SteamKit VS runninginproduction.com

So I will be making a client-side mod to show mmr changes as in the old client Upcoming data will be stored locally in the cfg folder (per account i.e. cloud synced) Wont know about matches played before adding the mod (valve went scorched earth removing data points from client.dll) But can populate previous history via an external opensource tool based on SteamKit samples

Or also you can check this or this github repositories, which emulate steam client (Or any other, there are lots of them)

Depends on what language you're using for JavaScript I think the defacto is anything Doctor McKay makes https://github.com/DoctorMcKay/node-steam-user, https://github.com/DoctorMcKay/node-steam-user etc. If you use python, I'd recommend https://github.com/Gobot1234/steam.py (I'm totally not biased). If you use C# then SteamKit is always a good option. If you use rust then SteamHelper looks interesting although doesn't support too many trading bot features

Me: Okay. I'm just going to prototype a game. Don't want to get carried away. I won't even write a game engine. I'll use Tabletop Simulator.

Friend: Sounds good. How's it going?

Me: Well. I needed to be able to debug my code. https://github.com/tts-community/moonsharp-tts-debug

Friend: Oh, neat. So your game is done now?

Me: Not exactly. I had to had in matchmaking by reverse engineering Steam. https://github.com/SteamRE/SteamKit/pull/704

Friend: Ah. Alright. Can I play it now?

Me: Nah, I was finding it hard to maintain code. I wrote a Lua code bundler. https://github.com/Benjamin-Dobell/luabundle

Friend: Sweet.

Me: Yeah, but I decided to integrate it into the official tooling. https://github.com/Berserk-Games/atom-tabletopsimulator-lua/...

Friend: I'm sure the community will be thankful.

Me: I hope so. I now run a small community of TTS developers. https://github.com/tts-community/

Friend: Right. You must be done by now.

Me: Nah, I couldn't statically type check my code. So I wrote some types. https://github.com/Benjamin-Dobell/tts-types

Friend: Seems unnecessary for a prototype, but sure.

Me: I had to write my own IDE to use them though. https://github.com/Benjamin-Dobell/IntelliJ-Luanalysis

Friend: Right... So how'd the game going then?

Me: Oh, I'm not doing that anymore. I now consult for Berserk Games, developers of Tabletop Simulator

Friend: ...

I don't know any direct resources for learning how the Steam network works, smart people figured it out over many years and lots of reverse engineering. I just know a few programming libraries which you can use to interact with it, the most popular two being Steam-User (JavaScript) and SteamKit2 (.NET).

It's possible to do it through Steam's internal protocol, you probably want to use SteamKit2 here.

A while back I started a podcast around this topic: https://runninginproduction.com/

If there's ever a time to ask such a question, it might be this thread.

Can I get some brutally honest feedback on a podcast I ran for 2 years (100+ episodes at once per week)) at https://runninginproduction.com/? It's a podcast focused on chatting with developers around how they build and deploy their web apps. It mostly focuses on the "why", tech stack choices, libraries, workflows, etc..

In my mind I thought it was a good idea but it got so little listeners that I had to abort recording new episodes due to burn out since there was no path forward to ever sustain it by outsourcing the burn out inducing parts. I still think it's a good idea but I wonder where I went wrong.

I tried everything I could think of. Guest variety from solo devs to bigger companies like Mux and Dropbox, audio editing to ensure the highest quality I could get for a remote guest<->host podcast with new guests having assorted mic qualities, moving a lot of "ums" and other fluff but not over editing things to make it unnatural, tags to quickly find tech stacks you care about and a ton of clickable timestamps with a summary of each show that's skimmable in seconds and tons of reference links.

On paper it feels like I did everything I could do to make things "good", but in practice after 100 episodes I had like 200-300 listens per episode which made it no longer viable to continue doing since each episode was about 6 hours of end to end time (finding a guest, editing it, show notes, etc.).

I chatted with 100+ different developers from 100+ different companies on how they build and deploy their apps: https://runninginproduction.com/

There's https://runninginproduction.com/ with 100+ assorted episodes with 100+ different guests talking about how they built and deployed their specific application.

Running in Production

I started a podcast around this topic a few years ago at https://runninginproduction.com/.

As someone who has personally edited over a hundred 1-2 hour podcasts with a new guest every time removing umms, ahhs, dead air and filler words is soul crushing. It has gotten to the point where after 2 years of running my podcast[0] I'm seriously considering stopping the show because I'm getting burnt out from editing and without sponsors it's not feasible to hire an editor, but even with the show making no money I would happily pay triple your asking price if I could click a button and have the problem solved in a way that matched a human's ability to edit out filler words.

It really is the difference between being able to edit a 1 hour episode in 1 real life hour (editing at 2x speed) vs literally spending 5 hours to edit 1 hour when there's a lot of filler words or ums.

In my opinion your "after" version doesn't sound natural. This isn't an attack on your service specifically, because the outcome is the same with all of the tools I've tried. I haven't tried them all but I did play with a few of them.

For example in your case the pause between "Removing" and "filler" doesn't match the pace of the rest of the sentence and the transition from "very" to "time" has a very hard cut. This is also a 10 word clip that's about 6 seconds. If you listened to a 1 hour podcast episode that was edited things like this would be much more noticeable.

There's so many intricate and subtle details around when and what to cut to remove these things in a way where it's not noticeable. Are there any paths moving forward in AI / ML that can lead to this being indistinguishable from being humanly edited?

I debated deleting this comment before posting it because it's a combination of feedback but also saying the service isn't something I would buy but I think it's more beneficial to post this to show there is a real demand for this service if it can be executed flawlessly.

[0]: https://runninginproduction.com/

If you're interested in hearing how 100+ different developers manage their apps in production I have a podcast at https://runninginproduction.com/.

The podcast is at: https://runninginproduction.com