle P\left(L_{k}\mid R_{k}\wedge \delta \wedge \pi \right)=P\left(L\mid R\wedge {\widehat {\delta }}\wedge {\widehat {\pi }}\right)} . When it is a form f μ ( L k ) {\displaystyle f_{\mu }\left(L_{k}\right)} , in general, μ {\displaystyle \mu } is a vector of parameters that may depend on R k {\displaystyle R_{k}} or δ {\displaystyle \delta } or both. Learning takes place when some of these parameters are computed using the data set δ {\displaystyle \delta } . An important feature of Bayesian programming is this capacity to use questions to other Bayesian programs as components of the definition of a new Bayesian program. P ( L k ∣ R k ∧ δ ∧ π ) {\displaystyle P\left(L_{k}\mid R_{k}\wedge \delta \wedge \pi \right)} is obtained by some inferences done by another Bayesian program defined by the specifications π ^ {\displaystyle {\widehat {\pi }}} and the data δ ^ {\displaystyle {\widehat {\delta }}} . This is similar to calling a subroutine in classical programming and provides an easy way to build hierarchical models. === Question === Given a description (i.e., P ( X 1 ∧ X 2 ∧ ⋯ ∧ X N ∣ δ ∧ π ) {\displaystyle P\left(X_{1}\wedge X_{2}\wedge \cdots \wedge X_{N}\mid \delta \wedge \pi \right)} ), a question is obtained by partitioning { X 1 , X 2 , ⋯ , X N } {\displaystyle \left\{X_{1},X_{2},\cdots ,X_{N}\right\}} into three sets: the searched variables, the known variables and the free variables. The 3 variables S e a r c h e d {\displaystyle Searched} , K n o w n {\displaystyle Known} and F r e e {\displaystyle Free} are defined as the conjunction of the variables belonging to these sets. A question is defined as the set of distributions: P ( S e a r c h e d ∣ Known ∧ δ ∧ π ) {\displaystyle P\left(Searched\mid {\text{Known}}\wedge \delta \wedge \pi \right)} made of many "instantiated questions" as the cardinal of K n o w n {\displaystyle Known} , each instantiated question being the distribution: P ( Searched ∣ Known ∧ δ ∧ π ) {\displaystyle P\left({\text{Searched}}\mid {\text{Known}}\wedge \delta \wedge \pi \right)} === Inference === Given the joint distribution P ( X 1 ∧ X 2 ∧ ⋯ ∧ X N ∣ δ ∧ π ) {\displaystyle P\left(X_{1}\wedge X_{2}\wedge \cdots \wedge X_{N}\mid \delta \wedge \pi \right)} , it is always possible to compute any possible question using the following general inference: P ( Searched ∣ Known ∧ δ ∧ π ) = ∑ Free [ P ( Searched ∧ Free ∣ Known ∧ δ ∧ π ) ] = ∑ Free [ P ( Searched ∧ Free ∧ Known ∣ δ ∧ π ) ] P ( Known ∣ δ ∧ π ) = ∑ Free [ P ( Searched ∧ Free ∧ Known ∣ δ ∧ π ) ] ∑ Free ∧ Searched [ P ( Searched ∧ Free ∧ Known ∣ δ ∧ π ) ] = 1 Z × ∑ Free [ P ( Searched ∧ Free ∧ Known ∣ δ ∧ π ) ] {\displaystyle {\begin{aligned}&P\left({\text{Searched}}\mid {\text{Known}}\wedge \delta \wedge \pi \right)\\={}&\sum _{\text{Free}}\left[P\left({\text{Searched}}\wedge {\text{Free}}\mid {\text{Known}}\wedge \delta \wedge \</p> <a href="https://aizhi.co/html/95d499900.html" class="read-more" title="Bayesian programming">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/374b999616.html" class="card-thumb-link" title="Virtual DOM"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/ef/Rocchioclassgraph.jpg/960px-Rocchioclassgraph.jpg" alt="Virtual DOM" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/374b999616.html" title="Virtual DOM">Virtual DOM</a></h2> <p class="article-excerpt">A virtual DOM is a lightweight JavaScript representation of the Document Object Model (DOM) used in declarative web frameworks such as React, Vue.js, and Elm. Since generating a virtual DOM is relatively fast, any given framework is free to rerender the virtual DOM as many times as needed relatively cheaply. The framework can then find the differences between the previous virtual DOM and the current one (diffing), and only makes the necessary changes to the actual DOM (reconciliation). While technically slower than using just vanilla JavaScript, the pattern makes it much easier to write websites with a lot of dynamic content, since markup is directly coupled with state. Similar techniques include Ember.js' Glimmer and Angular's incremental DOM. == History == The JavaScript DOM API has historically been inconsistent across browsers, clunky to use, and difficult to scale for large projects. While libraries like jQuery aimed to improve the overall consistency and ergonomics of interacting with HTML, it too was prone to repetitive code that didn't describe the nature of the changes being made well and decoupled logic from markup. The release of AngularJS in 2010 provided a major paradigm shift in the interaction between JavaScript and HTML with the idea of dirty checking. Instead of imperatively declaring and destroying event listeners and modifying individual DOM nodes, changes in variables were tracked and sections of the DOM were invalidated and rerendered