semvec/pypi-packages huggingface dataset:
lbfgs_lab 0.0.2
L-BFGS variants for academic research
License: MIT
Requires Python: >=3.8

# lbfgs_lab

## Set Up

```bash
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt 
```

https://pypi.org/project/lbfgs_lab/

https://packaging.python.org/en/latest/tutorials/packaging-projects/

## Documentation

https://docs.readthedocs.com/platform/stable/tutorial/

## References

This project is partially inspired by the following L-BFGS-related repositories.
Thanks to the developers of these projects.

* [DirL-BFGS](https://github.com/ashkansl/DirL-BFGS): Direct L-BFGS method using a low-rank plus diagonal inverse Hessian approximation.
* [LBFGSpp](https://github.com/yixuan/LBFGSpp): Header-only C++ library for L-BFGS and L-BFGS-B algorithms.
* [liblbfgs](https://github.com/chokkan/liblbfgs): C library implementing the L-BFGS optimization method.
* [mL-BFGS](https://github.com/yuehniu/mL-BFGS?tab=readme-ov-file): Momentum-based L-BFGS for distributed large-scale neural network training.
* [paper-regularized-qn-benchmark](https://github.com/dmsteck/paper-regularized-qn-benchmark): Regularized L-BFGS approach for large-scale nonconvex minimization.
* [py-owlqn](https://github.com/samson-wang/py-owlqn.git): Python implementation of the OWL-QN optimization algorithm with a logistic regression example.
* [pylbfgs-dedupeio](https://github.com/dedupeio/pylbfgs): Python/Cython wrapper for the liblbfgs library.
* [pylbfgs-larsmans](https://github.com/larsmans/pylbfgs): Alternative Python/Cython wrapper for the liblbfgs library.
* [python_lbfgsb](https://github.com/avieira/python_lbfgsb): Pure Python implementation of L-BFGS-B, though using a deprecated scipy module.

## License

This project is licensed under the MIT License. (`liblbfgs` is under the MIT License as well).

See the [LICENSE](LICENSE) file for details.
pyscbwrapper 0.1.2
Python wrapper for Statistics Sweden's API, which can be found at https://www.scb.se/en/api.
License: MIT

# pyscbwrapper
Version 0.1.1

Python wrapper for Statistics Sweden's API, which can be found at https://www.scb.se/en/api.

News in version 0.1:  
Compatible with changes in the API.  
Includes a function for generating JSON queries from user-supplied input.  
It is now possible to go up and down in the metadata tree more than one step at a time.

News in version 0.1.1:  
Bugfixes: Variables with space in their names can now be accessed by removing the spaces.  
New functionality: get_variables() returns a dict instead of only writing to the terminal.  

News in version 0.1.2:
Security fix: Updated API URL from HTTP to HTTPS to ensure secure communication with Statistics Sweden's API. 
This resolves issues with empty or invalid responses caused by using the insecure HTTP connection.

Dependencies: requests>=2.21.0

To install: 
```python
pip install pyscbwrapper
```

To import: 
```python
from pyscbwrapper import SCB
```

For info on usage, see the included notebooks. For detailed usage examples, see the subfolder fetch-deso-data-examples.




[![Mentioned in Awesome Official Statistics ](https://awesome.re/mentioned-badge.svg)](http://www.awesomeofficialstatistics.org)