semvec/pypi-packages huggingface dataset:
portalbrasil.devsite 1.0.0a1
Ferramenta de sites para profissionais de TI.
Requires Python: >=3.12
Keywords: CMS, Plone, PortalBrasil

# PortalBrasil: DevSite

Ferramenta de sites para profissionais de TI.

## Features

TODO: List our awesome features

## Installation

Install portalbrasil.devsite with `pip`:

```shell
pip install portalbrasil.devsite
```

And to create the Plone site:

```shell
make create_site
```

## Add features using `plonecli` or `bobtemplates.plone`

This package provides markers as strings (`<!-- extra stuff goes here -->`) that are compatible with [`plonecli`](https://github.com/plone/plonecli) and [`bobtemplates.plone`](https://github.com/plone/bobtemplates.plone).
These markers act as hooks to add all kinds of subtemplates, including behaviors, control panels, upgrade steps, or other subtemplates from `plonecli`.

To run `plonecli` with configuration to target this package, run the following command.

```shell
make add <template_name>
```

For example, you can add a content type to your package with the following command.

```shell
make add content_type
```

You can add a behavior with the following command.

```shell
make add behavior
```

```{seealso}
You can check the list of available subtemplates in the [`bobtemplates.plone` `README.md` file](https://github.com/plone/bobtemplates.plone/?tab=readme-ov-file#provided-subtemplates).
See also the documentation of [Mockup and Patternslib](https://6.docs.plone.org/classic-ui/mockup.html) for how to build the UI toolkit for Classic UI.
```

## Contribute

- [Issue Tracker](https://github.com/portal-br/devsite/issues)
- [Source Code](https://github.com/portal-br/devsite/)

## License

The project is licensed under GPLv2.

## Credits and Acknowledgements 🙏

This was generated by the [cookieplone-templates backend_addon template](https://github.com/plone/cookieplone-templates/tree/main/backend_addon) on 2025-03-14 18:50:03. A special thanks to all contributors and supporters!
melia-fastapi 0.5.0
fastapi project generator and servicemanager
Requires Python: <4.0,>=3.11

# Melia

### Tree

fastapi-starter/
  ├── app/
  │   ├── __init__.py
  │   ├── main.py                     # FastAPI app instance
  │   ├── core/
  │   │   ├── __init__.py
  │   │   ├── config.py              # Settings & config
  │   │   ├── database.py            # Database setup
  │   │   └── security.py            # Auth & security
  │   ├── api/
  │   │   ├── __init__.py
  │   │   ├── deps.py                # Dependencies
  │   │   └── endpoints/
  │   │       ├── __init__.py
  │   │       ├── auth.py            # Auth endpoints
  │   │       └── users.py           # User endpoints
  │   ├── models/
  │   │   ├── __init__.py
  │   │   └── user.py                # Database models
  │   └── schemas/
  │       ├── __init__.py
  │       └── user.py                # Pydantic schemas
  ├── tests/
  │   ├── __init__.py
  │   └── test_main.py
  ├── .env.example
  ├── .gitignore
  ├── Dockerfile
  ├── pyproject.toml
  ├── docker-compose.yml
  ├── melia.yml                      # Melia configuration
  └── README.md

## installation

````bash
pip install melia-fastapi
````

## Usage

- install poetry

- Create a new project with Melia:

```bash
melia new <project_name>
```
biosaic 0.1.5
Biosaic: a lightweight DNA and protein k-mer tokenizer with pre-trained vocab support.
Requires Python: >=3.10
Keywords: bioinformatics, tokenizer, dna, protein, kmer, machine-learning

# Biosaic

## Overview

Biosaic(Bio-Mosaic) is a tokenizer library built for [Enigma2](https://github.com/shivendrra/enigma2). It contains: Tokenizer, Embedder for DNA & Amino Acid Protein Sequences. Has a VQ-VAE & Evoformer architecture based encoders that could convert sequences into embeddings and vice-versa for model training use-case.

## Features

- **Tokenization:** converts the sequences into K-Mers.
- **Encoding:** converts sequences into embeddings for classification, training purposes.
- **Easy use:** it's very basic and easy to use library.
- **SoTA encoder:** Evoformer & VQ-VAE model are inspired from the [AlphaFold-2](https://www.biorxiv.org/content/10.1101/2024.12.02.626366v1.full)

## Prerequisites

### System Requirements

- **Operating System**: Linux, macOS, or Windows with support for GCC or Clang.
- **Python**: Version 3.9 or higher.