when a variable in their scope changed. This digest cycle provided a framework to write more declarative code that coupled logic and markup in a more logical way. While AngularJS aimed to provide a more declarative experience, it still required data to be explicitly bound to and watched by the DOM, and performance concerns were cited over the expensive process of dirty checking hundreds of variables. To alleviate these issues, React was the first major library to adopt a virtual DOM in 2013, which removed both the performance bottlenecks (since diffing and reconciling the DOM was relatively cheap) and the difficulty of binding data (since components were effectively just objects). Other benefits of a virtual DOM included improved security since XSS was effectively impossible and better extensibility since a component's state was entirely encapsulated. Its release also came with the advent of JSX, which further coupled HTML and JavaScript with an XML-like syntax extension. Following React's success, many other web frameworks copied the general idea of an ideal DOM representation in memory, such as Vue.js in 2014, which used a template compiler instead of JSX and had fine-grained reactivity built as part of the framework. In recent times, the virtual DOM has been criticized for being slow due to the additional time required for diffing and reconciling DOM nodes. This has led to the development of frameworks without a virtual DOM, such as Svelte, and frameworks that edit the DOM in-place such as Angular 2. == Implementations == === React === React pioneered the use of a virtual DOM to make components declaratively. Virtual DOM nodes are constructed using the createElement() function, but are often transpiled from JSX to make writing components more ergonomic. In class-based React, virtual DOM nodes are returned from the render() function, while in functional hook-based components, the return value of the function itself serves as the page markup. === Vue.js === Vue.js uses a virtual DOM to handle state changes, but is usually not directly interacted with; instead, a compiler is used to transform HTML templates into virtual DOM nodes as an implementation detail. While Vue supports writing JSX and custom render functions, it's more typical to use the template compiler since a build step isn't required that way. === Svelte === Svelte does not have a virtual DOM, with its creator Rich Harris calling the virtual DOM "pure overhead". Instead of diffing and reconciling DOM nodes at runtime, Svelte uses compile-time reactivity to analyze markup and generate JavaScript code that directly manipulates the DOM, drastically increasing performance.</p> <a href="https://aizhi.co/html/374b999616.html" class="read-more" title="Virtual DOM">Read more →</a> </div> </article> </li> <li class="article-item"> <article class="article-card"> <a href="https://aizhi.co/html/85e999905.html" class="card-thumb-link" title="Event cinema"><img class="card-thumb" src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e3/Linear_least_squares2.svg/960px-Linear_least_squares2.svg.png" alt="Event cinema" loading="lazy"></a> <div class="card-body"> <h2><a href="https://aizhi.co/html/85e999905.html" title="Event cinema">Event cinema</a></h2> <p class="article-excerpt">Event cinema sometimes called alternative content cinema or livecasts refers to the use of movie theaters to display a varied range of live and recorded entertainment excluding traditional films, such as sport, opera, musicals, ballet, music, one-off TV specials, current affairs, comedy and religious services. == History and development == Event Cinema was set up at the start of the century with rock concerts by Bon Jovi (2001), David Bowie (2003), and Robbie Williams (2005) bringing non-film audiences into cinemas that had newly installed digital equipment. The Metropolitan Opera in New York through their partnership with Fathom Events is acknowledged as the trailblazer in this area, aggressively seeking out new markets and setting high standards for live broadcasts via satellite. Emulated by other opera houses worldwide such as the Royal Opera House following a close second, Glyndebourne, La Scala and the Sydney Opera House the genre of opera within the 'Event Cinema' industry has been a huge success, and has brought new, younger audiences into cash-strapped opera houses depended on state funding and wealthy benefactors for the first time - an unforeseen and happy consequence of digitisation. Ballet and theater have also been very successful, as have rock concerts, both live and recorded. The UK's National Theatre has been a huge success here with their season of live broadcasts under the banner 'NT Live', featuring big name casts such as Helen Mirren, whose recent turn as Queen Elizabeth II in The Audience