semvec/pypi-packages huggingface dataset:
dioscuri 0.2.1
Read/write Gemini WorkList (gwl) files.
Keywords: biology

Project description
===================

Dioscuri provides classes and methods for working with Gemini WorkList (gwl) files.

A Gemini worklist file is a text file that contains pipetting instructions for the Tecan Freedom EVO robots. Dioscuri uses the Freedom EVOware software's specification of the gwl format.


**Install:**

.. code:: bash

  pip install dioscuri

**Web documentation:** `<https://edinburgh-genome-foundry.github.io/Dioscuri/>`_

**Github page:** `<https://github.com/Edinburgh-Genome-Foundry/Dioscuri>`_


**License:** MIT

Copyright 2020 Edinburgh Genome Foundry, University of Edinburgh


More biology software
---------------------

.. image:: https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/Edinburgh-Genome-Foundry.github.io/master/static/imgs/logos/egf-codon-horizontal.png
  :target: https://edinburgh-genome-foundry.github.io/

Dioscuri is part of the `EGF Codons <https://edinburgh-genome-foundry.github.io/>`_ synthetic biology software suite for DNA design, manufacturing and validation.
cheez-sdk 0.1.0
SDK for Cheez USB/BLE Devices
Requires Python: >=3.7


# Cheez SDK

## Installation

```bash
pip install cheez-sdk
```

## Quick Start

```python
from cheez_sdk import CheezSDK

# Initialize the SDK
sdk = CheezSDK()

# List available ports
ports = sdk.list_ports(verbose=True)

# Find specific devices
device_ports = sdk.find_devices("CheezUSB_VCP", "CheezBLE_VCP")

# Connect to a device
if device_ports:
    decoder = sdk.connect(device_ports[0])

    # Async data reading example
    import asyncio
    
    async def read_data():
        while True:
            data = await decoder.read_data()
            if data:
                print(f"Received data: {data}")
                print(f"Current packet rate: {decoder.get_packet_rate()} packets/sec")
            await asyncio.sleep(0.1)

    asyncio.run(read_data())
```

## Features

- Easy device port discovery
- Simple serial connection management
- Async data reading
- Configurable logging
- Error handling and validation

## Configuration

Customize device VID/PID mappings in the `config.json` file.

## License

[Your License Here]
```
torch-things 0.0.7
Helpful utilities for working with PyTorch.
Requires Python: >=3.9

# torch-things

A collection of useful PyTorch utilities and dataset helpers.

## Installation

```bash
pip install torch-things
```

## Features

### DelegatingSubset

A PyTorch dataset subset class that properly delegates all dataset attributes to the underlying dataset. This is particularly useful when working with datasets that have custom attributes that need to be preserved when creating subsets.

```python
from torch_things.dataset import DelegatingSubset
from torch.utils.data import Dataset

# Create your dataset
class MyDataset(Dataset):
    def __init__(self):
        self.data = torch.randn(100, 3, 32, 32)
        self.targets = torch.randint(0, 10, (100,))
        self.classes = ['class1', 'class2', 'class3']  # Custom attribute
    
    def __len__(self):
        return len(self.data)
    
    def __getitem__(self, idx):
        return self.data[idx], self.targets[idx]

# Create a subset that preserves all attributes
dataset = MyDataset()
subset = DelegatingSubset(dataset, indices=[0, 1, 2, 3])

# Access custom attributes from the subset
print(subset.classes)  # ['class1', 'class2', 'class3']
```
plasmid-assessor 0.2.1
Plasmid assessment for Golden Gate cloning
Keywords: biology, dna

Plasmid assessor
================

Plasmid assessment for Golden Gate cloning


**Install:**

.. code:: bash

    pip install plasmid_assessor


**Web documentation:** `<https://edinburgh-genome-foundry.github.io/Plasmid_assessor/>`_


**Github page:** `<https://github.com/Edinburgh-Genome-Foundry/Plasmid_assessor>`_


**License:** MIT

Copyright 2021 Edinburgh Genome Foundry, University of Edinburgh


More biology software
---------------------

.. image:: https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/Edinburgh-Genome-Foundry.github.io/master/static/imgs/logos/egf-codon-horizontal.png
  :target: https://edinburgh-genome-foundry.github.io/

Plasmid assessor is part of the `EGF Codons <https://edinburgh-genome-foundry.github.io/>`_ synthetic biology software suite for DNA design, manufacturing and validation.
python-binary-tree 1.0.2
Binary tree implementation for Python

# python-binary-tree
A simple implementation of a binary tree in Python.

## Installation
```bash 
pip install python-binary-tree
```
## Usage
```python
from binary_tree import BinaryTree
from binary_tree import BinaryTreeNode
# Create a binary tree and add nodes
bt = BinaryTree()
# Create nodes with values
root = BinaryTreeNode(0)
node1 = BinaryTreeNode(1)
node2 = BinaryTreeNode(2)
node3 = BinaryTreeNode(3)
node4 = BinaryTreeNode(4)
node5 = BinaryTreeNode(5)

# Add relationships between nodes
root.add_left(node1)
root.add_right(node2)

node1.add_right(node3)
node2.add_right(node4)
node1.add_left(node5)

# Insert nodes into the binary tree
bt.insert(root)
bt.insert(node1)
bt.insert(node2)

bt.draw()
```
### Example Output
![exampleplot.png](https://raw.githubusercontent.com/HangoverHGV/python-binary-tree/master/exampleplot.png)
debug2 0.1.0
A debug Python package

# DEBUG2

This library helps in debug activity.

No more putting print in between lines of big scripts and trying to do the RCA.

The library helps you store the entries of each debug points, as effortlessly as print.

The entries are stored in json format.

The entries helps in creating a lineage of the script execution.

There are 2 available methods in this package :
- dprint
- dprint2

## dprint
This method is for simple use cases.

It takes 3 input parameters :
- param_name - the label for the parameter
- param_value - the value of the parameter
- file_name (optional) - for storing the entries in json format.

By default the file name for storing the entries is debug_db.json. Custom name and path can be provided.

## dprint2
This method is for advanced use cases.

It takes 5 input parameters :
- script_name - name of the script from which the call is made.
- execution_id - this is to keep the entries of each execution in separate files.
- param_name - the label for the parameter
- param_value - the value of the parameter
- file_name (optional) - for storing the entries in json format.

The json file is in the format of TinyDB, hence portable, and can be easy parsed, with each entries, with their own doc_id.


## Usage

Here is a simple example on how to use the package :

```python
from debug2 import debug2 as dbg
dbg_file_name ='123debug'

def add(a,b):
    return a+b
    
def sub(a,b):
    return a-b

def mul(a,b):
    return a*b

def avg(a,b):
    return (a+b)/2
    

if __name__ == "__main__":

    data = {"type":"credit",
            "balance":10000,
            "amount":200}

    if data["type"] == 'credit':
        balance = add(data["balance"],data["amount"])
        dbg.dprint("new_balance",balance)

        
    if data["type"] == 'debit':
        balance = sub(data["balance"],data["amount"])
        dbg.dprint("new_balance",balance,"debit")


```