We just shipped 3.8.0.
PyInfra is an agentless infrastructure automation tool. Same job description as Ansible, Salt, Chef. SSH into hosts, describe desired state, it diffs and converges. No agent, no central server, no daemon.
The difference: your "playbook" is just Python. Not Python cosplaying as YAML. Not Jinja smuggled inside YAML inside a Helm chart inside a Kustomize overlay. Actual Python:
from pyinfra.operations import apt, files, server
apt.packages(packages=["nginx"], update=True)
files.template(src="nginx.conf.j2", dest="/etc/nginx/nginx.conf")
server.service(service="nginx", running=True, enabled=True)
About YAML. Wonderful format. For about eleven minutes. Then someone needs an `if`, and you have `{% if %}` inside a string inside a list inside a map. Then someone types `no` as a country code for Norway and it ships to prod as `False`. Then someone indents with a tab and the parser dies without saying where. Congratulations, you reinvented a programming language. Badly. The honest move is to admit you wanted code, then write code.
PyInfra skips the eleven good minutes and goes straight to code.
Release notes in the link. Happy to answer questions.
Infrastructure as Code, not infrastructure as YAML.
I've used Salt, CFEngine, Chef, Puppet, Make, Bash, and many hand-rolled iterations of this approach. I finally threw in the towel and forced myself to come to terms with Ansible and it's quirks because I needed the wider community support.
Now with AI tooling, I'm not so convinced the community modules moat is an actual moat. I'm going to very seriously consider porting all my Ansible code to this and see how it feels. I anticipate I'll be much happier after the change.
Do you have any plans to integrate with/build on other communities modules? i.e. even if it's not perfect, being able to call Ansible or Salt modules from PyInfra would be one way to fill the gap.
I've been down this path, implemented my own version of PyInfra many times over the years. I've used Ansible and my own implementations in anger. The _if param is far far far from the worst offender and it's a natural addition, especially when you are laying out a bunch of unrelated checks into something that looks more like a table.
Basically a flaw of the entire model where you write code as if executing a single host which is then executed on many in parallel, forcing the two step diff and deploy that causes this.
Funny thing is since v3 this behavior (diff then execute) is even desired with the yes prompt like terraform.
For anything dynamic and sufficiently complicated, ansible is horrible. Pyinfra is much better.
Ran into some bugs, like one machine that seems to cause errors and mess up the output on restart, although that looks like it might have been addressed in this release.
If it helps, I put together a video when initially exploring PyInfra: https://www.youtube.com/watch?v=S-_0RiFnKEs
You don't have to do crazy things with Ansible for that yaml DSL becoming the opposite of helpful. Things which would be quite straightforward to express in code become quite cumbersome, hard to understand and hard to debug. Also Jinja is often a horrible choice (you don't have in Ansible). Also Ansible excessively requires it in places where you want proper types and not just a string.
- Doesn't unnecessarily send code over the network.
- Has some sort of "execution optimizer".
Think for example a query planner/optimizer of a db. Or, as a good example, the query planner of the polars framework as opposed to how it works in pandas.
If I do a for loop and each loop iteration copies a file into the same dir, the optimizer should catch that and send over one compressed tar file.
The biggest difference is that Pyinfra is simply Python code. It's incredibly easy to control the system in whatever manner you need to. You can probably do the same thing in Ansible, but it's never quite as obvious how to do it. This also means it's much more clear where and why things work the way they do in Pyinfra, where in Ansible I end up digging through numerous role files to try to find where some variable gets injected.
Incredibly frustrating that the data you want is right there but you can't easily grab it.
If you're doing data manipulation locally you would simply write Python code.
Operations[1] are Python functions which execute (yield) commands which will be run on hosts.
That's the gist of what it takes to write custom modules for Pyinfra.
[0] https://docs.pyinfra.com/en/3.x/api/facts.html [1] https://docs.pyinfra.com/en/3.x/api/operations.html
But the main guy who developed it at that company left, so no idea on its longevity.
It worked well and was nicer to deal with than test kitchen for testing UNIXy things (is service running and/or enabled, does file have right permissions, does file include $TEXT, etc). It was very useful for us during big linux upgrades, such as when ubuntu went from upstart to systemd. It can also be good at capturing edge cases with brittle outcomes (especially as ansible went through enormous changes after the red hat acquisition).
Dislikes? I had to fight with pyenvs a bit..
Honestly the bigger issue was testing x86 docker images on an arm mac, as molecule didn't cleanly support cross platform images and we did pull in x86 binaries for our playbooks (by the end of my time at said company, I was also directly managed by product managers who didn't care about tech debt and I couldn't deal with the otherwise desirable idea to move our compute to ARM - a rant for another day). This may also be fixed now.
Switched to Pyinfra and the difference is day and night. You write python code you can organise your stuff into functions, classes and whatever you like and then instantiate them as you like. Highly reusable configuration.
You have full pwoer such as you can call boto to fetch the list of servers to target, filter base on tags and what not. Only sky is the limit because it is NOT a DSL (or YAML) rather full blow real python.