was a sell out everywhere. (This was in partnership with another West End theatre and the NT are keen to help other theatres maximise their potential through live broadcasts). The Globe and the Royal Shakespeare Company are also producing work for live broadcast and recorded exhibition. As digitisation of cinemas matures, the Event Cinema industry is growing. The strongest territory is the US, followed by the UK and mainland European territories. Latin America is also a very strong market. Recent additions include Pompeii Live, a unique exhibition by the UK's British Museum, featuring celebrities and curators taking the audience on a live tour around the recreated set of Pompeii within the museum itself, and they are also exploring the schools market for the first time, following the live broadcast on June 18 with a daytime broadcast aimed at UK schools for the first time. If successful this will no doubt prove a model for future museums to emulate. An added incentive for exhibitors is the ability to show alternative content, i.e. alternative to mainstream, studio-driven content, such as live special events, sports, pre-show advertising and other digital or video content. In industry terms this has become known as 'Alternative Content', but has recently become known more widely as 'Event Cinema'. === Expanding markets === Some low-budget films that would normally not have a theatrical release because of distribution costs might be shown in smaller engagements than the typical large release studio pictures. The cost of duplicating a digital "print" is very low, so adding more theaters to a release has a small additional cost to the distributor. Movies that start with a small release could scale to a much larger release quickly if they were sufficiently successful, opening up the possibility that smaller movies could achieve box office success previously out of their reach. ==== Technical specifications ==== Event Cinema is also finding a market in 3rd world countries in which the higher costs and quality of DCI equipment are not yet affordable, as crucially there are no DCI specifications for Alternative Content as there is in mainstream [studio] content. This has led to an explosion in the variety of content on offer, but a lack of standardisation has led to questionable quality at times. As the industry matures, this lack of regulation is expected to change and there are moves afoot to introduce codes of practice and technical specifications. Recorded content complements mainstream studio content by maximising the 'downtime' that plagues the cinema industry, where screens worldwide spend a large proportion of their time in darkness and cinemas empty. Some cinema chains have targeted pensioners in particular, offering free tea and coffee for afternoon matinees of recorded opera, for example. Digital Cinema Packages (DCPs) have been useful to cinemas not yet equipped with satellite broadcasting capability and has enabled exhibitors to build their Event Cinema audience, which is not generally the 18-24 demographic that multiplexes are targeting. ==== New Audiences ==== Event Cinema has seen a return of an older, affluent audience, previously turned off by the multiplex experience, and cinemas are starting to capitalise on this by offering waiter-serviced, high class finger food and alcoholic beverages, complete with bars and restaurants, a world away from the traditional popcorn/soft drink model; art house cinemas are increasingly marketing themselves as 'destination' venues for an evening's entertainment, somewhere to spend an entire evening, rather than just a couple of hours. As exhibition admissions have plateau'd in recent years due to the explosion in VOD, tablet and mobile content technology, this new revenue stream has been a surprise and welcome addition to the cinema industry, though the US studios have been cautious in embracing the change as yet. The thrill of Live broadcasts means they are generally regarded as more popular than recorded events, but there are exceptions; artists with a loyal cult or teenage following tend to do particularly well in this area, as concert films featuring artists such as the Grateful Dead, Pearl Jam, JLS, Led Zeppelin and the Rolling Stones have shown. ==== The Future ==== As more and more distributors are emerging, offering an increasingly broad range of content to cinemas worldwide, the landscape itself is shifting: screen advertising companies, technical providers, and exhibitors themselves are reinventing themselves as Alternative Content or Event Cinema distributors, and the industry is witnessing a re-evaluation of business models and practices worldwide. Predictions are that this industry could be work in excess of US$1bn by 2015. 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