semvec/pypi-packages huggingface dataset:
obs2nlm 1.1.2
Convert Obsidian vaults to NotebookLM sources
Requires Python: >=3.13
Keywords: obsidian, notebooklm, ai, llm, machine-learning

# obs2nlm - Make a NotebookLM-friendly source from an Obsidian Vault

`obs2nlm` is a simple command line tool designed to turn an
[Obsidian](https://obsidian.md) vault into a single
[Markdown](https://en.wikipedia.org/wiki/Markdown) file that can be uploaded
to Google's [NotebookLM](https://notebooklm.google.com/) (or presumably used
with other LLM tools for similar purposes).

It's probably fair to say that it's "opinionated" in that I wrote this to
serve my specific purpose; but where possible I've attempted to make it
generic and configurable.

## Installing

`obs2nlm` is a Python application and [is distributed via
PyPI](https://pypi.org/project/obs2nlm/). It can be installed with tools such
as [pipx](https://pipx.pypa.io/stable/):

```sh
pipx install obs2nlm
```

or [`uv`](https://docs.astral.sh/uv/):

```sh
uv tool install obs2nlm
```

Also, if you do have uv installed, you can simply use
[`uvx`](https://docs.astral.sh/uv/guides/tools/):

```sh
uvx obs2nlm
```

to run `obs2nlm`.

## Using

See [the main documentation](https://obs2nlm.davep.dev/) for details on how
to use the tool.

## Getting help

If you need some help using `obs2nlm`, or have ideas for improvements, please
feel free to drop by [the
discussions](https://github.com/davep/obs2nlm/discussions) and ask or
suggest. If you believe you've found a bug please feel free to [raise an
issue](https://github.com/davep/obs2nlm/issues).

[//]: # (README.md ends here)
klarfrs 0.2.1
Klarfrs is a parser written in Rust to read klarf files as a python dictionary. Currently it only supports version 1.2.
Requires Python: >=3.9
Keywords: parser, rust-lang, semiconductor, klarf, wafers

# klarfrs
Klarfrs is a parser written in Rust to read klarf files into structured objects. It supports versions 1.2 and 1.8 (via dynamic column handling).

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install klarfrs.

```bash
pip install klarfrs
```

## Usage

```python
import klarfrs
from typing import List

filename: str = "klarf.001"

# Parse Header
klarf_header: klarfrs.KlarfData = klarfrs.parse(filename)
print("File Version:", klarf_header.file_version)
print("Lot ID:", klarf_header.lot_id)

# Parse Defects
klarf_defects: List[klarfrs.DefectList] = klarfrs.parse_defects(filename)
for defect in klarf_defects:
    print(f"Defect ID: {defect.defect_id}, X: {defect.xrel}, Y: {defect.yrel}")
```

## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](https://choosealicense.com/licenses/mit/)
anuite-hesaplamalari 0.1.1
Anüite hesaplamaları için Python paketi
Requires Python: >=3.8

# Anüite Hesaplamaları

## Geliştirici Hakkında
- **Ad Soyad:** Ahsen Ekici  
- **Üniversite:** Selçuk Üniversitesi  
- **İletişim:** ekiciahsenn@gmail.com  

---

## Proje Hakkında

### Amaç
- Anüite hesaplamalarını Python programlama dili ile gerçekleştirmek  
- Aktüeryal ve finans matematiği kavramlarını uygulamalı hale getirmek  

### Kapsam
- Dönem sonu ödemeli anüite hesaplamaları  
- Dönem başı ödemeli anüite hesaplamaları  
- Bileşik anüite (ödeme dönemi ≠ faiz dönemi) hesaplamaları  
- Ertelenmiş anüite hesaplamaları  
- Artan ve azalan anüite hesaplamaları  
- Değişken faizli anüite hesaplamaları  
- Nominal ve efektif faiz dönüşümleri  

