semvec/pypi-packages huggingface dataset:
table-diff 0.2.3
Tool to compare tables
Requires Python: >=3.10

# Table Diff

Table Diff is a Python package that provides a text-based interface for comparing two tables. It is designed to be used by data analysts and data scientists to compare two tables and identify differences between them, especially as transformation rules are adjusted in an ETL pipeline.

The diff between two tables is printed to stdout as Markdown, and can be saved to a Markdown, HTML, or DuckDB file.

## Features

* Generate a diff report between two tables.
* View the diff quickly in Markdown.
* Supports the following input formats:
    * CSV
    * Parquet
* Supports the following output formats:
    * HTML (summary)
    * DuckDB (comprehensive)
    * Markdown (summary)
    * PDF (summary - experimental)
* View common enum/value transitions.

## Getting Started

1. Install Python 3.10 or later, and the `uv` Python package manager.

2. Install this package using `uv tool`:
```bash
uv tool install table-diff

# Optionally, install with PDF support (experimental):
uv tool install table-diff --with pymupdf
```

3. Run the either of the following to compare two tables:
```bash
table_diff <old_csv_path> <new_csv_path> -u PrimaryKeyCol1 PrimaryKeyColN
```

For development environment setup, please refer to the `CONTRIBUTING.md` guide.

## Contributing
Please submit Bug Reports and Merge Requests to the [GitLab project](https://gitlab.com/parker-research/table-diff).

Please refer to the `CONTRIBUTING.md` file for more details about the contribution policy.

## License
This project is licensed using the MIT License. For more information, see the LICENSE file.

Note that this project has been created and modified with the help of Large Language Model (LLM)-based tools like GitHub Copilot and ChatGPT.
screcode 2.2.0
RECODE - resolution of the curse of dimensionality in single-cell data analysis
Requires Python: >=3.8

# RECODE - python code

### Installation

To install RECODE package, use `pip` as follows:

```
$ pip install screcode
```

### Documentation

[Tutorials and API reference](https://yusuke-imoto-lab.github.io/RECODE/index.html)


### Requirements
* Python3
* numpy
* scipy
* scikit-learn
bradford-white-wave-client 0.1.2
Client for Bradford White Wave API
Requires Python: >=3.9

# Bradford White Wave Client

A Python client library for the Bradford White Wave API for water heaters. The "Wave"
platform is new and separate from the previous "Connect" platform. For instance the original Aerotherm uses an
optional "Connect" module add-on, while the Aerotherm G2 has built-in connectivity to the "Wave" platform.

This library is designed for use in a Home Assistant integration and general automation tasks.

To build this I took some inspiration from the [bradford-white-connect-client](https://github.com/ablyler/bradford_white_connect_client)
library and did some digging into how the new app works.

## Authentication

Some manual steps are required to authenticate with the API, since for the time being I have been unable to fully automate the process.

1. Run the example script:
   ```bash
   python example_script.py
   ```
2. The script will generate a login URL. Open it in your browser.
3. Log in with your Bradford White Wave credentials.
4. The browser will receive a redirect, but (at least for Firefox) it will fail to follow this redirect and show an error page.
5. Open the network tab in your browser's development tools and refresh the page. You'll see the failed redirect response. Look for the location: header starting with `com.bradfordwhiteapps.bwconnect://` in the response.
![Redirect Example](redirect_example.png)
6. Copy the full url and paste it back into the script terminal.
7. The script will save your credentials to `.credentials.json` so future runs of the script will skip the above steps (this file is in .gitignore).

## Usage

Once you have a `refresh_token`, you can initialize the client:

```python
client = BradfordWhiteClient(refresh_token="YOUR_REFRESH_TOKEN")
await client.authenticate()
```

From there, there are several methods available:

```python
# List devices
await client.list_devices()

# Get status
await client.get_status("MAC_ADDRESS")

# Get energy usage
await client.get_energy("MAC_ADDRESS", "hourly")

# Set temperature
await client.set_temperature("MAC_ADDRESS", 120)

# Set mode
from bradford_white_wave_client.models import BradfordWhiteMode
await client.set_mode("MAC_ADDRESS", BradfordWhiteMode.HEAT_PUMP)
```

## Installation

```bash
pip install bradford-white-wave-client
```

## Features
- Async/Await support using `aiohttp`
- Type-hinted with `Pydantic` models
- Auto-refresh of access tokens

## Disclaimers
- This is an unofficial library and is not affiliated with Bradford White.
- I have only tested with an Aerotherm G2.
- This is largely written in "collaboration" with Gemini, though I have manually reviewed the code and verified the flows.