semvec/pypi-packages huggingface dataset:
urllib3_request 0.1.5
urllib3 request extension.
License: MIT
Requires Python: <4.0,>=3.12
Keywords: urllib3, request

# urllib3 request extension.

## Installation

You can install via [pypi](https://pypi.org/project/urllib3_request/)

```console
pip install -U urllib3_request
```

## Usage

```python
from urllib3_request import request
```
philo-chat 0.3.1
Chat with your favorite philosophers - Nietzsche, Socrates, and more!
License: MIT
Requires Python: >=3.10

# PhiloChat

![PyPI](https://img.shields.io/pypi/v/philo-chat)
![License](https://img.shields.io/pypi/l/philo-chat)

Chat with your favorite philosophers - Nietzsche, Socrates, and more-in real-time!

## 📌 Overview

Philo-Chat is an interactive command-line application that allows users to have AI-powered conversations with famous philosophers. Each philosopher responds in their distinctive style, language, and perspective. Users can create multiple chats, select philosophers, and maintain conversation histories.

---

## 🌟 Features

* **User Authentication:** Signup and login functionality to secure chats.
* **Multiple Chats:** Create multiple chat sessions with different philosophers.
* **AI-Powered Philosopher Responses:** Each philosopher responds intelligently using an AI completion engine.
* **Chat Management:** Delete or exit chats at any time.
* **Interactive CLI:** Easy-to-use command-line interface with clear prompts and messages.
* **Chat History:** Maintains conversation history per chat.

---

## 🚀 Quick Start

```bash
# 1. Install
pip install -U philo-chat

# 2. Create .env file with your API credentials
echo "BASE_URL=your_url" > .env
echo "OPENAI_API_KEY=your_key" > .env
echo "MODEL_NAME=your_model" > .env

# 3. Run!
philo-chat
```

---

## ⚙️ Commands

* `signup` - Create a new user account.
* `login` - Log in with an existing account.
* `logout` - Log out from the current account.
* `delete_account` - Delete your account.
* `new_chat` - Start a new chat with a philosopher.
* `select_chat` - Enter an existing chat session.
* `exit_chat` - Exit the current chat session.
* `delete_chat` - Delete a specific chat session.
* `list_chats` - Show all your existing chats and their philosophers.
* `list_philosophers` - Show all available philosophers to chat with.
* `help` - Show available commands.
* `exit` - Exit the application.

---

## 📄 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
py-ftmarkets 0.1.5
Financial Times (markets.ft.com) data source for Python
License: MIT
Requires Python: >=3.10

# py-ftmarkets

Financial Times (markets.ft.com) data source for Python. Provides a high-level API and CLI to search for securities, fetch historical data, and validate prices.

## Installation

```bash
uv add py-ftmarkets
# or
pip install py-ftmarkets
```

## CLI Usage

The package provides a CLI tool named `ftmarkets`.

### Lookup a Ticker

Resolve an ISIN or Symbol to the Financial Times ticker format (e.g., `AAPL:NSQ`).

```bash
# Basic lookup by ISIN
ftmarkets lookup --isin DE000A0S9GB0

# Lookup with price and date validation (Returns 1 best matching ticker)
ftmarkets lookup --isin DE000A0S9GB0 --price 117.81 --date 2025-12-12 --limit 1

# Lookup with filters (currency, country, asset-class)
ftmarkets lookup --isin DE000A0S9GB0 --currency EUR --country DE --asset-class ETF

# Return all matching results in JSON format
ftmarkets lookup --isin DE000A0S9GB0 --limit 0 --format json
```

### Fetch History and Validate

Fetch historical data for a resolved ticker and optionally validate a trade price on a specific date.

```bash
# Fetch 1 month of history for an ISIN
ftmarkets history --isin DE000A0S9GB0

# Fetch 1 year of history and validate a price
ftmarkets history --isin DE000A0S9GB0 --period 1y --price 120.50 --date 2025-01-15
```

## Library Usage

`py-ftmarkets` implements the `DataSource` interface from `pydantic-market-data`.

```python
from ftmarkets.api import FTDataSource
from pydantic_market_data.models import SecurityCriteria

source = FTDataSource()

# Resolve a security
criteria = SecurityCriteria(isin="DE000A0S9GB0")
symbol = source.resolve(criteria)
print(f"Ticker: {symbol.ticker}")

# Fetch history
history = source.history(symbol.ticker, period="1mo")
df = history.to_pandas()
print(df.tail())

# Validate price
is_valid = source.validate(symbol.ticker, target_date="2025-01-15", target_price=120.50)
print(f"Price valid: {is_valid}")
```

## Features

- **Robust Resolution**: Searches by ISIN, Symbol, or Description.
- **Smart Mapping**: Prioritizes results based on preferred exchanges and currency.
- **Price Validation**: Verifies if a security traded within a range or near a specific price on a given date.
- **Pandas Integration**: Historical data is easily convertible to Pandas DataFrames.
- **Modern Python**: Built with Pydantic v2 and async-ready architecture (though currently synchronous).
httpx_request 0.1.9
httpx request extension.
License: MIT
Requires Python: <4.0,>=3.12
Keywords: httpx, request

# httpx request extension.

## Installation

You can install via [pypi](https://pypi.org/project/httpx_request/)

```console
pip install -U httpx_request
```

## Usage

```python
from httpx_request import request
```