Didn't yet go through the content, but having a AI generated image that you didn't even bother to at least touch-up a bit to fix the text does not give me a lot of confidence about the effort that went into this.
I came to this comment section to say exactly that.
At my work (university research lab) the Ph.D. students have to publish their thesis as a book to defend their degree. They are free to make the image for the cover, which is a very nice touch ang give you artistic freedom in what was supposed to be one of the most important moments of your career (I went for a picture of the chip I designed during my research).
For the past 3 years or so all we have are generic AI generated sciency-looking figures at the cover and it is depressing.
Adds nothing, they could just picked a totally unrelated stock photo if they wanted to add something there. It just immediately halo effects the whole thing as something put together without effort. Stop doing this!
Isn't this overly critical ?. The content matters far more than the image and the chapters are good. I didn't even register the image - I think most folks today have eyes that auto-skip images after being pattern-trained to ignore ads.
The cover has a stack that says "ngirx", and it's all a smudgy mess.
"Don't judge a book by its cover" is for people who don't actually read books. You can't necessarily tell when a book is good based on its cover, but you can absolutely tell with a high certainty that a book with a lazy, crappy, low effort cover is probably going to have a similar level of care and attention put to the contents. It's easily at least a 95% hit rate. Is not overly critical to see something presented lazily and assume it will also be lazy inside, and in this kind of field, I'd also expect that if the cover is AI generated, most of the content could easily be as well.
"Don't judge a book by its cover" indeed (and litteraly in that case), but also "first impression matters".
In that case throwing a generated image without touch up shows the lack of care of the author for a work that's not as fleeting as a podcast. It's not that hard to type the correct words and/or a non wobbly font with Paint.NET / Photopea / Gimp / Affinity Photo / Photoshop / <your favorite pixel editor here>. It also shows an usage of AI without supervision which is kind of a red flag.
I used to listen to Michael Kennedy a lot when my day job was Python, and still occasionally do so this may get a pass, but it's still a bad signal in my books.
I’m an occasional listener of the Talk Python podcast, and I’ve also taken Michael’s pytest course. It’s clear that he puts considerable effort into his content.
But there was no care in the images, which made me skeptical of the content. The free chapters are also poorly written. It reads like he dictated the content and didn't do a single review pass on it. The Docker Compose chapter especially is very light on details and doesn't explain how to use the various features and what tradeoffs or issues you may encounter. Like the AI images, the whole product feels rushed and haphazard and lacking in quality.
In which case it is very infuriating and sad. Honestly if he just did not put that AI art on every page, the whole thing would look way more serious. Presentation and first impression sadly do matter.
Put a pile of trash in a museum and people will think it's art, put art next to a pile of garbage and people will think it's trash.
Just not enough to actually record a podcast, but generate a script and send it to an API to generate a (very recognisable) AI voiced podcast. It's literally called "Talk Python" with no humans talking.
I agree with everyone! Michael's name is a big stamp of "this will be high quality" for me, but if I didn't previously know that and saw an AI generated cover, there's a good chance I'd assume the content inside was AI generated slop, and might tune out without looking any further.
I don't even understand why they do that, surely putting even a low quality something together would make it much better, and with actual font rendering.
Yeah, immediately off-putting, even though I actually enjoy the podcast. Not for like "AI bad" reasons, it's just ugly. Micheal, if you are reading this - please fix, it should take 5 minutes.
I clicked on the link and was greeted by AI slop instantly. I checked the comments, saw this, am writing this and will probably not look at it ever again. Guess I am just not the target audience. I wish them that their AI slop strategy works out just for the sake of good vibes, though. If everyone does it it can't be bad, right? I'm the issue here, clearly.
ngirx and granian are my favorite technologies to work with! Completely agree, this trend of putting a completely useless and ugly AI image on top of your page, I despise. You could have searched the web for an actual diagram, if you wanted one here. These images provided negative values to your articles.
