semvec/pypi-packages huggingface dataset:
propar 1.0.3
Run terminal commands easily!
Keywords: python, terminal, bash, command, commands, terminal command runner, execute command, run commands


# Donations
It takes me a long time to make these libraries. If you would like to support my work, Then you can follow my patreon :)

https://www.patreon.com/Schkimansky

# Library
This is a easy to use python library that allows you to run terminal commands easily. 

```python
import propar
result = propar.run_command('echo Hello, MG?')
print(result)
```

# Installation
```bash
pip install propar
```

# Documentation
There are only 2 functions:
```python
run_command(command: str, timeout=None, get_both_output_and_errors=False, get_return_code=False)
run_commands(commands_array: list[str], timeout=None, get_both_output_and_errors=False, get_return_code=False)
```

Run_command takes a command as a string and then runs it. The return value of the function depends on the parameters.
For example, In this case the return value will be the text that you get when you run the command manually in the terminal.
```python
result = run_command("mkdir NewFolder") # If this command gets a error, it will return the error. However if theres no error, Then it will just return the text you get when you execute that command manually.
```

However, you can put a timeout parameter to stop the function once it takes too long (defined in seconds)

Also, theres the run_commands function.
Its the same as run_command but this time it runs multiple commands.

Thats pretty much all, This can be used as a alternative to CMake. And is more powerfull, easier, extensible, simpler, reliable
stepshift 2.2.6
Implementation of the Views stepshifting modelling framework
Requires Python: >=3.8

# stepshift

Stepshift is a package that implements the stepshifting algorithm described in appendix A of  
[Hegre et al. (2020)](https://journals.sagepub.com/doi/full/10.1177/0022343320962157).

## Installation

Stepshift is currently only distributed as a source distribution, which means
that the end user needs a C compiler. This means that OSX users need to have
Xcode installed on their system before proceeding. In addition, the numpy
requirement is quite strict, since stepshift uses the Numpy C API via Cython.

Install by running:

```
pip install stepshift
```

## Usage

Stepshift has a module called `stepshift.views` which contains a class called
`StepshiftedModels`. This class wraps the stepshifting procedure, exposing a
simple, Scikit-Learn-like (but not equivalent) API. The model takes three
arguments: A scikit learn estimator, a list containing integers, which denotes
the steps, and a string variable which is the name of the dependent variable:

```
from sklearn.linear_model import LogisticRegression
from stepshift.views import StepshiftedModels

mdl = StepshiftedModels(LogisticRegression(),[1,2,3,4,5,6,7,8],"outcome")
```