### Dependencies

- **Python Modules**:
  - `pickle`: for loading and saving model files.
  - `os`: for file and path handling.
  - `urllib`: for loading the vocabs from repo.
  - `tempfile`: for loading the vocabs from repo.

## Installation

#### 1. From PyPI:
  
  ```cmd
	pip install biosaic
  ```

#### 2. Clone the Repo:
  
  ```bash
  git clone https://github.com/delveopers/biosaic.git
  cd biosaic
  ```

## Usage

Create an instance of the tokenizer with a specified k-mer size, & split them into tokens, encode & decode them fastly:

```python
import biosaic
from biosaic import tokenizer

token = tokenizer(mode="dna", kmer=3, continuous=True)
print(token.vocab_size)

sequence = "TCTTACATAGAAAGGAGCGGTATTTGGTATGAATTTATTTGCAACTGACTG"
encoded = token.encode(sequence)
decoded = token.decode(encoded)
tokenized = token.tokenize(sequence)

print(tokenized)
print(encoded[:100])
print(decoded[:300])
print(decoded == sequence)
```

For more information refer to the docs:
- [Usage.md](https://github.com/delveopers/biosaic/blob/dev/docs/Usage.md)
- [Technical.md](https://github.com/delveopers/biosaic/blob/dev/docs/Technical.md)

#### ***Output***

```cmd
84

['TCT', 'CTT', 'TTA', 'TAC', 'ACA', 'CAT', 'ATA', 'TAG', 'AGA', 'GAA', 'AAA', 'AAG', 'AGG', 'GGA', 'GAG', 'AGC', 'GCG', 'CGG', 'GGT', 'GTA', 'TAT', 'ATT', 'TTT', 'TTG', 'TGG', 'GGT', 'GTA', 'TAT', 'ATG', 'TGA', 'GAA', 'AAT', 'ATT', 'TTT', 'TTA', 'TAT', 'ATT', 'TTT', 'TTG', 'TGC', 'GCA', 'CAA', 'AAC', 'ACT', 'CTG', 'TGA', 'GAC', 'ACT', 'CTG']

[75, 51, 80, 69, 24, 39, 32, 70, 28, 52, 20, 22, 30, 60, 54, 29, 58, 46, 63, 64, 71, 35, 83, 82, 78, 63, 64, 71, 34, 76, 52, 23, 35, 83, 80, 71, 35, 83, 82, 77, 56, 36, 21, 27, 50, 76, 53, 27, 50]

TCTTACATAGAAAGGAGCGGTATTTGGTATGAATTTATTTGCAACTGACTG

True
```
zimer 0.4.0
A simple decorator for timing functions.
Requires Python: >=3.7

# zimer

A lightweight utility package that ships two decorators that make everyday Python development a bit easier:

* **`zimer`** – measure the execution time of synchronous and asynchronous functions, optionally repeating them and printing the average runtime.
* **`with_retry`** – automatically retry a function when it raises an exception, with optional exponential back-off. Works with both sync and async callables.

---

## Installation

```bash
pip install zimer
```

---

## `zimer` – timing decorator

```python
from zimer import zimer
import time, asyncio

@zimer                      # one run, prints elapsed time
def slow_sync():
    time.sleep(1)

@zimer(repeats=3)           # three runs, prints average
async def slow_async():
    await asyncio.sleep(0.5)

slow_sync()
asyncio.run(slow_async())
```

---

## `with_retry` – retry decorator

```python
from zimer import with_retry
import random, asyncio

# --- synchronous example -----------------------------------------
@with_retry(num_retries=3, backoff=1, backoff_exponent=2)  # 1s, 4s between tries
def flaky_sync():
    if random.random() < 0.7:
        raise ValueError("Still broken …")
    return "✓ finally worked"

# --- asynchronous example ----------------------------------------
@with_retry                # default: 5 retries, no back-off
async def flaky_async():
    if random.random() < 0.5:
        raise RuntimeError("Try again …")
    return "✓ async worked"

print(flaky_sync())
print(asyncio.run(flaky_async()))
```

Arguments:
* `num_retries` – total attempts (initial call + retries). Must be ≥ 1.
* `backoff` – initial pause between retries (seconds). Must be ≥ 0.
* `backoff_exponent` – growth factor applied to the retry count to compute the
  wait time: `sleep = backoff * ((attempt + 1) ** backoff_exponent)`.

---

## Testing

Clone the repo and run:

```bash
pip install -r requirements-dev.txt  # pytest, etc.
pytest -q
```

All unit tests live under `tests/` and cover both decorators.

---

## License

MIT © 2024 Zubin Aysola