semvec/pypi-packages huggingface dataset:
ffseval 1.1.4
Evaluation of fitness for service
License: MIT
Requires Python: >=3.6

# FFSeval
## Evaluation of fitness for service
#### Shinsuke Sakai   
 Emeritus Professor, The University of Tokyo, Japan   
 Visiting Professor, Yokohama National University, Japan



### Operation check


```python
from FFSeval import FFS as ffs
cls=ffs.Treat()
L=cls.Set('L_2_b')
data={
   'Ri':275e-3,
   't':16e-3,
   'Sy':514,
   'p':8.0,
   'a':11e-3
}
L.SetData(data)
L.Calc()
L.GetRes()
#{'Lr': 0.7709984917738504, 'pc': 10.376155187533834}
```
lemoDB 1.0.3
A lightweight, schema-aware, CSV-based database with auto-increment IDs
License: MIT
Requires Python: >=3.8
Keywords: database, csv, lightweight, schema, nosql

# lemoDB

A lightweight, schema-aware, CSV-based database for Python.

## Installation

```bash
pip install lemoDB
```

## Quick Start

```python
from lemoDB import LemonDB

# Define schema
schema = {
    "username": "string",
    "email": "string",
    "age": "integer"
}

# Create database
db = LemonDB(name="users", schema=schema)

# Save records
db.save(
    ("alice", "alice@example.com", 25),
    ("bob", "bob@example.com", 30)
)

# Query data
users = db.findAll()
alice = db.find({"username": "alice"})

# Update
db.updateOne({"username": "alice"}, {"age": 26})

# Delete
db.deleteOne({"username": "bob"})
```

## Features

- Schema validation with type checking
- Auto-increment IDs
- Simple CRUD operations
- CSV-based storage
- Zero external dependencies