hydra
yq
hydra | yq | |
---|---|---|
14 | 24 | |
8,229 | 2,472 | |
1.6% | - | |
6.3 | 7.7 | |
21 days ago | 7 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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hydra
- Hydra – a Framework for configuring complex applications
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Show HN: Hydra - Open-Source Columnar Postgres
Nice tool, only unfortunate name, consider changing it. Already very well know security tool named hydra https://github.com/vanhauser-thc/thc-hydra been around since 2001. Then facebook went ahead and named their config tool hydra https://github.com/facebookresearch/hydra on top of it. Like we get it, hydra popular mythology but we could use more original naming for tools
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Show HN: Hydra 1.0 – open-source column-oriented Postgres
This looks really impressive, and I'm excited to see how it performs on our data!
P.S., I think the name conflicts with Hydra, the configuration management library: https://hydra.cc/
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Best practice for saving logits/activation values of model in PyTorch Lightning
I've been trying to learn PyTorch Lightning and Hydra in order to use/create my own custom deep learning template (e.g. like this) as it would greatly help with my research workflow. A lot of the work I do requires me to analyse metrics based on the logits/activations of the model.
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[D] Alternatives to fb Hydra?
However, hydra seems to have several limitations that are really annoying and are making me reconsider my choice. Most problematic is the inability to group parameters together in a multirun. Hydra only supports trying all combinations of parameters, as described in https://github.com/facebookresearch/hydra/issues/1258, which does not seem to be a priority for hydra. Furthermore, hydras optuna optimizer implementation does not allow for early pruning of bad runs, which while not a deal breaker is definitely a nice to have feature.
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Show HN: Lightweight YAML Config CLI for Deep Learning Projects
Do you hate the fact that they don't let you return the config file: https://github.com/facebookresearch/hydra/issues/407
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Config management for deep learning
I kind of built this due to frustrations with Hydra. Hydra is an end to end framework, it locks you into a certain DL project format, it decides logging, model saving and a whole host of things. For example Hydra can do the same config file overwriting that I allow but you have to store the config file with the name config.yaml inside a specific folder. On top of that hydra doesn’t let you return the config file from the main function so you have to put all the major logic in the main function itself (link), the authors claim this is by design. I can find Hydra useful for a mature less experimental project. But in my robotics and ML research, I like being able to write code where I want and integrating it how I want, especially when debugging for which I think this package is useful. TLDR; If you just want the config file functionality use my package, if you want a complete DL project manager use Hydra. While hydra implements this config file functionality, it also adds a lot of restrictions to project structure that you might not like.
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The YAML Document from Hell
For managing configs of ML experiments (where each experiment can override a base config, and "variant" configs can further override the experiment config, etc), Hydra + Yaml + OmegaConf is really nice.
https://hydra.cc/
I admit I don't fully understand all the advanced options in Hydra, but the basic usage is already very useful. A nice guide is here:
https://florianwilhelm.info/2022/01/configuration_via_yaml_a...
- Hydra - namestitev in osnovna uporaba
- Hydra - namestitevt in osnovna uporaba
yq
- Jaq – A jq clone focused on correctness, speed, and simplicity
- jq 1.7 Released
- Using XPath in 2023
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How to troubleshoot yaml parsing error "did not find expected key"?
Install jq and yq, and wrap your commands with | yq -y ..
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Memes are all cool and all. But this is your daily remaining that 10000! =
Confusingly there is another project called yq that does exactly what you're suggesting and it's a preprocessor that converts yaml to json and then used jq. https://github.com/kislyuk/yq
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inhumane and error-prone
yq
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Yq is a portable yq: command-line YAML, JSON, XML, CSV and properties processor
I personally find the yq tool from https://github.com/kislyuk/yq much more useful: it has all the same options and formats as `jq` (as it's really a wrapper around jq). Rather than the `yq` in the OP here where only partial functionality exists.
- The YAML Document from Hell
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Scraping weather info
XML data from the API can be parsed and filtered with xq. There may be multiple ways to get it; first try the yq toolset which includes it.
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Show HN: Xq – command-line XML and HTML beautifier and content extractor
There is also yq [1], which attempts the same for yaml, toml and xml. (And confusingly also contains a binary named "xq" for querying xml, however with a different syntax)
[1] https://github.com/kislyuk/yq
What are some alternatives?
dynaconf - Configuration Management for Python ⚙
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
ConfigParser
yq - yq is a portable command-line YAML, JSON, XML, CSV, TOML and properties processor
python-dotenv - Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.
jq - Command-line JSON processor
python-decouple - Strict separation of config from code.
dasel - Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
django-environ - Django-environ allows you to utilize 12factor inspired environment variables to configure your Django application.
xmlq - filter xml in the command line with xpath
classyconf - Declarative and extensible library for configuration & code separation
hn-search - Hacker News Search