semvec/pypi-packages huggingface dataset:
waterworksai 3.0.0
Official Python client for waterworks.ai API
Requires Python: >=3.9

# waterworksai

[![PyPI version](https://img.shields.io/pypi/v/waterworksai)](https://pypi.org/project/waterworksai/)
[![Python Version](https://img.shields.io/pypi/pyversions/waterworksai)](https://pypi.org/project/waterworksai/)
[![License](https://img.shields.io/badge/license-MIT-green)](LICENSE)

Official Python client for the [waterworks.ai](https://waterworks.ai) API, providing seamless access to:

- Inflow & Infiltration decomposition
- Water component analysis
- 48-hour flow forecasting
- Leakage & sewer blockage detection
- Pipe survival & remaining useful life (RUL) estimation

---

## Installation

```bash
pip install waterworksai
```

## Quick Start

```python
import pandas as pd
from waterworksai import WaterworksClient
from waterworksai.adapters import from_dataframe
from waterworksai.tasks.forecast import Forecast48h

# Load your hourly flow CSV
df = pd.read_csv("hourly_flow.csv")
df["Date"] = pd.to_datetime(df["Date"])

# Convert to canonical TimeSeriesPoint
points = from_dataframe(df, time_col="Date", value_col="Volume")

# Initialize API client
client = WaterworksClient(api_key="YOUR_API_KEY")

# Run 48-hour forecast
result = client.post(
    "forecast",
    Forecast48h(df=points).payload()
)

print("Forecast MAE:", result["MAE"])
print("Forecast points:", result["forecast"])

```

## Examples
Examples

Full working examples for all tasks are available in the examples/ folder:

- forecast_48h.py

- inflow_infiltration.py

- leakage.py

- pipe_survival.py

These scripts demonstrate DataFrame integration, API calls, and result handling.

## License
MIT © waterworks.ai
nitrokeyapp 2.5.2
Graphical application to manage Nitrokey devices
Requires Python: <3.15,>=3.10

# Nitrokey App 2

This application allows to manage Nitrokey 3 devices. To manage Nitrokey Pro and Nitrokey Storage devices, use the older [Nitrokey App](https://github.com/Nitrokey/nitrokey-app).

## Documentation

The user documentation for Nitrokey App 2 is available on [docs.nitrokey.com](https://docs.nitrokey.com/software/nk-app2/).

## Compatibility

Nitrokey App 2 requires Python 3.10 or later.

## Development

See the [docs](./docs) directory for developer information.

## Author

Nitrokey GmbH, Jan Suhr and [contributors](https://github.com/Nitrokey/nitrokey-app2/graphs/contributors).

## License

Nitrokey App 2 is licensed under the Apache License, Version 2.0 (see the [LICENSE](./LICENSE) file or http://www.apache.org/licenses/LICENSE-2.0).
changelog-version-bump 0.4.9
A CLI tool to detect version labels in temp.md
Requires Python: >=3.7

# Bump versions automagically
Bump versions based on changelog entries.

# Setup
This package only works together with scriv and works best if used with hatch.

In the `scriv` configuration the following is assumed:
```toml
[tool.scriv]
format = "md"
categories = [
  "Major: Feature",
  "Minor: Feature",
  "Minor: Fix", 
  "Patch: Fix", 
  "Major: Business impact",
  "Minor: Business impact"
]
```
You can adjust the categories as you like the `BUMB: ` part is what is checked for, and the bumps must be `Major, Minor, Patch`


For a nice integration in hatch use these two additional env definition blocks:
```toml
[tool.hatch.envs.changelog]
dependencies = [
  "scriv",
  "changelog-version"
]

[tool.hatch.envs.changelog.scripts]
init = "mkdir changelog.d"
new = "scriv create --edit --add"
collate = "scriv print > temp.md && hatch version $(changelog-version-bump)  && scriv collect"
```
1) Initial setup needed once is the `init` part (feel free to not bother with a seperate command).

2) In each branch you'll need to run `scriv create` or `hatch run changelog:new` to create and edit the changelog fragment for scriv.

3) The actual magic is the `collate` comand that should run in `ci/cd` when you create tags / releases.

# Pre-commit hook

> This was originally created by [TypicalArray](https://github.com/TypicalArray).

Some places (like Azure DevOps) do not render `.md` files automatically. So in order to clean them up, this repo also contains a pre-commit hook which automatically removes all commented out lines, removes superfluous empty lines and enforces that all lines have to start with a `#` or a `-`, which helps with formatting. It can be used as follows:

```yaml
repos:
  - repo: https://github.com/banking-circle-advanced-analytics/changelog-version-bump
    rev: <insert-latest-release>
    hooks:
      - id: remove-comments
```

# FAQ
Can you change the options and headings?
No. It would be easy to add configurability via the toml and a tool.changelog-version-bump section but for now I see no need, the defaults should suffice.

Could this not just be some bash?
Yes. This code was actually bash, but for distribution and later configuration, see above, python scripts are easier.
hepbrowse 0.1.4
Interactive TUI for exploring HEP data files
Requires Python: >=3.10

# Welcome to HEPBrowse

HEPBrowse is a terminal-based browser for High-Energy Physics data files (`.h5` and `.root`).

## Features

- Browse the internal structure of HEP data files
- Visualize datasets with in-terminal plots

## Getting Started

1. Use the **sidebar** to navigate your data files.
2. Switch tabs to access different functionalities:
   - **Plot**: Visualize your datasets