Every month Epic Games give away several free items from the Unreal Engine marketplace and this month is no exception.  There are 5 items that are yours free forever, so long as you “purchase” them before the first Tuesday of next month.  There is also one permanently free item.  In addition to this months giveaways, Epic are running a 50% off Flash sale until March 6th.

This months free content includes:

Free For March

• Ability Pack – Time and Space
• Android Native Goodies
• FPS Assault Pack
• Phoenyx Anim Pack 3
• Ultimate Archvis Kit

Free Forever

You can learn more about the giveaway in the video below.

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GameDev News Unreal

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When I was brought on as head coach of the Cleveland team, it was out of desperation. It was a tragedy of a team that couldn’t muster a winning record. No veteran players in their right mind would have wanted to be traded there. Rookies lived in fear that they would be drafted there, ending their career before it started. Cleveland football was a disaster.

Now, six years later, fans enthusiastically pile into the stadium every game to power our team into the playoffs. We have a consistent, league leading offense that can score on any drive. Rookies come to Cleveland looking to become a franchise player and lead this team to dynastic greatness. We’re no longer an afterthought, we’re inevitable. Next stop: the Retro Bowl.

This isn’t the engagement I’d expect from such a small game. Retro Bowl aims to create an American football simulator to rival that of genre juggernaut, Madden. It can’t possibly compete with that entire video game empire, one who’s entire look and feel is so influential that the real life sport has been jacking it’s style for years. But when you consider it’s scale, and the platform it’s limited to, Retro Bowl is special. It has no peers when it comes to mobile football games – including the Madden ports and downscaled efforts that pepper the App Store yearly.

Where it succeeds is it’s clever mix of team management simulation and focused gameplay. Before the games, you manage things like team rosters, player morale, coaches, and facility quality. This kind of granular micro-management can be tedious though, so Retro Bowl only includes the things that matter. Your team has enough players to field for a full game, but you only manage the stars. Keeping a select few players happy and healthy is enough to keep all the random no name role-players in line.

I find that this mimics lots of sports mentality pretty well. On real football teams, everyone is an individual, of course. But anyone who isn’t an analyst will rarely weigh the strength or potential of a team using anything but how good their standouts are. The New England Patriots are synonymous with QB Tom Brady and not Kicker Steve Gostkowski for a reason. Possible proliferation of the sports-forward mentality that reduces people to mindless human capital aside, Retro Bowl can be appreciated for being realistic about how we interact with sports with this design choice.

These star players can also improve while on your team. They gain experience every time you play, and leveling up allows them to raise some stats up to a projected maximum. When new players come to you via draft or trade, they’ll have two ratings – one for what they are now, and one for what they can potentially be. There’s a lot of strategy in managing this simple roster season to season. Do you keep the solid 3 star player knowing that that is as good as they get? Do you trade them for a 2 star that can become a 4 and a half in a couple of seasons? How does your salary cap fit into this?

When it’s time to hit the field, Retro Bowl takes a lot of shortcuts, as well. You have two options on every play: throw the ball to a receiver or toss the ball to a running back. By dragging back on the screen, you’ll see the trajectory of your throw, and can aim the pass at will. After the ball is caught, you can avoid defenders with quick swipes up or down, or swipe forward to dive for more yards. All of these things work reasonably well, and are modified heavily by the player’s stats. A running back with low stamina can juke way fewer times before they start running at a snail’s pace. A quarterback with low throw accuracy has a short trajectory line, making it hard to predict exactly where the ball will go.

This scaled down system is fun and simple. You can’t move your QB around the pocket during a play, but watching your receivers struggle to get open while feeling that encroaching pressure of a defensive line caving in successfully translates that pocket pressure that makes big plays so satisfying. How reliable things like catching and fumbling are depends on the quality of your players, but more than once have I had a really good wide receiver have a ball just bounce off of their helmet while they stand wide open down field.

