semvec/pypi-packages huggingface dataset:
bean-inquiry 0.3.0
A CLI tool to INject parameters into Beancount queries specified in your ledger
Requires Python: >=3.11

# Beancount INquiry

A CLI tool to INject parameters into Beancount queries specified in your ledger

## Usage

Beancount INquiry will inject parameters into query directives specified in your ledger file using pythons `.format` function, and so uses the same syntax. Here is an example query directive with two parameters:

```
2025-01-01 query "balance" "SELECT date, account, sum(number) as total WHERE account ~ '{}' AND date >= {} ORDER BY account"
```

And then pass in the ledger, the name of the query, and the list of parameters

```
bean-inquiry ledger.beancount balance Assets 2014-05-01
```

You can also use indexed placeholders:

```
2025-01-01 query "balance" "SELECT date, {0}, sum(number) as total WHERE {0} ~ '{1}' AND date >= {2} ORDER BY {0}"
...
bean-inquiry ledger.beancount balance account Assets:Bank 2025-05-01
```

And named placeholders, with parameter keys separated with a colon:

```
2025-01-01 query "balance" "SELECT date, {select}, sum(number) as total WHERE {select} ~ '{account}' AND date >= {date} ORDER BY {select}"
...
bean-inquiry ledger.beancount balance select:account account:Assets:Bank date:2025-05-01
```

See the `--help` for more options

```
bean-inquiry --help
```

## Installation

There are two different versions of Beancunt INquiry, the **[CLI tool](#cli)** and the **[script](#script)**, the main difference being that the **CLI tool** can run stand-alone and has `beanquery` as a dependency, and the **script** does not have dependencies but needs `bean-query` installed on your system and in your PATH. Also currently the **script** can only run query directives that are on a single line in your ledger, whereas the **CLI tool** can run query directives that traverse multiple lines.

### CLI

#### Pipx (recommended)

Install using pipx from [PyPi](https://pypi.org)

```
pipx install bean-inquiry
bean-inquiry --help
```

#### Build from source using pipx

Clone this repository and install systemwide using pipx:

```
git clone https://github.com/aleyoscar/beancount-inquiry.git
cd beancount-inquiry
pipx install .
bean-inquiry --help
```

#### Run using poetry

Clone this repository and run using [poetry](https://python-poetry.org/)

```
git clone https://github.com/aleyoscar/beancount-inquiry.git
cd beancount-inquiry
poetry install
poetry run bean-inquiry
```

### Script

Does not need `beanquery`, but does need the `bean-query` executable installed on your system and in your PATH. Simply download [bean-inquiry.py](https://github.com/aleyoscar/beancount-inquiry/blob/main/bean-inquiry.py) or clone this repository and run the script `bean-inquiry.py` in the root project folder:

```
python bean-inquiry.py --help
```

## Dependencies

This project uses [beancount](https://github.com/beancount/beancount) to parse the ledger and [beanquery](https://github.com/beancount/beanquery) for running the queries.
blazegraph-io 0.0.1
Document intelligence platform - coming soon
Requires Python: >=3.9
Keywords: document intelligence graph pdf analysis parsing parser

# Blazegraph IO

**Document Intelligence Platform**

🔥 Transform any document into intelligent, interactive knowledge graphs.

## Status

This package is currently in development.

## Features (Coming Soon)

- 📄 **Multi-Format Support** - PDF, Word, PowerPoint, Web pages
- 📊 **Export Capabilities** - Multiple output formats
- 🎯 **Bounding Box Detection** - Precise content mapping

## Use Cases

- **Document Analysis** - Research papers, reports, legal documents
- **Knowledge Extraction** - Turn documents into structured data/graphs
- **Content Intelligence** - Understand document relationships
- **Research Workflows** - Academic and professional research

## Links

- **Website**: [blazegraph.io](https://blazegraph.io)
- **Documentation**: Coming Soon
- **GitHub**: [amplifytechnology/blazegraph-io](https://github.com/amplifytechnology/blazegraph-io)

