semvec/pypi-packages huggingface dataset:
livesolid 0.0.32
Add a short description here!
License: MIT

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|

=========
livesolid
=========


    Add a short description here!


A longer description of your project goes here...


.. _pyscaffold-notes:

Making Changes & Contributing
=============================

This project uses `pre-commit`_, please make sure to install it before making any
changes::

    pip install pre-commit
    cd livesolid
    pre-commit install

It is a good idea to update the hooks to the latest version::

    pre-commit autoupdate

Don't forget to tell your contributors to also install and use pre-commit.

.. _pre-commit: https://pre-commit.com/

Note
====

This project has been set up using PyScaffold 4.4. For details and usage
information on PyScaffold see https://pyscaffold.org/.
sayt 0.6.5
Package short description.
License: MIT


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------

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    :target: https://sayt.readthedocs.io/en/latest/

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Welcome to ``sayt`` (Search as you type) Documentation
==============================================================================
``sayt`` (Search as you type) is a Python library provide Google liked searching experience using your own dataset. It focus on quickly indexing your own dataset and start searching on it. ``sayt`` is not a full text search database, it doesn't support update/delete operation on your dataset, if your dataset is changed, ``sayt`` will delete the old one and re-index everything.

Features:

1. Support id search, ngram search, full text search, fuzzy search, range search.
2. Query results are automatically cached, and will expire based on your configuration.


.. _install:

Install
------------------------------------------------------------------------------

``sayt`` is released on PyPI, so all you need is to:

.. code-block:: console

    $ pip install sayt

To upgrade to latest version:

.. code-block:: console

    $ pip install --upgrade sayt
prepare-toolbox 0.4.0
Toolbox containing helper functions for prepare-assignment actions
License: MIT
Requires Python: >=3.8,<4.0

# Toolbox

This repository contains helper functions for:

- Interacting with a run in `prepare_assignment`
  - Retrieving input
  - Setting output
- Finding files based on globs
- Creating zip files

## Interacting with `prepare_assignment`

To help a `prepare_assignment` action interact with a run, a couple of helper functions are defined in `core.py`.

To retrieve input use the `get_input` function, this has the following parameters:

 - `key: str`: The key of the input to retrieve, this is the same as the key as defined in the `action.yml`
 - `required: bool= False`: if true and the key is not present it will raise an exception
 - `trim_whitespace: bool`: if true it will automatically trim whitespace from the retrieved value

To set output that can be used by other actions in the run, use the `set_output` function. This function has the following parameters:

- `name: str`: the key that other actions can use to retrieve the value
- `value: Any`: the value

Furthermore it defines helper methods for logging:

- `set_failed`: log exception/message with level `ERROR` and exit the process
- `set_error`: log exception/message with level `ERROR`
- `set_warning`: log message with level `WARNING`
- `info`: log message with level `INFO`
- `debug`: log message with level `DEBUG`

## Finding files

A common task for actions is to find files based on a glob. To make this repetitive task easier a helper function is defined in `file.py`. The function `get_matching_files` returns a list of paths (as strings) that match the files, given the parameters. The following parameters are available:

- `included: Union[str, List[str]]`: Glob(s) that should be matched
- `excluded: Union[str, List[str], None]`: Glob(s) that should be excluded from being matched. I.e. if a path matches the `included` glob, it should not be processed if it also matches the `excluded` glob. Default: `None`
- `relative_to: : Union[str, None]`: Set relative path from where the globs should be matched. If `None` the current working directory is used. Default: `None`
- `allow_outside_working_dir: bool`: Allow `relative_to` to be outside the current working directory. Allow the matched glob(s) to be outside the `relative_to` directory. Default: `False`
- `recursive: bool`: If true the glob should recurse directories. Default: `True` 

## Creating zip files

To help with creating zip files the `zip.py` adds a helper method `create_zip` to easily create a simple zip archive. It takes the following parameters:

- `name: str`: name of the archive
- `files: List[str]`: paths to the files to include
- `output: Optional[str]`: the output directory to write to (default to current working directory). Default: `None`
darlehen.py 0.9.1
darlehenpy bietet Funktionen zur Berechnung eines Darlehens
License: MIT

# darlehenpy

Ein kleines Paket zur Berechnung von Darlehen. Bei weitem (noch 😉) nicht so mächtig wie z.B. der [Hypothekenrechner](https://www.zinsen-berechnen.de/hypothekenrechner.php).

