The Detroit Post
Friday, 15 October, 2021

How Much Data Does Rust Use

Brent Mccoy
• Tuesday, 24 November, 2020
• 8 min read

I've played league with it and it uses about 60 MB for a 30-min game and I have a ping of 80-100. A central place for discussion, media, news and more.

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PlayersGain% Gained PlayersLast 30 Days71531.20+10359.6+16.94%202608 December 2020 61171.655763.61+10.40%97445 November 2020 55408.036857.23+14.12%101365 October 2020 48550.802120.27+4.57%80422 September 2020 46430.53-6857.11-12.87%76611 August 2020 53287.65-4951.07-8.50%89147 July 2020 58238.727821.00+15.51%97741 June 2020 50417.72-6926.93-12.08%93513 May 2020 57344.65-10159.40-15.05%102051 April 2020 67504.059062.03+15.51%125415 March 2020 58442.038366.82+16.71%102296 February 2020 50075.20-1545.19-2.99%92016 January 2020 51620.392525.55+5.14%97340 December 2019 49094.845586.88+12.84%81928 November 2019 43507.96-3196.42-6.84%74292 October 2019 46704.38-2931.73-5.91%82827 September 2019 49636.12-8895.12-15.20%80293 August 2019 58531.24-3728.72-5.99%88929 July 2019 62259.9617127.39+37.95%93595 June 2019 45132.579351.90+26.14%81658 May 2019 35780.66-2420.12-6.34%67338 April 2019 38200.78-2524.51-6.20%72544 March 2019 40725.29-1706.13-4.02%77896 February 2019 42431.42-3769.88-8.16%77622 January 2019 46201.303579.02+8.40%85208 December 2018 42622.284915.93+13.04%70775 November 2018 37706.365886.14+18.50%70969 October 2018 31820.224501.02+16.48%58564 September 2018 27319.20-4169.08-13.24%48430 August 2018 31488.28-5170.92-14.11%53885 July 2018 36659.196350.30+20.95%65952 June 2018 30308.906415.11+26.85%54779 May 2018 23893.78-2153.26-8.27%46328 April 2018 26047.04-3027.77-10.41%51233 March 2018 29074.81-4432.46-13.23%57873 February 2018 33507.28-1161.53-3.35%68204 January 2018 34668.811694.81+5.14%67410 December 2017 32974.004826.77+17.15%60373 November 2017 28147.232386.73+9.27%57223 October 2017 25760.504165.09+19.29%49984 September 2017 21595.41-3962.61-15.50%40577 August 2017 25558.02-4005.08-13.55%43117 July 2017 29563.10277.67+0.95%53425 June 2017 29285.433905.15+15.39%48228 May 2017 25380.27-3208.53-11.22%46948 April 2017 28588.81-3850.18-11.87%53621 March 2017 32438.98-3964.56-10.89%66194 February 2017 36403.552403.64+7.07%68103 January 2017 33999.915024.99+17.34%63843 December 2016 28974.926095.72+26.64%49147 November 2016 22879.20-1526.98-6.26%47571 October 2016 24406.17-1863.62-7.09%48435 September 2016 26269.79-4162.74-13.68%50680 August 2016 30432.53-517.22-1.67%50364 July 2016 30949.755588.78+22.04%64555 June 2016 25360.97-136.91-0.54%45791 May 2016 25497.88-108.06-0.42%47100 April 2016 25605.94-1661.66-6.09%49920 March 2016 27267.60-5126.97-15.83%55147 February 2016 32394.574747.51+17.17%61260 January 2016 27647.069173.00+49.65%50628 December 2015 18474.065412.43+41.44%38110 November 2015 13061.63-44.48-0.34%26697 October 2015 13106.11695.25+5.60%24201 September 2015 12410.86-2459.21-16.54%24075 August 2015 14870.061052.36+7.62%25352 July 2015 13817.7182.06+0.60%22622 June 2015 13735.65-84.17-0.61%27177 May 2015 13819.825683.08+69.84%25625 April 2015 8136.74-133.76-1.62%16636 March 2015 8270.49-1102.20-11.76%16341 February 2015 9372.69-1218.37-11.50%20267 January 2015 10591.064439.66+72.17%22303 December 2014 6151.40767.28+14.25%11826 November 2014 5384.12-988.43-15.51%12062 October 2014 6372.5525.86+0.41%12294 September 2014 6346.70-2393.85-27.39%11040 August 2014 8740.55-1391.93-13.74%12764 July 2014 10132.47-1805.76-15.13%15027 June 2014 11938.23-1212.72-9.22%18081 May 2014 13150.96-4508.02-25.53%24306 April 2014 17658.98-7215.16-29.01%31321 March 2014 24874.13-9879.31-28.43%48870 February 2014 34753.459878.63+39.71%58973 January 2014 24874.8215669.05+170.21%51872 December 2013 9205.77--22571 All trademarks are property of their respective owners in the US and other countries.

