semvec/pypi-packages huggingface dataset:
spydcmtk 1.2.19
Simple python dicom toolkit.
License: MIT
Requires Python: >=3.9.0
Keywords: ct, dicom, imaging, medical, mri

# *spydcmtk*

*Simple PYthon DiCoM Tool Kit*

Dicom organisational, querying and conversion toolkit

*spydcmtk* is a pure Python package built on top of [*pydicom*](https://github.com/pydicom/pydicom).

This package extends pydicom with a class structure based upon the Patient-Study-Series-Image hierarchy. In addition, it provides a number of built in routines for common actions when working with dicom files, such as human readable renaming, anonymisation, searching and summarising. 


## Installation

Using [pip](https://pypi.org/project/spydcmtk/):
```
pip install spydcmtk
```

## Quick start

If you installed via pip then *spydcmtk* console script will be exposed in your python environment. 

Access via:
```bash
spydcmtk -h
```
to see the commandline usage available to you.


If you would like to incorporate spydcmtk into your python project, then import as:
```python
import spydcmtk

listOfStudies = spydcmtk.dcmTK.ListOfDicomStudies.setFromDirectory(MY_DICOM_DIRECTORY)
# Example filtering
dcmStudy = listOfStudies.getStudyByDate('20230429') # Dates in dicom standard string format: YYYYMMDD
dcmSeries = dcmStudy.getSeriesBySeriesNumber(1)
# Example writing new dicom files with anonymisation
dcmStudy.writeToOrganisedFileStructure(tmpDir, anonName='Not A Name')

```


# Configuration

spydcmtk uses a spydcmtk.conf file for configuration. 

By default spydcmtk.conf files are search for in the following locations: 

1. source_code_directory/spydcmtk.conf (file with default settings)
2. $HOME/spydcmtk.conf
3. $HOME/.spydcmtk.conf
4. $HOME/.config/spydcmtk.conf
5. Full file path defined at environment variable: "SPYDCMTK_CONF"
6. Full path passed as commandline argument to `spydcmtk`

Files are read in the above order with each subsequent variable present over writing any previously defined. 
For information on files found and variables used run:

`spydcmtk -INFO` 


## Documentation

Clear documentation of basic features can be seen by running the *"spycmtk -h"* command as referenced above. 
For detailed documentation please see [spydcmtk-documentation](https://fraser29.github.io/spydcmtk/)
remote-box 0.1.2
Type-safe remote Python function execution framework with multiple backend support
License: MIT
Requires Python: >=3.12
Keywords: async, distributed, execution, pydantic, remote

# Remote Box

Type-safe remote Python function execution framework with multiple backend support.

## Installation

```bash
uv add remote-box
```

## Quick Start

Execute Python functions on remote machines with type safety:

```python
from pathlib import Path
from pydantic import BaseModel
from remote import remote, E2B, BackendShell

class Input(BaseModel):
    name: str

class Output(BaseModel):
    greeting: str

@remote(
    local_project_root=Path(__file__).parent,
    backend=E2B(
        shell=BackendShell.BASH4,
        template_prefix="my-project"
    )
)
async def greet(input: Input) -> Output:
    # This code runs on a remote E2B sandbox!
    return Output(greeting=f"Hello {input.name}!")

# Usage
result = await greet(Input(name="World"))
print(result.greeting)  # "Hello World!"
```

## Features

- **Type-safe**: Inputs/outputs validated using Pydantic models
- **Multiple backends**:
  - [E2B](https://e2b.dev) - Execute on remote secure sandboxes
  - Subprocess - Local execution for development
- **Async-first**: Built on asyncio for high performance
- **Automatic serialization**: No manual JSON handling needed

## Backends

### E2B (Production)
Execute code on remote secure sandboxes via [E2B](https://e2b.dev). Perfect for:
- Running untrusted code safely
- Scaling compute workloads
- Isolating execution environments

### Subprocess (Development)
Execute code in local subprocesses. Ideal for development and testing.

## License

MIT