semvec/pypi-packages huggingface dataset:
etempmail 4.0.0.0
A simple module to get free disposable temporary email address
License: MIT
Requires Python: >=3.7
Keywords: temp mail, temporary mail, disposable mail, temp email, etempmail, etempmail.com

# etempmail

[![PyPI](https://img.shields.io/pypi/v/etempmail)](https://pypi.org/project/etempmail/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/etempmail)](https://pypi.org/project/etempmail/)
[![PyPI - License](https://img.shields.io/pypi/l/etempmail)](https://pypi.org/project/etempmail/)

A simple module to get free disposable temporary email address.

## Installation

To install etempmail use pip:

```bash
pip install etempmail
```

## Usage

```python
from etempmail import TempMail

# recovery: str = None, url: str = 'https://etempmail.com', debug_response: bool = True
temp_mail = TempMail()  # or TempMail('OGFHVIX7915')

print(temp_mail.id)
# 7915

print(temp_mail.email)
# sidavm5dhc@upperbox.xyz

print(temp_mail.recovery)
# OGFHVIX7915

print(temp_mail.inbox())
# [{'subject': 'test', 'from': 'Anonymousemail <noreply@gmail.com>', 'date': '16/08/2022 19:40:47', 'body': 'Test Body Code: 123'}]

temp_mail.recover('OGFHVSZ115741')  # Recover email address
temp_mail.change()  # Change email address
```

## Note

You can use the following domains or similar:

+ https://etempmail.com
+ https://gecicimail.com.tr
+ https://toprakmail.com
+ https://segamail.com

## License

The MIT License (MIT). Please see [License File](LICENSE) for more information.
iac-inscript 1.0.1
python代码一键加密
License: MIT

# jmpy

![](https://img.shields.io/badge/python-3.0-brightgreen)

## 简介

将python代码一键加密为so或pyd。支持单个文件加密，整个项目加密。

Git仓库地址: https://github.com/Boris-code/jmpy.git

## 安装

    pip install iac-inscript

## 使用方法

    iac-inscript -i "xxx project dir" [-o output dir]

加密后的文件默认存储在 dist/project_name/ 下
crossandra 2.2.1
A fast and simple enum/regex-based tokenizer with decent configurability
License: MIT
Requires Python: >=3.8

# Crossandra
Crossandra is a fast and simple tokenization library for Python operating on
enums and regular expressions, with a decent amount of configuration.

## Installation
Crossandra is available on PyPI and can be installed with pip, or any other
Python package manager:
```sh
$ pip install crossandra
```
(Some systems may require you to use `pip3`, `python -m pip`, or `py -m pip`
instead)

## [Documentation]

## Examples
```py
from enum import Enum
from crossandra import Crossandra

class Brainfuck(Enum):
    ADD = "+"
    SUB = "-"
    LEFT = "<"
    RIGHT = ">"
    READ = ","
    WRITE = "."
    BEGIN_LOOP = "["
    END_LOOP = "]"

bf = Crossandra(Brainfuck, suppress_unknown=True)
print(*bf.tokenize("cat program: ,[.,]"), sep="\n")
# Brainfuck.READ
# Brainfuck.BEGIN_LOOP
# Brainfuck.WRITE
# Brainfuck.READ
# Brainfuck.END_LOOP
```
```py
from crossandra import Crossandra, Rule, common

def hex2rgb(hex_color: str) -> tuple[int, int, int]:
    r, g, b = (int(hex_color[i:i+2], 16) for i in range(1, 6, 2))
    return r, g, b

t = Crossandra(
    ignore_whitespace=True,
    rules=[
        Rule(r"#[0-9a-fA-F]{6}", hex2rgb),
        common.WORD
    ]
)

text = "My favorite color is #facade"
print(t.tokenize(text))
# ['My', 'favorite', 'color', 'is', (250, 202, 222)]
```
```py
# Supporting Samarium's numbers and arithmetic operators
from enum import Enum
from crossandra import Crossandra, Rule

def sm_int(string: str) -> int:
    return int(string.replace("/", "1").replace("\\", "0"), 2)

class Op(Enum):
    ADD = "+"
    SUB = "-"
    MUL = "++"
    DIV = "--"
    POW = "+++"
    MOD = "---"

sm = Crossandra(
    Op,
    ignore_whitespace=True,
    rules=[Rule(r"[\\/]+", sm_int)]
)

print(*sm.tokenize(r"//\ ++ /\\/ --- /\/\/ - ///"))
# 6 Op.MUL 9 Op.MOD 21 Op.SUB 7
```

## Contributing

Contributions are welcome!

