PHP 7.4 releases with type declarations, shorthand syntax in Arrow functions, and more!

In the month of April, the PHP development team announced the availability of PHP version 7.4. This marks the fourth feature update to the PHP 7 series. PHP 7.4 comes with numerous improvements and new features.

Key features in PHP 7.4

  • Class properties support type declarations.
  • Starting from PHP 7.4, arrow functions will provide a shorthand syntax for defining functions with implicit by-value scope binding
  • The full variance support is only available if autoloading is used by the user. Also, a single file will now only support non-cyclic type references.
  • Numeric literals can contain underscores between digits.
  • Weak references in PHP 7.4 will allow the programmers to retain a reference to an object that does not prevent the object from being destroyed.
  • Users can now throw exceptions from __toString(). This was previously not permitted in PHP as it used to result in a fatal error.
  • The CURLFile now supports stream wrappers in addition to plain file names.
  • The FILTER_VALIDATE_FLOAT filter will support the min_range and max_range options, with the same semantics as FILTER_VALIDATE_INT.
  • A new FFI extension is introduced. It will provide a simple way to call native functions, access native variables, and create/access data structures defined in C libraries.
  • A new IMG_FILTER_SCATTER image filter is added to introduce a scatter filter to images.
We are happy with the new features in PHP 7.4 release.

To know the full list of changes, head over to the PHP archive page. Users can also check out the PHP manual to learn how to migrate from PHP 7.3.x to PHP 7.4.x.

Comments

Post a Comment

Popular posts from this blog

Making open source JavaScript pay

Image
Money isn’t everything to the success of the most popular JavaScript frameworks. Or is it? Looking at the  2019 State of JavaScript report , something stands out: Money apparently can’t buy everything. Or, at least, not every major front-end and back-end programming framework is sponsored by a big company. Sure, we have Google to thank for  Angular , and Facebook gets credit for  React , but what about  Vue.js ? Or Gatsby? Or Next.js? While these (and other) open source projects do seem to suggest a future without Big Corps shoveling Big Money into open source, the reality is a bit more nuanced. For the developers looking to pay their way through open source, however, reality isn’t nuanced at all. For every Vue.js founder  Evan You making $16,000 per month with Patreon contributions , there are thousands of developers struggling to scrape together $16 for the important open source work they’re doing. [  Also on InfoWorld: 15 great alternatives to React, Angular, and Vue  ]
Read more

How artificial intelligence is making the education system more relevant?

Image
Digital learning solutions equipped with artificial intelligence are making revolutionary changes to the way education is imparted in students with varied interests and capabilities. When we think of artificial intelligence, there is a hardwired imagery of gigantic thinking machines working in sci-fi environment. This imagery often comes from the science fiction that we have been watching or reading since childhood. However, deep diving suggests that artificial intelligence is an advanced form of algorithm that empowers machines to emulate human behavior under real life situations. Today, there is no industry untouched by the ripples caused by artificial intelligence. Education sets the foundation of human behavior. Educational ecosystem is formed by knowledge base, teaching skills and experience, learning capability, and evolving teaching methods. Digital learning solutions equipped with artificial intelligence are making revolutionary changes to the way education is im
Read more

Open-source software tracks neural activity in real time

Image
The tool, called CaImAn, replaces the process of manually tracking the location and activity of neurons Tracking the firings of individual neurons is like trying to discern who is saying what in a football stadium full of screaming fans. Until recently, neuroscientists have had to tediously track each neuron by hand. "People spent more time analyzing their data to extract activity traces than actually collecting it," says Dmitri Chklovskii, who leads the neuroscience group at the Center for Computational Biology (CCB) at the Flatiron Institute in New York City. A breakthrough software tool called CaImAn automates this arduous process using a combination of standard computational methods and machine-learning techniques. In a paper published in the journal  eLife  in January, the software's creators demonstrate that CaImAn achieves near-human accuracy in detecting the locations of active neurons based on calcium imaging data. CaImAn (an abbreviation of c
Read more