semvec/pypi-packages huggingface dataset:
jzip-zig 0.0.8
Python bindings for jzip (Zig) - near-lossless embedding compression
Requires Python: >=3.10
Keywords: compression, embeddings, zstd, zig

# jzip Python Bindings

Python bindings for `jzip` (near-lossless compression for unit-norm embedding vectors).

## Install (dev)

Requires Zig and Python 3.10+.

```bash
pip install -e .
```

## Usage

```python
import numpy as np
import jzip

x = np.random.randn(1000, 384).astype(np.float32)
x /= np.linalg.norm(x, axis=1, keepdims=True)

blob = jzip.compress(x, level=1, threads=8)
y = jzip.decompress(blob, threads=8)
```

## PyPI

```bash
pip install jzip-zig
```
cyta 0.2.3
cython -a for terminal (no HTML/browser needed)
Requires Python: >=3.9
Keywords: cython, annotation, terminal, performance

# cyta

`cython -a` for terminal. No HTML, no browser.

## Usage

```bash
uvx cyta file.py                    # yellow = Python interaction
uvx cyta --annotate-fullc file.py   # show generated C code
uvx cyta --raw file.py              # plain text (no colors)
```

## Install

```bash
uv add cyta   # or: pip install cyta
```

## Example

```bash
$ cyta demo.py

demo.py
Yellow = Python interaction

  1 | import cython
  2 |
  3 | def slow_sum(data: list) -> float:  # highlighted yellow
  4 |     total = 0.0                      # highlighted yellow
  5 |     for x in data:                   # highlighted yellow
  6 |         total += x                   # highlighted yellow
  7 |     return total
```

## Name

**cy**thon **t**erminal **a**nnotation

## License

MIT
limesurvpy 0.0.4
A Python package for analyzing and visualizing LimeSurvey data.
Requires Python: >=3.8
Keywords: Limesurvey, Data Visualization, Survey Analysis

# limesurvpy

A Python package to support evaluating LimeSurvey questionnaires. The package provides support for various types of questions (e.g., lists, multiple choice questions, rankings, matrix questions, text questions, etc.). For supported question types, the tool compiles dataframes of responses, and generates a number of pre-defined plots to support interpretation. For multi-lingual surveys, the tool supports presenting information in a specific locale.

## Features

- **Import LimeSurvey structure files** (.lss format)
- **Import response data** from CSV files
- **Describe** responses using appropriate visualizations
- **Multi-language support** to show responses in any locale included in the questionnaire
- **Export** of processed data to Excel and CSV formats
- **Automatic translation** of text to user-defined language

## Installation

```bash
pip install limesurvpy
```

## Quick Start

### 1. Import and Create Survey Object

```python
from limesurvpy import Survey

# Create survey from LimeSurvey structure file
my_survey = Survey.from_lss(structure_filename='path/to/survey.lss')

# Get basic information about the survey
my_survey.summary()
my_survey.list_questions()
```

### 2. Import responses

```python
# Import responses from CSV file
# Note: Export responses from Limesurvey with question codes and response codes (not labels)
my_survey.import_responses('path/to/responses.csv', sep=',')
```

### 3. Analyze Questions

```python
# Get question details
my_survey.print_details(question_code='Q001', include_attributes=True)

# Compile responses and automatically plot results for convenience
responses = my_survey.describe(question_code='Q001')
```

### 4. Export Results

```python
# Export single question responses
Survey.export(responses, target='xlsx', excel_filename='results.xlsx')

# batch-export: If questions is None, export all
my_survey.export_questions(questions=None, target='xlsx', path=export_path, index=False)

```

## Multi-language Support

Compiled dataframes and plots will include labels for responses for the specified language. Text items are translated into the specified language using *deep-translator*.

```python
# Specify language for labels and responses
responses = my_survey.describe(question_code='Q001', lang='vi')  
```