View Entire Discussion (2 Comments)More posts from the play rust community A central place for discussion, media, news and more.

For online gaming of these sorts you can generally expect around 100-150mb per an hour. Over the last month, almost all capable organizations and educational institutions have sought the assistance of various video calling or conferencing software.

While applications like Skype and Google Duo are fully capable of hosting small meetings, they don’t quite serve the purpose if the number of participants crosses 50. Zoom, like Microsoft Teams and Hangouts Meet, is a remote video conferencing platform.

An application that uses video and audio is bound to consume a lot of data, which is a big problem for people required to stay under a monthly cap. It allows us to connect to our friends and colleagues in a heartbeat and keep the operations running as smoothly as possible.


However, since it’s a video conferencing application, it’s a little hard on people with limited data plans and slower connections. In this section, we’ll take a look at exactly how much data Zoom consumes during a 1:1 or group video call.

Finally, the highest quality, Full HD, would hurt your data balance the most. For a healthy balance of quality and economy, we recommend 720P video calling on Zoom.

Translating those speeds to rough numbers, you’re looking at around 360 MB of upload and 450 MB of download per hour, bringing the total to 810 MB. Zoom requires 1.5mbps download and upload speeds for 720P calling or Gallery View.

Since it’s pretty much unnecessary to host Full HD conference calls, we hope you’d be able to steer clear of this one. Screen sharing is another important aspect of Zoom, but it’s hardly as resource hungry as the other two.

Well, here are various ways to make your mobile data last for a long time on Zoom video calls, which is especially helpful when you have got a bunch of games to play. That way, you’ll save a chunk of data and won’t experience lag or stutters while in a meeting.

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Simply go to Zoom’s official portal, hover your mouse over to ‘ Host a Meeting ‘ and click on ‘ With video off.’ Depending on your hardware or internet connection, HD video might already be turned off, by default.

To double-check, open the Zoom desktop client, go to Settings, navigate to the ‘ Video ‘ tab, and uncheck ‘ Enable HD ‘. The aim of this tutorial is to take you to a place where you can read and write enough Rust to fully appreciate the excellent learning resources available online, in particular The Book.

There is a lot of new stuff to learn here, and it's different enough to require some rearrangement of your mental furniture. By 'gentle' I mean that the features are presented practically with examples; as we encounter difficulties, I hope to show how Rust solves these problems.

To put it in flowery language, we are going for a hike in hilly country and I will point out some interesting rock formations on the way, with only a few geology lectures. Even if you do not immediately land a cool job using that language, it stretches the mental muscles and makes you a better programmer.

That seems a poor kind of return-on-investment but if you're not learning something genuinely new all the time then you will stagnate and be like the person who has ten years of experience in doing the same thing over and over. The big difference from C and C++ is that Rust is safe by default ; all memory accesses are checked.

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This gets the compiler, the Cargo package manager, the API documentation, and the Rust Book. I'd suggest you start out with basic syntax highlighting at first, and work up as your programs get larger.

Personally I'm a fan of Meany which is one of the few editors with Rust support out-of-the-box; it's particularly easy on Linux since it's available through the package manager, but it works fine on other platforms. The main thing knows how to edit, compile and run Rust programs.

Zed Shaw's advice about learning to program in Python remains good, whatever the language. There's also good advice from Yoga and the soft martial arts like Tai Chi; feel the strain, but don't over-strain.

Kubernetes is used quite extensively to run cloud software across many vendors and companies and is primarily written in the Go programming language. Recent work has enabled compiled Was binaries (called modules) to be run on any system.

