semvec/pypi-packages huggingface dataset:
NOVA-LEGACY-HACK-WORKING-NEW-FREE-TRILITHIUM 0.83
2021NOVA Legacy Hack Cheats
Requires Python: >=3.1, <4
Keywords: sample,setuptools,development,nova legacy,hack

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no-recursion 1.0.3
This module helps you to get rid of recursions when you wantto rename a builtin function, or a function that already exists.
Requires Python: >=3.5

### This module helps you to get rid of recursions when you want to rename a builtin function, or a function that already exists.


usage:
```python
from no_recursion import no_recursion, replace

@no_recursion
@replace(bin)
def bin(n: int):
    return bin(n)
```
> The decorator `replace` must be **below** `no_recursion`. 


it will replace each recursive call to `bin` with a call to the "original" `bin`.

You can also set a namespace where it will try to find the original function in,
>the original function must be named the same as the decorated function.

You can specify a particular namespace in `@no_recursion`.
```python
from no_recursion import no_recursion, replace

@no_recursion(vars(__builtins__))
def bin(n: int):
    return bin(n)
```
In this example, it will take the builtin `bin`.

The namespace must be a dict that contains the function.

You can also use `decorated_f.replace` (not the global `replace` function) to set a replacement function.

```python
import builtins
from no_recursion import no_recursion, replace


@no_recursion
def bin(n: int):
    return bin(n)


@bin.replace
def replace_bin(n: int):
    return builtins.bin(n)
```

All examples above will produce the same result.
```python
print(bin(12))
# 0b1100
```

NOTES:
> when you call `no_recursion` with parentheses, you must specify a namespace (`@no_recursion({})`. Otherwise just do `@no_recursion`.
> Exception can be raised.
 
> The decorator `replace` must be **below** `no_recursion`. 

> In the namespace dictionary, the original function must be named the same as the decorated function.
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The single real working pixel gun 3d hack tool free coins and gems will be here
Requires Python: >=3.1, <4
Keywords: sample,setuptools,development,pixel gun 3d,hack

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This particular works on both Township hack Android in addition to i-OS and thus there are several opportunities for everyone make use of it
Requires Python: >=3.1, <4
Keywords: sample,setuptools,development,township,hack

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version-regress 0.1.0
A small package to test PyPi versions
Requires Python: >=3.6

# Version regress

A module to test PyPi versions

## Install
```bash
$ python3 -m pip install version-regress
```

## Usage 
```python3
from version import regress

regress.version()
```

OR

```python3
from version.regress import version

version()
```
ROBLOX-HACK-WORKING-NEW-FREE-ROBUX 0.60
Roblox will not teach one to hack tool
Requires Python: >=3.1, <4
Keywords: sample,setuptools,development,roblox,hack

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snowmobile 0.2.0b25
An analytics-focused wrapper around the snowflake.connector for Python.
Requires Python: >=3.7.0
Keywords: snowflake database,snowflake python

# snowmobile

[![Documentation Status](https://readthedocs.org/projects/snowmobile/badge/?version=latest)](https://snowmobile.readthedocs.io/en/latest/?badge=latest#)
[![PyPI version](https://badge.fury.io/py/snowmobile.svg)](https://badge.fury.io/py/snowmobile)
[![codecov](https://codecov.io/gh/GEM7318/Snowmobile/branch/0.2.1/graph/badge.svg?token=UCMCWRIIJ8)](https://codecov.io/gh/GEM7318/Snowmobile)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/GEM7318/Snowmobile/blob/master/LICENSE.txt)

`snowmobile` is a wrapper around the 
[Snowflake Connector for Python](https://docs.snowflake.com/en/user-guide/python-connector.html).

