semvec/pypi-packages huggingface dataset:
nlator 1.0
A simple translator package for multiple languages.
Requires Python: >=3.6

# Nlator

Nlator is a simple Python package for translating text between multiple languages and detecting the language of a given text. It uses the Google Translate API for its functionality.

## Installation

You can install the package using pip:

```bash
pip install nlator
```

## Usage

Here are some examples of how to use the Nlator package:

# Importing The Package
```python
import nlator
```

## Translating Text

To translate text from one language to another, you can use the `translate` method. For example, to translate "Hello" from English to Spanish:

```python
translator = nlator.Nlator()
hello_es = translator.translate("Hello", from_lang="en", to_lang="es")
print(hello_es)  # Output: Hola
```

## Detecting Language

You can also detect the language of a given text using the `findlanguage` method. For example, to detect the language of the word "ciao":

```python
language = translator.findlanguage("ciao")
print(language)  # Output: it (Italian)
```

## Supported Languages
The package supports a wide range of languages. You can find the list of supported languages in the https://cloud.google.com/translate/docs/languages
obsidian-brain 0.1.3
Give claude access to your obsidian brain
Requires Python: >=3.10

# obsidian-brain MCP server

Give claude access to your obsidian brain

### Install

#### Claude Desktop

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

#### Development/Unpublished Servers Configuration
```
"mcpServers": {
  "obsidian-brain": {
    "command": "uv",
    "args": [
      "--directory",
      "/Users/shubhaankar/github.com/Shubhaankar-Sharma/obsidian_brain",
      "run",
      "obsidian-brain"
    ],
    "env": {
      "OBSIDIAN_MIND_PATH": "/path/to/obsidian/vault"
    }
  }
}

```

#### Published Servers Configuration 
```
"mcpServers": {
  "obsidian-brain": {
    "command": "uvx",
    "args": [
      "obsidian-brain"
    ],
    "env": {
      "OBSIDIAN_MIND_PATH": "/path/to/obsidian/vault"
    }
  }
}
```

## Development

### Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:
```bash
uv sync
```

2. Build package distributions:
```bash
uv build
```

This will create source and wheel distributions in the `dist/` directory.

3. Publish to PyPI:
```bash
uv publish
```

Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`

### Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).


You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:

```bash
npx @modelcontextprotocol/inspector uv --directory /Users/shubhaankar/github.com/Shubhaankar-Sharma/obsidian_brain run obsidian-brain
```


Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
executor-invest-helper 0.1.5
Database Executor for Invest Helper
Requires Python: >=3.5

# Database executor

**Техническое название:** executor_invest_helper

## Описание

Database executor — это мощный инструмент для взаимодействия с базой данных мега-крутого телеграм-бота про инвестиции. Этот пакет упрощает выполнение запросов к базе данных и управление данными, что позволяет разработчикам сосредоточиться на создании функционала бота.

## Установка

Для установки пакета используйте pip:

```bash
pip install executor_invest_helper
noko-cli 0.1.5
A simple CLI interface for Noko time tracking.

# Noko CLI

The Noko CLI allows you to log a time entry directly from the CLI and sync all of your calendar events from GCal to Noko.

It makes three CLI commands available:

| Command        | Shorthand | Description                                        |
|----------------|-----------|----------------------------------------------------|
| noko_cli_setup | ncs       | Configure the Noko CLI app                         |
| noko_log       | nl        | Log a time entry to Noko                           |
| call_sync      | cs        | Sync events from Google Calendar into Noko entries |

## Installation

To install the complete app and dependencies, run:

```shell
pip install noko-cli
```

To install only what's required to one specific command, run:

```shell
pip install noko-cli[noko_log]
```

```shell
pip install noko-cli[call_sync]
```

**Note:** To be able to run the `call_sync` command, you'll need to add a `credentials.json` file with the Google web credentials to `.noko_cli`. 

## noko_cli_setup

Run the `noko_cli_setup` or `ncs` command to set up the application. It'll ask you to provide the information needed to run the commands.

The result of this command will be a `config.json` file with the necessary details.

## noko_log

The `noko_log` or `nl` command requires at least three parameters: minutes, project and description. It also allows an
optional date parameter.

It supports four flags:

| Flag | Meaning                              |
|------|--------------------------------------|
| -u   | Add the unbillable tag to the entry. |
| -p   | Add the pair tag to the entry.       |
| -c   | Add the calls tag to the entry.      |
| -y   | Mark the entry as from yesterday.    |

Example usage:

```shell
nl 30 Operations "Slack convos and emails"
```

```shell
nl --date "2024-09-20" 60 Sales "Sales call with Lead X"
```

## gcal_sync

The `gcal_sync` or `cs` command does not require any parameters. It allows an optional date parameter.

Example usage:

```shell
cs
```

```shell
cs -d "2024-09-20"
```
currency-normalizer 0.0.2
A module to normalize currency strings
Requires Python: >=3.7

Whole purpose of this package is to normlize currency strings to the standard currency codes

You can input USD or $ or USD dollars and it will be normalized. This is it. 


```

cn = CurrencyNormalizer()
r=cn.normalize("$")
print(r)

# output is "USD"

```