semvec/pypi-packages huggingface dataset:
wtf-dev 0.1.4
What did I work on? A snarky standup generator.
Requires Python: >=3.11

# wtf-dev

A CLI tool that tells you what you worked on - with personality.

## Install

```bash
pip install wtf-dev
```

## Setup

```bash
wtf setup
```

This will prompt for your OpenRouter API key and let you pick a model.

## Usage

```bash
# what did I do today?
wtf

# look back N days
wtf --days 3

# only current repo
wtf --here

# copy to clipboard
wtf --copy
```

## Features

- **Standup summary** - LLM-generated summary of your commits
- **WIP tracking** - Shows uncommitted changes + what you're currently working on
- **Streak counter** - Track your commit streak
- **Late night detection** - Spots those 2am coding sessions
- **Branch context** - Shows which branches you touched
- **History** - View past standups with `wtf --history`
- **Cost tracking** - Track API spending with `wtf --spending`

## Output

```
PREVIOUSLY ON YOUR CODE...  Feb 02, 2026
  * 5 day streak
────────────────────────────────────────────────────────────

   ai-platform (main) ─── 2 commits
  ├─ feat(sdr): add langsmith tracing
  └─ feat(sdr): add automatic follow-up

   [wip]
   ai-platform ─── 3 files changed
  ├─ M src/api/routes.py
  └─ A src/new_feature.py

────────────────────────────────────────────────────────────

  Added LangSmith tracing and automatic follow-up for stale
  conversations in the SDR pipeline.

  Currently working on: Adding new API routes for validation.

  Two features down, infinite bugs to go.
```

## Flags

| Flag | Short | Description |
|------|-------|-------------|
| `--dir PATH` | `-d` | Scan a specific directory |
| `--here` | `-H` | Only current repo |
| `--days N` | `-n` | Look back N days (default: 1) |
| `--author NAME` | `-a` | Filter by author |
| `--copy` | `-c` | Copy to clipboard |
| `--history` | | View past standups |
| `--spending` | | Show API costs |
| `--json` | | Output as JSON |
xwmb 0.5.5
Efficient and lazy computation of Water Mass Budgets in arbitrary sub-domains of C-grid ocean models
Requires Python: >=3.11
Keywords: ocean mixing, water mass transformation

# xwmb

**xWMB** is a Python package that provides a efficient and lazy computation of Water Mass Budgets in arbitrary sub-domains of C-grid ocean models. Most of the heavy lifting is done by dependency packages by the same team of developers:
- [`sectionate`](https://github.com/MOM6-Community/sectionate): for computing transports normal to a section (open or closed)
- [`regionate`](https://github.com/hdrake/regionate): for converting between gridded masks and the closed sections that bound them
- [`xbudget`](https://github.com/hdrake/xbudget): for model-agnostic wrangling of multi-level tracer budgets
- [`xwmt`](https://github.com/NOAA-GFDL/xwmt): for computing bulk water mass transformations from these budgets

Documentation is not yet available, but the core API is illustrated in the example notebooks here and in each of the dependency packages.

If you use `xwmb`, please cite the companion manuscript: Henri F. Drake, Shanice Bailey, Raphael Dussin, Stephen M. Griffies, John Krasting, Graeme MacGilchrist, Geoffrey Stanley, Jan-Erik Tesdal, Jan D. Zika. Water Mass Transformation Budgets in Finite-Volume Generalized Vertical Coordinate Ocean Models. Journal of Advances in Modeling Earth Systems. 08 March 2025. DOI: [doi.org/10.1029/2024MS004383](https://doi.org/10.1029/2024MS004383)

Quick Start Guide
-----------------

**Minimal installation within an existing environment**
```bash
pip install xwmb
```

**Installing from scratch using `conda`**

This is the recommended mode of installation for developers.
```bash
git clone git@github.com:hdrake/xwmb.git
cd xwmb
conda env create -f docs/environment.yml
conda activate docs_env_xwmb
pip install -e .
```

You can verify that the package was properly installed by confirming it passes all of the tests with:
```bash
pytest -v
```

You can launch a Jupyterlab instance using this environment with:
```bash
python -m ipykernel install --user --name docs_env_xwmb --display-name "docs_env_xwmb"
jupyter-lab
```
MaaDebugger 1.18.1
MaaDebugger
Requires Python: <3.14,>=3.9

<p align="center">
  <img alt="LOGO" src="https://cdn.jsdelivr.net/gh/MaaAssistantArknights/design@main/logo/maa-logo_512x512.png" width="256" height="256" />
</p>

<div align="center">

# MaaDebugger

<a href="https://pypi.org/project/MaaDebugger/" target="_blank"><img alt="pypi" src="https://img.shields.io/pypi/dm/MaaDebugger?logo=pypi&label=PyPI"></a>

<a href="https://github.com/MaaXYZ/MaaDebugger/releases/latest" target="_blank"><img alt="release" src="https://img.shields.io/github/v/release/MaaXYZ/MaaDebugger?label=Release"></a>
<a href="https://github.com/MaaXYZ/MaaDebugger/releases" target="_blank"><img alt="pre-release" src="https://img.shields.io/github/v/release/MaaXYZ/MaaDebugger?include_prereleases&label=Pre-Release"></a>
<a href="https://github.com/MaaXYZ/MaaDebugger/commits/main/" target="_blank"><img alt="activity" src="https://img.shields.io/github/commit-activity/m/MaaXYZ/MaaDebugger?color=%23ff69b4&label=Commit+Activity"></a>

**[简体中文](./README.md) | [English](./README-en.md)**

</div>

## 需求版本

- Python >= 3.9,<= 3.13
- nicegui >= 2.21,< 3.0

## 安装

```bash
python -m pip install MaaDebugger
```

## 更新

```bash
python -m pip install MaaDebugger MaaFW --upgrade
```

## 使用

```bash
python -m MaaDebugger
```

### 指定端口

MaaDebugger 默认使用端口 **8011**。你可以通过使用 --port [port] 选项来指定 MaaDebugger 运行的端口。例如，要在端口 **8080** 上运行 MaaDebugger：

```bash
python -m MaaDebugger --port 8080
```

## 开发 MaaDebugger

```bash
cd src
python -m MaaDebugger
```

或者

使用 VSCode，在项目目录中按下 `F5`
findata-api 0.21
Common API to access financial data
Requires Python: >=3.9

# findata_api

Common API to access and manipulate financial data.


## Install

The library can be installed using *PyPi*:

```Shell
$ pip install findata_api
```

Or directly from the *Github* repository:

```Shell
$ pip install git+https://github.com/davidel/findata_api.git
```