The idea of the book is to pull away a lot of the hype of big cloud providers, show practical steps how we run things over at Talk Python (podcast, courses, e-commerce, and more).I hope some of you find this refreshing!
You can read the first 1/3 online for free. The rest is available DRM free.
I recently compared AWS and Hetzner, not only in terms of raw compute costs but also by factoring in the personnel costs required for operation. I found this perspective particularly interesting: https://beuke.org/hetzner-aws/
Seems interesting, read the online summary. I am curious to read about your part on Chapter 14 (I am part of Litestar maintainer). Thank you for the book anyway !
Unrelated to the content: why on earth is super-light grey a good "bold" colour for a white background? I'm having to highlight each of the bolded parts of the text just to understand it :/
edit: console command for anyone else struggling to read this `document.documentElement.style.setProperty('--bulma-strong-color', '#000');`
Is this some new trend where websites include @media (prefers-color-scheme: light) and @media (prefers-color-scheme: dark) in their css, but it just breaks the site?
This site doesn't even have two themes, that css is just there to break the bold text!
The main text is black yes, but anything that's bold is light grey as per the CSS, which is near unreadable (even if you're not as colourblind as me I suspect)
Haha, came here to mention the light grey text on white background as well. This is a great example of poor accessibility. It should be obvious to a human eye that this is bad; but in case it weren't, one could open up Chrome dev tools, find the styles for this text, click on the color picker, and observe that Chrome reports the contrast ratio for that text to be 1.17, whereas a comfortable (accessible) contrast ratio starts at 4.5.
"Have you heard the phrase "You're not Google, you're not Facebook, and you're not Netflix"? The TL;DR; is those tech giants that have 1M+ concurrent users. They have a hard requirement for no downtime."
Actually, one of the more interesting parts of the Google SRE book was that they don't try to aim for 0 downtime. They consider the background error rate of any network request and optimising much beyond this is counter productive.
Even for individual services they make a point of not trying to make them perfectly available, as this means downstream services are less likely to build in adequate provision for failure.
You can and probably should go thinner than this, with uv we effectively have a workflow comparable to deploying static binaries in other language stacks. You don't need the complexity of docker for this book's goal.
This go thin with uv is good advice for smaller projects. But as you grow with more aspects, it gets more problematic.
I ran code that way for years. But now we have 23 different services: web apps, APIs, and database servers, my code and other self-hosted services.
I would NOT run 23 projects/servers (3 versions of postgres) this way. Like so much, it depends. FWIW, the book goes into depth about these trade-offs.
Presumably just directly on whatever system they are using. If you have something that can be plopped on whatever linux distro and run reliably then you've already got what docker is supposed to give you.
Exactly as sibling comment says, e.g. let's pretend the popular httpx cli was my project to deploy and run on the server. With only uv installed, i can:
uv tool run "httpx[cli] @ git+https://github.com/encode/httpx"
To be clear in this example i'm not pulling a package published on pypi, i'm running the HEAD of that git repo (i could do a branch or tag instead). I could use the "uvx" shortcut instead of "uv tool run". I could specify a specific python version (either one already installed on this OS or choose a dist which uv downloads for me).
This caches the deps in an isolated virtual env for me. It'll only download the deps in the first run.
I'm glad to see people recognizing that computers are quite fast and that they don't need massive cloud-scale solutions for simple problems. That being said, Python really shines as glue code and in small scripts where performance doesn't matter. You'll see considerable performance (and likely maintainability) gains by moving off of Python to almost any other language.
I don't know, but the "Read Online" button leads me to "https[://]talkpython.fm/books/python-in-production/#read-online", and that URL then tries to redirect to "https[://]talkpython.fm/books/python-in-production#read-online". (Notice how the last slash of the path is missing).
This forced my browser to reload the page, and it beats the entire purpose of anchoring and fragment-based navs.
I don't think I've seen a cloud-first company that spent less engineering time on managing their infrastructure. You just replace one set of work with another.