But after we started to get a better understanding of how to code things, we realized how many bugs and problems the compiler was saving us from. After a month, we all were comfortable enough that we were back up to full efficiency (in terms of how much code we could write).

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However, we noticed that we gained productivity in the sense that we didn’t spend as much time manually checking specific conditions, like null pointers, or not having to debug as many problems (I’ll cover that some more below). Occasionally, we run into a more complex case that takes us longer to figure out than it would with other languages.

Rustle is responsible for running arbitrary numbers of Was modules in parallel. Even though we sometimes miss having a garbage collector, so we don’t have to worry about cloning, borrowing, ownership, etc., the pain we have avoided because of the Rust compiler’s strict rules is incalculable.

Because of the large amount of customization (at least in Kubernetes) with custom data types and the distributed nature of cloud computing, having these protections and safety guarantees at the compiler level gives us great confidence in the code we are writing. In addition, having a strong type system that still allows for extensibility (in the form of traits, which the Rust docs describe as the ability “to define shared behavior in an abstract way” and bind generic parameters to that behavior) is incredibly useful and flexible for projects that need to handle multiple custom data types in similar ways.

In short, the flexibility, safety, and security of Rust outweighs any inconvenience of having to follow strict lifetime, borrowing, and other compiler rules or even the lack of a garbage collector. These features are a much -needed addition to cloud software projects and will help avoid many bugs commonly found in them.

We also learned of a few gotchas that we consider important to point out as you make the decision of whether to users for a new cloud software project. Rust has made great progress in the past year with its asynchronous story, but there are still some issues that are being worked out.

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However, that hard effort up front pays off in dividends due to the aforementioned safety features. We also noticed that once developers are over that initial curve, they are able to contribute to code just as easily as with any other language.

All languages have their trade offs, but we feel the benefits gained outweigh any of these pain points. It’s important to give up the idea that “we must accomplish something in an amount of time.” Only with the sigh of relief that comes from liberating yourself from goals is your brain allowed to float to the most interesting places.

My friend Jeremy Cerise, who comes to most of these retreats, said that he had become re-interested in the Rust language and wanted to explore it. I was skeptical, but I’ve found that if Jeremy is interested in something, there’s probably something there, so Rust was worth a second look.

We had both gotten COVID-19 at the Winter Tech Forum in March, so it seemed like we could probably spend time together reasonably safely. To do that, it provides as much language and compiler support as possible to guarantee that you don’t mismanage your memory, because you’re doing it all by hand.

They liberate programmers to focus on the problem at hand rather than being forced to pay attention to low-level details. Any Rust code you look at leaves a metallic taste in your mouth of being right next to the hardware.

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That awareness of hardware is ever-present, and for that reason I’ve started calling Rust a “very-high-level assembly language.” I don’t think I’ve seen anything that comes close to Rust for solving the problem of writing low-level code.

So we wondered whether Rust might be a good solution for speeding up slow parts of a Python program. We started with this article, but couldn’t get it to work because of what turned out to be a simple renaming problem that doesn’t seem to be mentioned anywhere.

Upon giving up, we discovered PyO3, which beautifully solves most or all of the setup for interfacing Python and Rust. A core part of CORBA was the goal of making language-agnostic function calls across networks.

In most RPC protocols you describe data and functions using an interface description language (IDL). An IDL is like a restricted programming language that can only describe data structures and function interfaces.

The Object Management Group that created CORBA was (at least at the time) bogged down with bureaucracy and was controlled predominantly by the larger organizations that could pay the costs of being on that committee. My first experience of creating a CORBA system didn’t happen until it was available (and easy) on Python.


The specification-first, design-by-special-interests approach floundered for a long time and never gained traction, despite huge investments in creating and promoting it. Other RPC systems learned from CORBA’s mistakes; in particular the need for implementations and supporting tools.

And consider Google’s massive system: tiny amounts of memory or delays could produce immense impacts. However, if Go has features you want, even with the speed differences with Rust, it could still be so much faster than what you were trying to do in Python that it might never be an issue.

If you already understand Go and are comfortable with it and don’t have time to delve into Rust right now, then Go and GRC will almost certainly solve your problem. But if you know from the start that squeezing out every drop of performance is essential, then you want Rust for your Python extension.

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