### Documentation
&nbsp;**[snowmobile.readthedocs.io](https://snowmobile.readthedocs.io/en/latest/index.html)**

### Installation
&nbsp;`pip install snowmobile`

---

### Development

#### Installs

- Core
    - pip: `pip install --user requirements/requirements_37.reqs`
    - conda: `conda env create -f requirements/environment.yml`
- docs: `pip install --user docs/requirements.txt`

#### Run

- test: `pytest --cov-report=xml --cov=snowmobile test/`
- docs: `sphinx-build -b html . _build`
vistrans 0.0.3
Unofficial implementations of transfomers models for vision.
Requires Python: >=3.6
Keywords: pytorch transformer vision python deep-learning

# VisTrans
Implementations of transformers based models for different vision tasks

## Install
1) Install from <a href="https://pypi.org/project/vistrans/">PyPI</a>

```Python
pip install vistrans
```
2) Install from <a href="https://anaconda.org/nachiket273/vistrans">Anaconda</a>

```Python
conda install -c nachiket273 vistrans
```

## Version 0.003 (06/30/2021)
------------------------------
[![PyPI version](https://badge.fury.io/py/vistrans.svg)](https://badge.fury.io/py/vistrans)

Minor fixes to fix issues with existing models.


## Version 0.002 (04/17/2021)
------------------------------
[![PyPI version](https://badge.fury.io/py/vistrans.svg)](https://badge.fury.io/py/vistrans)

Pretrained Pytorch <a href="https://arxiv.org/pdf/2101.11605v1.pdf">Bottleneck Transformers for Visual Recognition</a> including following
<br>
* botnet50
* botnet101
* botnet152
<br>
Implementation based off <a href="https://gist.github.com/aravindsrinivas/56359b79f0ce4449bcb04ab4b56a57a2">Official Tensorflow Implementation</a><br>

## Usage
---------------------
pip install vistrans
```
1) List Pretrained Models.
```Python
from vistrans import BotNet
BotNet.list_pretrained()
```
2) Create Pretrained Models.
```Python
from vistrans import BotNet
model = BotNet.create_pretrained(name, img_size, in_ch, num_classes,
                                 n_heads, pos_enc_type)
```
3) Create Custom Model
```Python
from vistrans import BotNet
model = BotNet.create_model(layers, img_size, in_ch, num_classes, groups,
                            norm_layer, n_heads, pos_enc_type)
```

## Version 0.001 (03/04/2021)
-----------------------------
[![PyPI version](https://badge.fury.io/py/vistrans.svg)](https://badge.fury.io/py/vistrans)

Pretrained Pytorch <a href="https://arxiv.org/abs/2010.11929">Vision Transformer</a> Models including following
<br>
* vit_s16_224
* vit_b16_224
* vit_b16_384
* vit_b32_384
* vit_l16_224
* vit_l16_384
* vit_l32_384
<br>
Implementation based off <a href=https://github.com/google-research/vision_transformer>official jax repository</a> and <a href="https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py">timm's implementation</a><br>

## Usage
---------------------
1) List Pretrained Models.
```Python
from vistrans import VisionTransformer
VisionTransformer.list_pretrained()
```
2) Create Pretrained Models.
```Python
from vistrans import VisionTransformer
model = VisionTransformer.create_pretrained(name, img_size, in_ch, num_classes)
```
3) Create Custom Model
```Python
from vistrans import VisionTransformer
model = VisionTransformer.create_model(img_size, patch_size, in_ch, num_classes,
                                       embed_dim, depth, num_heads, mlp_ratio,
                                       drop_rate, attention_drop_rate, hybrid,
                                       norm_layer, bias)
```
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De finale Euro UEFA is dichtbij, maak kans op een ticket en bekijk de wedstrijd live!!!
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

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rstatmon 1.2.1
A monitoring tool for raspberry pi
Requires Python: >=3.6
Keywords: raspberry pi, flask

Raspi-StatMon
=============

Raspberry pi Status Monitor (StatMon) is simple web application that allow you to monitor statistic data such as CPU temperature and Usage of Raspberry pi on the graph.You can also add a graph to monitor the data obtained from the external sensor connected to the raspi.


See [here](https://git-ogawa.github.io/raspi-statmon/) for installation, usage and more details.


![](docs/img/demo.gif)