---

## Kurulum / Çalıştırma Adımları

```bash
git clone https://github.com/kullanici_adi/anuite_hesaplamalari.git
cd anuite_hesaplamalari

---

## Örnek Kullanım
from anuite_hesaplamalari import (
    donem_sonu_anuite,
    donem_basi_anuite,
    bilesik_anuite,
    ertelenmis_anuite,
    nominalden_efektife
)

donem_sonu_anuite(1000, 0.10, 5)
donem_basi_anuite(1000, 0.10, 5)
bilesik_anuite(500, 0.12, 12, 4, 10)
ertelenmis_anuite(1000, 0.08, 5, 3)
nominalden_efektife(0.12, 12)

---
### Parametrelerin Anlamları

| Parametre | Açıklama |
|----------|----------|
| **A** | Her dönem yapılan ödeme tutarı |
| **i** | Dönemsel faiz oranı |
| **n** | Toplam ödeme dönemi sayısı |
| **m** | Yıldaki faizlendirme sayısı (nominal faiz için) |
| **k** | Yıldaki ödeme sayısı |
| **d** | Erteleme süresi (ödemenin başlamadığı dönem sayısı) |
| **g** | Dönemsel artış / azalış tutarı |
| **j** | Nominal faiz oranı |
zest 0.1.3
An interactive Python learning platform with automated code testing and feedback
Requires Python: >=3.9
Keywords: python, learning, coding, challenges, education

# Zest

Python programming challenge platform with secure code execution.

## Structure

```
zest/
├── website/           # Flask web application
│   ├── auth.py       # User authentication
│   ├── models.py     # Database models
│   ├── questions.py  # Question routes
│   ├── api.py        # Submission API
│   └── templates/    # HTML templates
├── aws-lambda/       # Code executor (Docker container)
├── terraform/        # Infrastructure as code
├── tests/            # Pytest test suite
└── src/zest/         # Python package
```

## Local Development

```bash
# Install dependencies
pip install -e ".[dev]"

# Run development server
python run.py

# Run tests
pytest
```

## Deployment

### AWS Lambda (Code Executor)

```bash
cd terraform
terraform init
terraform apply -target=aws_ecr_repository.executor

# Build and push Docker image
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin $(terraform output -raw ecr_repository_url | cut -d'/' -f1)
cd ../aws-lambda && docker build -t zest-code-executor .
docker tag zest-code-executor:latest $(cd ../terraform && terraform output -raw ecr_repository_url):latest
docker push $(cd ../terraform && terraform output -raw ecr_repository_url):latest

# Deploy Lambda + API Gateway
cd ../terraform && terraform apply

# Save these outputs
terraform output api_gateway_url
terraform output -raw api_key_value
```

### PythonAnywhere (Web App)

```bash
# Upload code via Git or Files tab
git clone https://github.com/yourusername/zest.git

# Create virtualenv in PythonAnywhere console
mkvirtualenv --python=/usr/bin/python3.10 zest
pip install -e .

# Configure web app:
# - Source code: /home/username/zest
# - Working directory: /home/username/zest
# - Virtualenv: /home/username/.virtualenvs/zest
# - WSGI file: from website import create_app; application = create_app()

# Set environment variables in WSGI file:
import os
os.environ['AWS_LAMBDA_URL'] = 'your-api-gateway-url'
os.environ['AWS_API_KEY'] = 'your-api-key'
os.environ['SECRET_KEY'] = 'generate-random-key'

# Reload web app
```
aws logs tail /aws/lambda/zest-code-executor --follow
```

View API Gateway metrics in AWS Console or CloudWatch.

## Cost Estimates

For low-moderate usage (~10,000 submissions/month):
- **Lambda**: ~$0.50/month
- **API Gateway**: ~$0.04/month
- **ECR**: ~$0.05/month
- **CloudWatch**: ~$0.50/month

**Total**: ~$1-2/month

## Troubleshooting

### Code execution fails
1. Check `.env` configuration
2. Test locally: `python scripts/test_executor_local.py`
3. Check Lambda logs in CloudWatch

### Database errors
1. Ensure `DATABSE_DEV` setting matches your database
2. Check database credentials
3. Run migrations if needed

### AWS deployment issues
See [terraform/README.md](terraform/README.md) troubleshooting section.