That sort of randomness is everywhere in Retro Bowl. For example, you can’t call your own plays. At the beginning of a play, you see patterns laid out for you, and you can only choose to throw it or run it. There’s no telling how the game has come to call this play. Does it take into account the defense? Does having a better offensive coordinator determine what kinds of plays get called? I think taking the minute elements of play calling out (audibles, play action) is fine, but being locked into a play that looks no good, without any understanding of why it was called and no option to change it, feels bad. Especially if you only have average offensive tools at your disposal.

There’s also absolutely no defensive plays. Defense is played out via a series of text boxes that give you a gist of how the rival team’s drive is going. The success of your defense is determined by how good your overall defense is. That’s determined by the quality of your defensive players and coordinators. But it always feels like a crap shoot. When opposing teams have average or higher offenses, you’ll do best to assume that every time they have the ball, they’ll score. It reminds me of blackjack, where your best bet is to assume that the dealer’s face down card is a 10 at all times. Gambling also feels bad.

The stripped down features and mechanics are a good way to translate football sim experience to the small screen. The extreme lack of information and abundant RNG make for a game that is hard to fully engage with. All that said, if you want football in quick doses, and that head coach management experience from the big boys on the go, you’ll be hard pressed to find a better alternative than Retro Bowl.

It’s not often that we hear about an indie game coming to Switch three years before its planned release date, but that’s the exact situation we find ourselves in with Nocturne.

This story-driven rhythm RPG has just seen its ‘Prelude’ – essentially the first chapter of the game – launch on Steam today, alongside news of a promised 2023 launch for the full game on both Steam and Switch. It’s set in a dystopian future where humanity lives in a digital afterlife, as explained in this official description:

Humanity is extinct, but an echo of civilization lives on. Maya, the fabled utopian afterlife where people abandon their corporeal forms in favour of an eternal existence with loved ones in a digital world, is not all as it seems. Decay and corruption await Karma, the world’s first newcomer in thousands of years, and derails a desperate attempt to reunite with their missing brother on the other side.

Befriend a charmingly quirky crew like a wise orange fish in monk garb and a headstrong little boy to unravel the mysteries of the Blackout, an enigmatic catalyst that triggered Maya’s plunge into chaos. Test the limits of human existence, exposing an insidious threat lurking among the remains of humanity.

Players will need to march to the beat of battle, taking on traditional RPG-style combat blended with “intense” rhythm battles. You’ll be tapping along to a progressive symphonic rock soundtrack, dodging dangerous notes and watching out for other surprises.

If you’re liking the sound of it, we hope you can deal with that three-year wait. Feel free to share any thoughts you might have on it in the comments below.

The web is full of tutorials about regular expressions. But I realized that most of those tutorials lack a thorough motivation.

• Why do regular expressions exist?
• What are they used for?
• What are some practical applications?

Somehow, the writers of those tutorials believe that readers are motivated by default to learn a technology that’s complicated and hard to learn.

Well, readers are not. If you’re like me, you tend to avoid complexity and you first want to know WHY before you invest dozens of hours learning a new skill. Is this you? Then keep reading. (Otherwise, leave now—and don’t tell me I didn’t warn you.)

So what are some applications of regular expressions?

As you read through the article, you can watch my explainer video:

Here’s the ToC that also gives you a quick overview of the regex applications:

Search and Replace in a Text Editor

The most straightforward application is to search a given text in your text editor. Say, your boss asks you to replace all occurrences of a customer 'Max Power' with the name 'Max Power, Ph.D.,'.

Here’s how it would look like:

I used the popular text editor Notepad++ (recommended for coders). At the bottom of the “Replace” window, you can see the box selection “Regular expression”. But in the example, we used the most straightforward regular expression: a simple string.

So you search and replace all occurrences of the string ‘Max Power’ and give it back to your boss. But your boss glances over your document and tells you that you’ve missed all occurrences with only 'Max' (without the surname 'Power'). What do you do?