Es wird zwischen der Berechnung basierend auf der Monatsrate oder basierend auf der anfänglichen Tilgungsrate unterschieden. Die Angabe einer jährlichen Sondertilgung ist auch möglich.

[Projekt auf PyPI](https://pypi.org/project/darlehen.py/)

## Quickstart

```
pip install darlehen.py
import darlehenpy.darlehen as darlehen
darlehen.berechne_mit_monatsrate(...)
darlehen.berechne_mit_tilgungsrate(...)
```

**Achtung!** Punkt als Dezimaltrennzeichen!

## Beispiel

Aus der [beispiel.py](https://github.com/Allaman/darlehenpy/blob/main/beispiel.py).

```python
import src.darlehenpy.darlehen as darlehen
# Die Ausgabe kann man schöner machen ;)

# Rahmenbedingungen
P = 100000
i = 4.1
n = 10
S = 5000

print(
    f"Darlehensumme: {P} €\nZinssatz (p.a.): {i} %\nLaufzeit: {n} Jahre\nSondertilung (p.a.): {S}\n"
)

# Berechnung basierend auf einer Monatsrate
M = 500
print(f"Monatsrate: {M} €")
t0, R, gesamtaufwand, jahr, monat = darlehen.berechne_mit_monatsrate(P, i, M, n, S)
print(
    f"Anfängliche Tilgungsrate: {t0} %\nRestschuld nach {n} Jahren: {R} €\nGesamtaufwand: {gesamtaufwand} €\nAbbezahlt im {jahr}. Jahr und {monat}. Monat\n"
)

# Berechnung basierend auf der anfänglichen Tilgungsrate
t0 = 5.5
print(f"Anfängliche Tilgungsrate: {t0} %")
M, R, gesamtaufwand, jahr, monat = darlehen.berechne_mit_tilgungsrate(P, i, t0, n, S)
print(
    f"Monatsrate: {M} €\nRestschuld nach {n} Jahren: {R} €\nGesamtaufwand: {gesamtaufwand} €\nAbbezahlt im {jahr}. Jahr und {monat}. Monat"
)
```

Ausgabe:

```
❯ python test.py
Darlehensumme: 100000 €
Zinssatz (p.a.): 4.1 %
Laufzeit: 10 Jahre
Sondertilung (p.a.): 5000

Monatsrate: 500 €
Anfängliche Tilgungsrate: 1.9 %
Restschuld nach 10 Jahren: 16033.91 €
Gesamtaufwand: 126033.91 €
Abbezahlt im None. Jahr und None. Monat

Anfängliche Tilgungsrate: 5.5 %
Monatsrate: 800.0 €
Restschuld nach 10 Jahren: 0.0 €
Gesamtaufwand: 118474.63 €
Abbezahlt im 9. Jahr und 3. Monat
```

Man kann sich damit natürlich viele Werte auf einmal berechnen lassen und vergleichen. Z.B. mit einer CSV mit folgenden Spalten als Input:

```csv
P,i,M,n,S,
```

bzw.

```
P,i,t0,n,S,
```

## Tests

Eine Testmatrix mit Werten ermittelt aus dem [Hypothekenrechner](https://www.zinsen-berechnen.de/hypothekenrechner.php) testet die berechneten Ergebnisse.

**Es kann keine Gewährleistung für die von diesem Paket berechneten Ergebnisse übernommen werden**