I found PyInfra to be a great tool for the job at hand. Even though it didn't have many of the operations I needed, I found it easy to write new operations specific to macOS management tasks.
I recently looked at it again to help build EC2 Mac AMIs in combination with Packer, but I ended up with pydoit this time instead.
I could likely vibecode something up if I had to, but I'm interested in a job orchestration system that can run things like upgrades, scheduled backups, ideally with a nice dashboard showing successful/failed jobs.
I worked for a telco company that had a lot of Nortel Passport devices (does anyone know what Frame Relay is?). We started changing the network from Nortel to Cisco. Cisco used telnet (later SSH), but Nortel people were extremelly reluctant to switch.
Turns out the Nortel network managment system (nortel nms) had a very interesting feature: you could open the command console to connect to one of the passport devices... or you could connect to a device group (or all the network) and run the same command in all devices.
This was great for auditing which version had every single device in the network... or for changing access-lists globally.
Stuff I threw into the inputs before working with pyinfra
I despise YAML, but I can appreciate that it makes it harder to introduce imperative logic, and it forces you to stay on the paved path - which is very well-tested.
This is just the pendulum swinging back again, and at least Python tends to be a little less "clever" (and therefore less write-only) than Ruby.
It seems to me that infra management is inherently suited to declarative logic. I'm pragmatic enough to understand why SWEs with little infra experience might prefer an imperative approach, but I tend to think you should pick one or the other and stick to it. In my experience, hybrid systems end up combining the worst aspects of both.
https://github.com/pyinfra-dev/pyinfra/blob/3.x/src/pyinfra/...
“Built on Python, Salt is an event-driven automation tool and framework to deploy, configure, and manage complex IT systems. Use Salt to automate common infrastructure administration tasks and ensure that all the components of your infrastructure are operating in a consistent desired state.”
https://docs.saltproject.io/en/latest/topics/about_salt_proj...
pyinfra is just python that gets transpiled into ssh commands
If you're a software engineer who wants to setup and maintain infrastructure, give PyInfra and Pulumi a go!
Huge fan of PyInfra. For my homelab, I use Pulumi with Python and PyInfra to build fully declarative intent based infrastructure. You can use actual software engineering principles like composition, inheritance, DI to setup and wire your infrastructure and services. One of the benefits of this is your infrastructure and services are now self documenting (have them write out a mermaid diagram!) and easily testable using pytest (from cheap unit tests to extensive integration tests (I use Incus)).
Instead of Pulumi, I originally used Terraform CDK with Python before CDK got IBM'd. The migration to Pulumi was refreshingly painless. My original reason for not choosing Pulumi was the crippled state of the open source, self hosted backend support a decade ago but it looks like that is now way more mature and less crippled.
PyInfra is a breath of fresh air compared to Ansible - its not just fast, it's more Pythonic, so IDE features actually work, readable, maintainable, debuggable. I call it infrastructure for software engineers.
If anyone wants to use an AI agent to try out PyInfra - One issue I've faced is that PyInfra was rearchitected in v2 (and some more in v3?) but what belongs in v1 vs v2 vs v3 isn't very clear, so an AI agent could spend a lot of time writing v1 code, having it fail and iterate to v2 and then to v3.
The official site uses the version in the URL as the namespace but it seems like the SOTA AI agents don't pay much attention to that.
Maybe writing a llms.txt for PyInfra v2, or v3 would be an extremely useful task to help with onboarding newcomers?
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The original post by the OP https://news.ycombinator.com/user?id=wowi42:
Disclosure: PyInfra core contributor here. We just shipped 3.8.0.
PyInfra is an agentless infrastructure automation tool. Same job description as Ansible, Salt, Chef. SSH into hosts, describe desired state, it diffs and converges. No agent, no central server, no daemon.
The difference: your "playbook" is just Python. Not Python cosplaying as YAML. Not Jinja smuggled inside YAML inside a Helm chart inside a Kustomize overlay. Actual Python:
from pyinfra.operations import apt, files, server
apt.packages(packages=["nginx"], update=True)
files.template(src="nginx.conf.j2", dest="/etc/nginx/nginx.conf")
server.service(service="nginx", running=True, enabled=True)PyInfra skips the eleven good minutes and goes straight to code.
Release notes in the link. Happy to answer questions.
Infrastructure as Code, not infrastructure as YAML.
Disclosure: another contributor here.
TBH, I was worried a few years ago that there was basically just one (original) contributor. This now gives me added trust that I'm taking the right decision to lean heavily into it.
I hope more people start using pyInfra.
Thank You for your contribution and attention!
There are currently 3 active maintainers incl. the creator of pyinfra. But there are many more contributors incl. repeat contributors.
I can't get over the fact of how suspicious he looks while doing it. And doesn't even cover his face. Crazyness
https://x.com/porqueTTarg/status/2047652413306277970 https://xcancel.com/porqueTTarg/status/2047652413306277970