Simple, you’re using a more powerful regex: 'Max( Power)?' rather than only 'Max Power':

Don’t worry, it’s not about the specific regex 'Max( Power)?' and why it works. I just wanted to show you that it’s possible to match all strings that either look like this: 'Max Power' or like this: 'Max'.

Anyways, if you’re interested, you can read about the two regex concepts on the Finxter blog: matching groups and the question mark operator.

Searching Your Operating System for Files

This is another common application: use regular expressions to search (and find) certain files on your operating system.

For example, this guy tried to find all files with the following filename patterns:

abc.txt.r12222

tjy.java.r9994

He managed to do it on Windows using the command:

dir * /s/b | findstr \.r[0-9]+$

Large parts of the commands are a regular expression. In the final part, you can already see that he requires the file to end with .r and an arbitrary number of numeric symbols.

As soon as you’ve mastered regular expressions, this will cost you no time at all and your productivity with your computer will skyrocket.

Searching Your Files for Text

But what if you don’t want to find files with a certain filename but with a certain file content? Isn’t this much harder?

As it turns out, it isn’t! Well, if you use regular expression and grep.

Here’s what a grep guru would do to find all lines in a file 'haiku.txt' that contain the word 'not'.

Grep is an aged-old file search tool written by famous computer scientist Ken Thompson. And it’s even more powerful than that: you can also search a bunch of files for certain content.

A Windows version of grep is the find utility.

Search Engines

Well, using regular expressions to find content on the web is considered the holy grail of search. But the web is a huge beast and supporting a full-fledged regex engine would be too demanding for Google’s servers. It costs a lot of computational resources. Therefore, nobody actually provides a search engine that allows all regex commands.

However, web search engines such as Google support a limited number of regex commands. For example, you can search queries that do NOT contain a specific word:

The search “Jeff -Bezos” will give you all the Jeff’s that do not end with Bezos. If a firstname is dominated like this, using advanced search operators is quite a useful extension.

Here’s an in-depth Google search guide that shows you how to use advanced commands to search the huge web even faster.

With the explosion of data and knowledge, mastering search is a critical skill in the 21st century.

Validate User Input in Web Applications

If you’re running a web application, you need to deal with user input. Often, users can put anything in the input fields (even cross-site scripts to hack your webserver). Your application must validate that the user input is okay—otherwise you’re guaranteed to crash your backend application or database.

How can you validate user input? Regex to the rescue!

Here’s how you’d check whether

• The user input consists only of lowercase letters: [a-z]+,
• The username consists of only lowercase letters, underscores, or numbers: [a-z_0-9]+, or
• The input does not contain any parentheses: [^\(\)]+.

With regular expressions, you can validate any user input—no matter how complicated it may seem.

Think about this: any web application that processes user input needs regular expressions. Google, Facebook, Baidu, WeChat—all of those companies work with regular expressions to validate their user input. This skill is wildly important for your success as a developer working for those companies (or any other web-based company for that matter).

Guess what Google’s ex tech lead argues is the top skill of a programmer? You got it: regular expressions!

Extract Useful Information With Web Crawlers

Okay, you can validate user input with regular expressions. But is there more? You bet there is.

Regular expressions are not only great to validate textual data but to extract information from textual data.

For example, say you want to gain some advantage over your competition. You decide to write a web crawler that works 24/7 exploring a subset of webpages. A webpage links to other webpages. By going from webpage to webpage, your crawler can explore huge parts of the web—fully automatized.

Imagine the potential! Data is the asset class of the 21st century and you can collect this valuable asset with your own web crawler.

A web crawler can be a Python program that downloads the HTML content of a website:

Your crawler can now use regular expressions to extract all outgoing links to other websites (starting with "<a href=").

A simple regular expression can now automatically get the stuff that follows—which is the outgoing URL. You can store this URL in a list and visit it at a later point in time.

As you’re extracting links, you can build a web graph, extract other information (e.g., embedded opinions of people) and run complicated subroutines on parts of the textual data (e.g., sentiment analysis).