Please open an issue before submitting a pull request (unless it's a minor
change like fixing a typo).

To get started:
1. Clone your fork of the project.
2. Set up the project with `just install` (uses [uv]).
3. After you're done, run `just check` to check your changes.

> [!note]
> If you don't want to use [`just`][just], simply look up the recipes
> in the project's [`justfile`][justfile].

## License
Crossandra is licensed under the MIT License.

If you have any questions, or would like to get in touch, join my
[Discord server]!

[Documentation]: https://trag1c.github.io/crossandra/
[Discord server]: https://discord.gg/C8QE5tVQEq
[just]: https://github.com/casey/just
[justfile]: https://github.com/trag1c/crossandra/blob/main/justfile
[uv]: https://github.com/astral-sh/uv
sima-torch 0.0.2
Paper - Pytorch
License: MIT
Requires Python: <4.0,>=3.10
Keywords: artificial intelligence, deep learning, optimizers, Prompt Engineering

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# Sima Implementation
Implementation of the model from the deepmind paper "Scaling Instructable Agents Across Many Simulated Worlds" [PAPER LINK](https://arxiv.org/abs/2404.10179)


## Install
`$ pip3 install -U sima-torch`

## Usage
```python
import torch 
from sima_torch.transformer import SimaTransformer

# Example
x = torch.randint(0, 256, (1, 1024))

# Instantiate the model
model = SimaTransformer(
    dim=512,
    enc_depth=6,
    enc_heads=8,
    dec_depth=6,
    dec_heads=8,
    tie_token_emb=False,
    num_tokens=20000,
    num_memory_tokens=20,
    encoder_dim=512,
    decoder_dim=512,
    max_seq_len=1024,
)

out = model(x)
print(out.shape)  # torch.Size([1, 1024, 512])

```


# License
MIT

# Citation
```bibtex
@misc{simateam2024scaling,
      title={Scaling Instructable Agents Across Many Simulated Worlds}, 
      author={SIMA Team and Maria Abi Raad and Arun Ahuja and Catarina Barros and Frederic Besse and Andrew Bolt and Adrian Bolton and Bethanie Brownfield and Gavin Buttimore and Max Cant and Sarah Chakera and Stephanie C. Y. Chan and Jeff Clune and Adrian Collister and Vikki Copeman and Alex Cullum and Ishita Dasgupta and Dario de Cesare and Julia Di Trapani and Yani Donchev and Emma Dunleavy and Martin Engelcke and Ryan Faulkner and Frankie Garcia and Charles Gbadamosi and Zhitao Gong and Lucy Gonzales and Kshitij Gupta and Karol Gregor and Arne Olav Hallingstad and Tim Harley and Sam Haves and Felix Hill and Ed Hirst and Drew A. Hudson and Jony Hudson and Steph Hughes-Fitt and Danilo J. Rezende and Mimi Jasarevic and Laura Kampis and Rosemary Ke and Thomas Keck and Junkyung Kim and Oscar Knagg and Kavya Kopparapu and Andrew Lampinen and Shane Legg and Alexander Lerchner and Marjorie Limont and Yulan Liu and Maria Loks-Thompson and Joseph Marino and Kathryn Martin Cussons and Loic Matthey and Siobhan Mcloughlin and Piermaria Mendolicchio and Hamza Merzic and Anna Mitenkova and Alexandre Moufarek and Valeria Oliveira and Yanko Oliveira and Hannah Openshaw and Renke Pan and Aneesh Pappu and Alex Platonov and Ollie Purkiss and David Reichert and John Reid and Pierre Harvey Richemond and Tyson Roberts and Giles Ruscoe and Jaume Sanchez Elias and Tasha Sandars and Daniel P. Sawyer and Tim Scholtes and Guy Simmons and Daniel Slater and Hubert Soyer and Heiko Strathmann and Peter Stys and Allison C. Tam and Denis Teplyashin and Tayfun Terzi and Davide Vercelli and Bojan Vujatovic and Marcus Wainwright and Jane X. Wang and Zhengdong Wang and Daan Wierstra and Duncan Williams and Nathaniel Wong and Sarah York and Nick Young},
      year={2024},
      eprint={2404.10179},
      archivePrefix={arXiv},
      primaryClass={cs.RO}
}
```

# Todo
- [ ] Implement Phenaki as a video encoder
- [ ] Create mouse and keyboard policy