## License

MIT © 2025 Amplify Technology
paddle-nnAudio 0.0.3
A fast GPU audio processing toolbox with 1D convolutional neural network
Requires Python: >=3.6

# paddle-nnAudio

paddle-nnAudio 是基于 PaddlePaddle 卷积神经网络作为后端的音频处理工具箱。通过这种方式， 梅尔频谱可以在神经网络训练过程中实时从音频生成，并且傅里叶核（如 CQT 核）可以被训练。paddle-nnAudio 移植自 [nnAudio](https://github.com/KinWaiCheuk/nnAudio)，旨在为 PaddlePaddle 生态提供类似的音频处理能力。

## 安装
```bash
pip install git+https://github.com/PlumBlossomMaid/paddle-nnAudio.git
```
或
```bash
pip install paddle-nnAudio
```

## 快速开始
```python
import paddle
import librosa
import numpy as np
from ppAudio.features import MelSpectrogram

def main() -> None:
    paddle.device.set_device("gpu:0") # 使用gpu:0进行运算
    example_y, example_sr = librosa.load(librosa.example('vibeace', hq=False)) # 加载音频

    n_fft, win_length = (512, 400)
    melspec = MelSpectrogram(n_fft=n_fft, win_length=win_length, hop_length=512)
    X = melspec(paddle.to_tensor(example_y).unsqueeze(0)).squeeze() # 将波形前向传播以获取 spectrogram
    X_librosa = librosa.feature.melspectrogram(example_y, n_fft=n_fft, win_length=win_length, hop_length=512) # 设置对照
    assert np.allclose(X.cpu(), X_librosa, rtol=1e-3, atol=1e-3) # 精度对齐
    print("done")


if __name__ == "__main__":
    main()

```

## 依赖项
- Numpy >= 1.14.5
- Scipy >= 1.2.0
- PaddlePaddle >= 2.0.0 (或PaddlePaddle-gpu >= 2.0.0)
- Python >= 3.6
- librosa = 0.7.0

## 引用
如果您使用了 paddle-nnAudio，请引用原 nnAudio 的论文：

K. W. Cheuk, H. Anderson, K. Agres and D. Herremans, "nnAudio: An on-the-Fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolutional Neural Networks," in IEEE Access, vol. 8, pp. 161981-162003, 2020, doi: 10.1109/ACCESS.2020.3019084.

### BibTex
```
@ARTICLE{9174990,
  author={K. W. {Cheuk} and H. {Anderson} and K. {Agres} and D. {Herremans}},
  journal={IEEE Access}, 
  title={nnAudio: An on-the-Fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolutional Neural Networks}, 
  year={2020},
  volume={8},
  number={},
  pages={161981-162003},
  doi={10.1109/ACCESS.2020.3019084}}
```

## 许可证
[MIT License](LICENSE)
pointpca2 0.5.1
A Rust-based Python library for extracting pointpca2 features from Point Clouds.
Requires Python: <3.13,>=3.10

# PointPCA2 - Python Lib
#### A seamless Python integration to the Rust implementation of PointPCA2

This project aims to integrate Python to [pointpca2-rs](https://github.com/akaTsunemori/pointpca2-rs), enabling the use of Python's comprehensive data science tools combined to the performance provided by the Rust implementation of PointPCA2.

## Setup
### From PyPI
```bash
pip install pointpca2
# or
python -m pip install pointpca2
```

### From source
- **Prerequisites**
  - rustc == 1.77.2
  - anaconda3 >= 23.7.4

- **Build**
```bash
# Clone this repository
https://github.com/akaTsunemori/pointpca2-pylib.git

# cd into the project folder
cd pointpca2-pylib

# Setup and activate the conda environment
conda env create -f environment.yml
conda activate pointpca2-pylib

# Compile the project into a python module using maturin
maturin develop -r
```