Don’t underestimate the power of web crawlers when used in combination with regular expressions!

Data Scraping and Web Scraping

In the previous example, you’ve already seen how to extract useful information from websites with a web crawler.

But often the first step is to simply download a certain type of data from a large number of websites with the goal of storing it in a database (or a spreadsheet). But the data needs to have a certain structure.

The process of extracting a certain type of data from a set of websites and converting it to the desired data format is called web scraping.

Web scrapers are needed in finance startups, analytics companies, law enforcement, eCommerce companies, and social networks.

Regular expressions help greatly in processing the messy textual data. There are many different applications such as finding titles of a bunch of blog articles (e.g., for SEO).

A minimal example of using Python’s regex library re for web scraping is the following:

from urllib.request import urlopen

import re html = urlopen("https://blog.finxter.com/start-learning-python/").read() print(str(html))

titles = re.findall("\<title\>(.*)\</title\>", str(html)) print(titles)

# ['What's The Best Way to Start Learning Python? A Tutorial in 10 Easy Steps! | Finxter']

You extract all data that’s enclosed in opening and closing title tags: <title>...</title>.

Data Wrangling

Data wrangling is the process of transforming raw data into a more useful format to simplify the processing of downstream applications. Every data scientists and machine learning engineer knows that data cleaning is at the core of creating effective machine learning models and extracting insights.

As you may have guessed already, data wrangling is highly dependent on tools such as regular expression engines. Each time you want to transform textual data from one format to another, look no further than regular expressions.

In Python, the regex method re.sub(pattern, repl, string) transforms a string into a new one where each occurrence of pattern is replaced by the new string repl. You can learn everything about the substitution method on my detailed blog tutorial (+video).

This way, you can transform currencies, dates, or stock prices into a common format with regular expressions.

Parsing

Show me any parser and I show you a tool that leverages hundreds of regular expressions to process the input quickly and effectively.

You may ask: what’s a parser anyway? And you’re right to ask (there are no dumb questions). A parser translates a string of symbols into a higher-level abstraction such as a formalized language (often using an underlying grammar to “understand” the symbols). You’ll need a parser to write your own programming language, syntax system, or text editor.

For example, if you write a program in the Python programming language, it’s just a bunch of characters. Python’s parser brings order into the chaos and translates your meaningless characters into more meaningful abstractions (e.g. keywords, variable names, or function definitions). This is then used as an input for further processing stages such as the execution of your program.

If you’re looking at how parsers are implemented, you’ll see that they heavily rely on regular expressions. This makes sense because a regular expression can easily analyze and catch parts of your text. For example, to extract function names, you can use the following regex in your parser:

import re code = '''

def f1(): return 1 def f2() return 2 ''' print(re.findall('def ([a-zA-Z0-9_]+)', code))

# ['f1', 'f2']

You can see that our mini parser extracts all function names in the code. Of course, it’s only a minimal example and it wouldn’t work for all instances. For example, you can use more characters than the given ones to define a function name.

If you’re interested in writing parsers or learning about compilers, regular expressions are among the most useful tools in existence!

Programming Languages

Yes, you’ve already learned about parsers in the previous point. And parsers are needed for any programming language. To put it bluntly: there’s no programming language in the world that doesn’t rely on regular expressions for their own implementation.

But there’s more: regular expressions are also very popular when writing code in any programming language. Some programming languages such as Perl provide built-in regex functionality: you don’t even need to import an external library.

I assure you, if you’re becoming a professional coder, you will use regular expressions in countless of coding projects. And the more you use it, the more you’ll learn to love and appreciate the power of regular expressions.

Syntax Highlighting Systems

Here’s how my standard coding environment looks like:

Any code editor provides syntax highlighting capablities:

• Function names may be blue.
• Strings may be yellow.
• Comments may be red.
• And normal code may be white.

This way, reading and writing code becomes far more convenient. More advanced IDEs such as PyCharm provide dynamic tooltips as an additional feature.

