semvec/pypi-packages huggingface dataset:
simple-pygame-ui 0.1.19
Simple UI Library for pygame
License: MIT
Requires Python: >=3.9

# PyGameUI Is a PyGame UI Library that adds simple UI for with the use of PyGame

## Setting up a simple setup:

in your Main Class write:

```python
if __name__ == "__main__":
  pygameui.setup(YourMainScene())
```

and also make a Script and add a class to that script in my Case "YourMainScene"

```python
class YourMainScene(PyGameScene):
  def update(self):
    # Write your Code here that Should only run when the Window is updated
  def render(self,screen,events):
    # Write your Rendering Code here
```
now lets say you want to add a Button then write a snippet like this in update:

```python
self.drawables.append(Button("Here Goes the Button Text",
  (Here Goes a tuple of 2 ints that is the center of the button),
  (Here Goes a tuple of 2 ints that is the size of the button),
  heres a reference for what should happen when the button gets clicked(lamda supported),
  [Heres a list of values that should be passed onto the on_clicked methode]))
```
python-turkish-translation 0.9.1
Python'ın bazı yerleşik fonksiyonlarını Türkçeleştiren küçük bir paket.
License: MIT
Requires Python: >=3.8
Keywords: turkce, python, cevirmen, pyt, turtle, grafik, renk

# python-turkish-translation: Türkçe Python Fonksiyonları Paketi (v0.9.1)

`python-turkish-translation`, Python'ın en çok kullanılan yerleşik fonksiyonlarını ve temel modül komutlarını (Girdi/Çıktı, Veri Tipleri, Turtle Grafikleri) Türkçeleştirmeyi amaçlayan bir eğitim ve geliştirme paketidir. Amacımız, Python öğrenimini Türkçe konuşan kullanıcılar için daha akıcı ve eğlenceli hale getirmektir.

## Özellikler (Features)

- **Temel I/O:** `yazdır()` (`print`), `girdi_al()` (`input`)
- **Veri İşleme:** `uzunluk_bul()` (`len`), `tür_bul()` (`type`), `değer_dönüştür()` (`int`/`float`)
- **Grafik (Turtle):** Tüm temel çizim komutlarının Türkçe karşılıkları ve Türkçe renk desteği (Örn: `renk_ayarla("kırmızı")`, `ileri_git(100)`). Türkçe pembe tonları desteği (`açıkpembe`, `derinpembe` vb.) eklenmiştir.

---

## 🇹🇷 Kurulum ve Kullanım

Paketi kurmak için `pip` kullanabilirsiniz:

```bash
pip install python-turkish-translation
idr-torch 2.5.0
Distribution initialization util tool
License: MIT
Requires Python: >=3.8

# idr_torch

## Description

Permet de récupérer les variables SLURM afin de gérér le multi-GPU/multi-noeuds pour le parallélisme sur Pytorch.

```python
import torch.distributed as dist
import idr_torch

if idr_torch.rank == 0:
    print(">>> Training on ", len(idr_torch.nodelist), " nodes and ", idr_torch.world_size, " processes") 

dist.init_process_group(backend='nccl', 
                        init_method='env://', 
                        world_size=idr_torch.world_size, 
                        rank=idr_torch.rank)
```


Si on veut rajouter une nouvelle API, on peut la mettre dans le dossier `api` et l'importer dans le `__init__.py`. Ou alors on peut la coder n'importe où, et après appeler `idr_torch.register_api(nouvelle_api)`.
Les nouvelles APIs doivent hériter de `idr_torch.API`. Si on veut faire en sorte que la MASTER_ADDR et le MASTER_PORT soit mis automatiquement (dans le cas où le lanceur ne le fait pas comme SLURM), alors il faut utiliser `idr_torch.AutoMasterAddressPort` comme décorateur de notre nouvelle API.

On patche aussi le profiler. Il suffit de remplacer `from torch.profiler import ...` par `from idr_torch.profiler import ...`.

Note : idr_torch est compatible avec submitit.
C2Percentiles 0.1.1
All nine Hyndman-Fan sample-quantile estimators plus pandas helpers & plots.
License: MIT
Requires Python: >=3.8

# C2Percentiles

A lightweight, zero-dependency (core) Python package that delivers **all nine Hyndman-Fan sample-quantile estimators**—plus ready-made helpers for multi-column, group-wise, and visual work-flows.

 **PyPI**  `pip install C2Percentiles` 
 
**License**  MIT 

 **Python**  ≥ 3.8 

---

## Why this package?

Standard libraries (NumPy, pandas) give you **only one** estimator—Type 7.  
Research or regulatory work often needs **Type 8** (median-unbiased) or **Type 9** (normal QQ-plots).  
`C2Percentiles` gives you **all nine** in a single line, plus batteries-included helpers for:

* single vectors
* many columns at once
* stratification by groups
* quick Seaborn/ Matplotlib visuals

---

## Installation

```bash
# core only – no plotting
pip install C2Percentiles

# with plotting extras
pip install "C2Percentiles[plots]"
```

---

## 60-second tutorial

```python
import numpy as np, pandas as pd, quantile_kit as qk

# any 1-D data
x = np.random.randn(100)

# all nine 0.25, 0.50, 0.75 quantiles
qk.quantile_custom(x, [0.25, 0.5, 0.75], qtype="all")
# → DataFrame indexed by probability

# only Types 7 & 8, 4 sig-digits, pretty strings
qk.quantile_custom(x, [0.1, 0.9], qtype=[7, 8], sig_digits=4)

# many columns at once
df = pd.DataFrame({"A": np.random.randn(80),
                   "B": np.random.randn(80)*50 + 100,
                   "Group": np.random.choice(["G1", "G2"], 80)})

qk.quantiles_for_vars(df, ["A", "B"], probs=[0.05, 0.5, 0.95])
# → long table: Variable | Probability | Type1 … Type9

# group-wise
qk.quantiles_by_group(df, "Group", ["A", "B"], probs=[0.25, 0.75])

# quick plot – estimator spread
qk.plot_quantile_line(df["B"], probs=[0.05, 0.5, 0.95])
```

---



## API reference

| Signature 						| Description |
|-------------------------------------------------------|-------------|
| `quantile_custom(x, probs, qtype=7, sig_digits=None)` | core engine |
| `quantiles_for_vars(df, vars, probs, qtype, sig_digits)` | multi-column |
| `quantiles_by_group(df, group_var, num_vars, probs, qtype, sig_digits)` | grouped |
| `plot_quantile_line(x, probs, …)` | single-variable plot |
| `plot_qfv(df, vars, probs, …)` | faceted by variable |
| `plot_qbg(df, group_var, vars, probs, …)` | faceted by group & variable |

Full doc-strings are available via `help(...)` or your IDE.

---

## Citation

If you use this package in research, please cite:

Hyndman, R. J. and Fan, Y. (1996) “Sample Quantiles in Statistical Packages”, *American Statistician* **50**(4): 361–365.

---

## License

MIT – see `LICENSE` file.