semvec/pypi-packages huggingface dataset:
adnexus 0.1.7
Modern and fully typed declarative Di and IoC Framework
Requires Python: <4.0,>=3.11

[![tests](https://github.com/Nictec/Adnexus/actions/workflows/main.yml/badge.svg)](https://github.com/Nictec/Adnexus/actions/workflows/main.yml) [![docs](https://github.com/Nictec/adnexus/actions/workflows/docs.yml/badge.svg)](https://github.com/Nictec/adnexus/actions/workflows/docs.yml) [![build](https://github.com/Nictec/adnexus/actions/workflows/build.yml/badge.svg)](https://github.com/Nictec/adnexus/actions/workflows/build.yml)
# Adnexus Framework
**Adnexus is a modern and declarative DI and IoC framework using pydantic for config and data.**

## Key features

- **Fast:** Very high performance thanks to pydantic and preemptive wiring
- **Developer friendly:** Declarative Container definition to take the "Magic" out of DI
- **Good compatibility:** Can be used with almost every framework and supports async

## Installation
```bash
pip install adnexus
```

## Basic Example

```python3
from pathlib import Path
from datetime import datetime

from pydantic import BaseModel
from adnexus.containers import DeclarativeContainer
from adnexus.config.builtin import TOMLLoader
from adnexus.config import load_config
from adnexus.providers import FactoryProvider
from adnexus.markers import Provide
from adnexus.decorators import inject


class UpstreamInjectable:
    def __init__(self):
        self.time = datetime.now()

    def get_time(self):
        return self.time


class TestInjectable:
    def __init__(self, name: str, timer: Provide[UpstreamInjectable]):
        self.timer = timer
        self.name = name

    def greet(self):
        print(self.timer.get_time())
        return f"Hello {self.name}"


@inject
def test(greeter: Provide[TestInjectable]):
    print(greeter.greet())


class MyConfig(BaseModel):
    name: str


class MyContainer(DeclarativeContainer):
    # the loaded config can be accessed by calling MyContainer.config.<name>
    config = load_config(TOMLLoader(Path("/path/to/settings.toml")))

    injectables = [
        FactoryProvider(TestInjectable, config.name),
        FactoryProvider(UpstreamInjectable)
    ]


if __name__ == "__main__":
    container = MyContainer()
    container.wire([__name__])

    test()  # <-- dependencies are injected automatically
```
agi-med-metrics 0.0.7
Utils for agi-med team metric calculation

# agi-med-metrics

Стандартизация компонент общей библиотеки отдела для расчета метрик качества моделей

## Ответственный разработчик

@bakulin

## Метрики

### ML: 

- false positive rate
- false negative rate

### NLP: 

- BLEU
- ROUGE1, ROUGE2, ROUGEL
- cosine similarity

### CV: 

- mean character error rate

## Тесты

- `sudo docker-compose -f docker-compose.yaml up --build`
aiidalab-qe-vibroscopy 1.1.4
AiiDAlab QE plugin for vibrational spectoscopies.
Requires Python: >=3.8
Keywords: aiidalab, plugin

# aiidalab-qe-vibroscopy
Plugin to compute vibrational properties of materials via the aiida-vibroscopy AiiDA plugin

## Installation

Once cloned the repository, `cd` into it and:

```shell
pip install --user .
```

If you want to easily set up phonopy, use the CLI of this package (inspect it via `aiidalab-qe-vibroscopy --help`):

```shell.
pip install phonopy --user # if phonopy is not installed in your machine; it should be already installed as it is a dependency of the package.
aiidalab-qe-vibroscopy setup-phonopy # setup phonopy@localhost in AiiDA; this post-install command is automatically triggered if you install the plugin from the aiidalab-qe interface.
```

### h5py installation for arm64 architectures

In case the installation of the `aiidalab-qe-vibroscopy` fails due to `h5py` installation problem, you may try to first install
`h5py` by:

```shell
conda install h5py==3.11.0
```

this will install also the `hdf5` library as dependency.

## License

MIT

## Contact

miki.bonacci@psi.ch
andres.ortega-guerrero@empa.ch
gentleParserPy 1.0.0
This is my first module
Requires Python: >=3.7
Keywords: example python

# Simple JSON Parser

A simple JSON parser implemented in Python without using any external libraries. This parser can handle a limited subset of JSON, including strings, numbers, objects, arrays, booleans, and null values.

## Features

- Parses JSON strings into Python data structures (dictionaries and lists).
- Supports basic JSON data types: strings, numbers, objects, arrays, booleans, and null.
- No external dependencies; written entirely in Python.

## Installation

You can simply copy the `JSONParser` class into your Python project. There is no need for installation via pip or any other package manager.

## Usage

To use the JSON parser, create an instance of the `JSONParser` class with a JSON string and call the `parse()` method. Here's an example:

```python
from json_parser import JSONParser  # Adjust the import based on your file structure

json_text = '{"name": "John", "age": 30, "is_student": false, "courses": ["Math", "Science"], "address": null}'
parser = JSONParser(json_text)
parsed_data = parser.parse()

print(parsed_data)
```

## Error Handling
The parser raises ValueError for various issues, such as:

Unexpected end of input
Invalid JSON values
Unterminated strings
Missing colons or commas in objects and arrays

## Limitations
This parser is a basic implementation and may not handle all edge cases or complex JSON structures.
It does not support JSON features like comments or special escape sequences in strings.