All of those functionalities are implemented with regular expressions to find the keywords, function names, and normal code snippets—and, ultimately, to parse the code to be highlighted and enriched with additional information.

Lexical Analysis in a Compiler

In compiler design, you’ll need a lexical analyzer:

The lexical analyzer needs to scan and identify only a finite set of valid string/token/lexeme that belong to the language in hand. It searches for the pattern defined by the language rules.

Regular expressions have the capability to express finite languages by defining a pattern for finite strings of symbols. The grammar defined by regular expressions is known as regular grammar. The language defined by regular grammar is known as regular language.

Source

As it turns out, regular expressions are the gold standard for creating a lexical analyzer for compilers.

I know this may sound like a very specific application but it’s an important one nonetheless.

Formal Language Theory

Theoretical computer science is the foundation of all computer science. The great names in computer science, Alan Turing, Alonzo Church, and Steven Kleene, all spent significant time and effort studying and developing regular expressions.

If you want to become a great computer scientist, you need to know your fair share of theoretical computer science. You need to know about formal language theory. You need to know about regular expressions that are at the heart of these theoretical foundations.

How do regular expressions relate to formal language theory? Each regular expression defines a “language” of acceptable words. All words that match the regular expression are in this language. All words that do not match the regular expression are not in this language. This way, you can create a precise sets of rules to describe any formal language—just by using the power of regular expressions.

Where to Go From Here?

Regular expressions are widely used for many practical applications. The ones described here are only a small subsets of the ones used in practice. However, I hope to have given you a glance into how important and relevant regular expressions have been, are, and will remain in the future.

Want to learn more about how to convert your computer science skills into money? Check out my free webinar that shows you a step-by-step approach to build your thriving online coding business (working from home). You don’t need to have any computer science background though. The only thing you need is the ambition to learn.

Click: https://blog.finxter.com/webinar-freelancer/

Need some more stability?

• 
• by Liam Doolan 8 hours ago

Organizations around the world are going through rapid digital transformation. This is especially true in the US Market, where we see this phenomena being accelerated by the scale and agility of the Cloud and fueled by the latest innovation in machine learning and artificial intelligence. As they progress through their transformations and examine impacts on employees, partners, customers, and society, new strategies are emerging with socio-environmental factors with sustainability at the center.

We’re just at the beginning of what is possible with AI, endless possibilities not only for companies and partners but for everyone to benefit from improved societal impact, social good and sustainability. All requiring the need for a strong ecosystem and strategic private & public partnerships to build a trusted and secure future with new AI innovations and solutions. I’m delighted to share I’ve taken a new role at Microsoft to address both of these challenges: Vice President, AI Country Strategy & Sustainability Partnership for the US Microsoft Subsidiary. Focused on driving cross-boundary collaboration and transformation at scale, my new team and I will build strategies and partnerships that strengthen Microsoft’s position in the US as the leader in Cloud & AI, and leverage that knowledge into delivering in the US on Microsoft’s sustainability promise to be carbon negative by 2030.

Microsoft is making big, strategic bets on Cloud & AI and I look forward to driving digital transformation the US with a holistic view of the partner ecosystem—from customers and partners to developers and other strategic partnerships. Through the development of private and public partnerships we will drive technology innovation and ecosystem activation and begin to utilize Microsoft’s $1B investment in support of sustainability agendas across the US.

I have always been passionate about building teams that help shape the future of new technologies; and this new role creates the connections and opportunities for expansion of Microsoft’s mission to empower people, and drive growth and economic prosperity at a global level. The chance to leverage AI and sustainability to help us solve the world’s most vexing challenges is an opportunity for us all—and I’m grateful to be at a company that supports this mission.

While this will be a transition from my current charter in leading Go-To-Markets as a strategic advantage for Microsoft’s commercial partners, I’m excited to see the role the Microsoft community and its tens of thousands of partners will play in driving the future of AI and sustainability.

If you’re interested in learning more about how we are partnering with customers, commercial partners, developers, students and startups, follow along!

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