## Usage
```python
import open3d as o3d
import numpy as np
import pointpca2

# Load both reference and test PCs
PC_REF_PATH = "examples/pcs/amphoriskos_vox10.ply"
pc_ref = o3d.io.read_point_cloud(PC_REF_PATH)
points_a, colors_a = np.asarray(pc_ref.points), np.asarray(pc_ref.colors)
PC_TEST_PATH = "examples/pcs/tmc13_amphoriskos_vox10_dec_geom01_text01_octree-predlift.ply"
pc_test = o3d.io.read_point_cloud(PC_TEST_PATH)
points_b, colors_b = np.asarray(pc_test.points), np.asarray(pc_test.colors)

# Compute the features (predictors) through the pointpca2 function
predictors = pointpca2.compute_pointpca2(
    points_a, colors_a, points_b, colors_b, search_size=81, verbose=True
)
print(*predictors)
```

## Contributing
Feel free to open any kind of issues and contributions related to this Python package. Issues related to the Rust implementation should be open on the [pointpca2-rs](https://github.com/akaTsunemori/pointpca2-rs) repository.

## Acknowledgments
- [pointpca2-rs](https://github.com/akaTsunemori/pointpca2-rs) - An implementation of PointPCA2 in Rust

## License
MIT License

---

> GitHub [@akaTsunemori](https://github.com/akaTsunemori)
objective-lol 0.0.2
Python bindings for Objective-LOL

# Objective-LOL Python Bindings

Python bindings for the Objective-LOL programming language - a modern, strongly-typed language inspired by LOLCODE.

## Installation

```bash
pip install objective-lol
```

## Quick Start

```python
import objective_lol as olol

# Create a VM instance
vm = olol.ObjectiveLOLVM()

# Execute Objective-LOL code
code = """
I CAN HAS STDIO?
HAI ME TEH FUNCSHUN MAIN
    I HAS A VARIABLE X TEH INTEGR ITZ 42
    SAYZ WIT X
KTHXBAI
"""

vm.execute(code)  # Prints: 42
```

## Features

- **Execute Objective-LOL code**: Run complete programs or code snippets
- **Python integration**: Call Python functions from Objective-LOL and vice versa
- **Type conversion**: Automatic conversion between Python and Objective-LOL types
- **Module system**: Import and use custom modules
- **Class definitions**: Define and use classes from Python

## Advanced Usage

### Defining Python Functions for Objective-LOL

```python
vm = olol.ObjectiveLOLVM()

def add_numbers(a, b):
    return a + b

vm.define_function("add_numbers", add_numbers)

code = """
I CAN HAS STDIO?
HAI ME TEH FUNCSHUN MAIN
    I HAS A VARIABLE RESULT TEH INTEGR ITZ add_numbers WIT 10 AN WIT 20
    SAYZ WIT RESULT
KTHXBAI
"""

vm.execute(code)  # Prints: 30
```

### Working with Classes

```python
vm = olol.ObjectiveLOLVM()

class Calculator:
    def add(self, x, y):
        return x + y

    def multiply(self, x, y):
        return x * y

vm.define_class(Calculator)

code = """
I CAN HAS STDIO?
HAI ME TEH FUNCSHUN MAIN
    I HAS A VARIABLE CALC TEH Calculator ITZ NEW Calculator
    I HAS A VARIABLE SUM TEH INTEGR ITZ CALC DO add WIT 5 AN WIT 3
    SAYZ WIT SUM
KTHXBAI
"""

vm.execute(code)  # Prints: 8
```

## Type Mapping

| Objective-LOL Type | Python Type |
|-------------------|-------------|
| INTEGR            | int         |
| DUBBLE            | float       |
| STRIN             | str         |
| BOOL              | bool        |
| NOTHIN            | None        |
| BUKKIT (array)    | list        |
| BASKIT (map)      | dict        |

## Links

- [Main Project](https://github.com/bjia56/objective-lol)
- [Language Documentation](https://github.com/bjia56/objective-lol/tree/main/docs)

## License

MIT License

## Changelog

### [0.0.2] - 2025-09-16

#### Changed
- Modified octal prefix from `0` to `0o`

#### Fixed
- Fixed a stack corruption crash on Windows by using compatibility function calls with separate goroutines

### [0.0.1] - 2025-09-14

#### Added
- Initial Python bindings for Objective-LOL interpreter
- Pre-built wheels for Windows, macOS, and Linux for Python 3.9+