Those numbers bother me. What does it mean to be "6x cheaper"? Is that a sixth the price? If something costs $100, what is 6x cheaper than it? 2x cheaper? 1x cheaper?
It is as frustrating as when people use "200% faster" to mean exactly the same thing as "twice as fast", and "100% faster" to mean the same thing.
A lot are getting ripped off. To what degree depends on their tech capabilities and business savvy (i.e. what would it cost them to do it themselves and what kind of discount can they negotiate from the cloud provider. If you're paying the listed rates you are getting ripped of).
At which monthly spend should we negotiate with AWS for example? And will they check if we are using 25 of their services instead of easily migratable VM-hosted apps?
Readit News
At my work (university research lab) the Ph.D. students have to publish their thesis as a book to defend their degree. They are free to make the image for the cover, which is a very nice touch ang give you artistic freedom in what was supposed to be one of the most important moments of your career (I went for a picture of the chip I designed during my research).
For the past 3 years or so all we have are generic AI generated sciency-looking figures at the cover and it is depressing.
"Don't judge a book by its cover" is for people who don't actually read books. You can't necessarily tell when a book is good based on its cover, but you can absolutely tell with a high certainty that a book with a lazy, crappy, low effort cover is probably going to have a similar level of care and attention put to the contents. It's easily at least a 95% hit rate. Is not overly critical to see something presented lazily and assume it will also be lazy inside, and in this kind of field, I'd also expect that if the cover is AI generated, most of the content could easily be as well.
In that case throwing a generated image without touch up shows the lack of care of the author for a work that's not as fleeting as a podcast. It's not that hard to type the correct words and/or a non wobbly font with Paint.NET / Photopea / Gimp / Affinity Photo / Photoshop / <your favorite pixel editor here>. It also shows an usage of AI without supervision which is kind of a red flag.
I used to listen to Michael Kennedy a lot when my day job was Python, and still occasionally do so this may get a pass, but it's still a bad signal in my books.
I had the same initial thought, but I was skimming the page and came across this line:
> Then, see how to deploy a Flask+HTMX app via Granian, wire it into NGINX, and ensure automatic startups with systemd.
So I've just discovered that https://github.com/emmett-framework/granian exists...
Dead Comment
You can read the first 1/3 online for free. The rest is available DRM free.
For example, if you run `sqldump --db umami ...` in regular postgres (which is what they are using IIRC), then you run:
docker exec umami "sqldump --db umami ..."
Or something almost exactly like this (just from memory here and I wrote that script a year ago).
edit: console command for anyone else struggling to read this `document.documentElement.style.setProperty('--bulma-strong-color', '#000');`
This site doesn't even have two themes, that css is just there to break the bold text!
Actually, one of the more interesting parts of the Google SRE book was that they don't try to aim for 0 downtime. They consider the background error rate of any network request and optimising much beyond this is counter productive.
Even for individual services they make a point of not trying to make them perfectly available, as this means downstream services are less likely to build in adequate provision for failure.
Those tech giants got to where they are by recognising specifically that they don't have "no downtime" requirements.
"Move fast and break things" isn't the mantra of companies with zero downtime requirements.
Was hoping the book would cover data persistence.
I ran code that way for years. But now we have 23 different services: web apps, APIs, and database servers, my code and other self-hosted services.
I would NOT run 23 projects/servers (3 versions of postgres) this way. Like so much, it depends. FWIW, the book goes into depth about these trade-offs.
This caches the deps in an isolated virtual env for me. It'll only download the deps in the first run.
This forced my browser to reload the page, and it beats the entire purpose of anchoring and fragment-based navs.
It is as frustrating as when people use "200% faster" to mean exactly the same thing as "twice as fast", and "100% faster" to mean the same thing.
A 8 CPU / 16 GB Ram server at Hetzner is $30 or so per month. It's $200+ at AWS / Azure.
Bandwidth is 4TB included from free at Hetzner, it's $92.16 / TB or $368.64 additional at AWS / Azure.
That is where the 6x comes from. It's described in detail with that math in the book BTW.