semvec/pypi-packages huggingface dataset:
dicommeta 0.6.7
Dicom Metadata structures
Requires Python: >=3.10,<4.0

# DicomMeta

dicommeta is a Python library for efficiently storing large amounts of Dicom Metadata

## Installation

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

```bash
pip install dicommeta
```

## Usage

```python
from pprint import pprint

from dicommeta.Utils import Mode
from dicommeta.Struct import Study, Series, Instance

new_dicom_study = Study(
                        StudyInstanceUID='1.3.6.1.4.1.14519.5.2.1.4334.1501.757929841898426427124434115918',
                        SpecificCharacterSet='ISO_IR 100',
                        StudyDate="20190701",
                        StudyTime='023750',
                        AccessionNumber='sdfk324234',
                        ReferringPhysicianName='Dr Strange',
                        PatientName='John Doe',
                        PatientID='A123',
                        StudyUID='study001',
                        PatientBirthDate='20000101',
                        mode=Mode.CT)

new_series01 = Series(seriesUID='series001')
new_series01.add_instance(Instance(SOPinstanceUID='Instance001'))
new_series01.add_instance(Instance(SOPinstanceUID='Instance002'))
new_series01.add_instance(Instance(SOPinstanceUID='Instance002'))
new_dicom_study.add_series(new_series01)
new_series11 = Series(seriesUID='series001')
new_series11.add_instance(Instance(SOPinstanceUID='Instance002'))
new_dicom_study.add_series(new_series11)
new_series11.add_instance(Instance(SOPinstanceUID='Instance003'))
new_dicom_study.add_series(new_series11)

new_series02 = Series(seriesUID='series002')
new_series02.add_instance(Instance(SOPinstanceUID='Instance002'))
new_series02.add_instance(Instance(SOPinstanceUID='Instance003'))
new_dicom_study.add_series(new_series02)

pprint(new_dicom_study.get_dict())
pprint(new_dicom_study.get_series(seriesUID='series002'))

new_study01 = Study(StudyUID='study002', StudyDate=['20200101'])
new_series03 = Series(seriesUID='series003')
new_series03.add_instance(Instance(SOPinstanceUID='Instance01'))
new_study01.add_series(new_series03)

study_list = [new_dicom_study, new_study01]

for study in study_list:
    for instance in study.series_dict:
        pprint(study.get_series(instance))
        print("")

print(new_dicom_study.get_series_ids())

print(new_dicom_study.study_datetime)
print(new_dicom_study.patient_age)

print(new_study01.study_datetime)
print(new_study01.patient_age)


```

## 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/)
jaxprvis 0.0.1
A visualizer for JaxPrs
Requires Python: >=3.8

# JaxPr Visualizer

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
![License Badge](https://img.shields.io/badge/License-GPL3-red)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v1.json)](https://github.com/charliermarsh/ruff)
![Python Version](https://img.shields.io/badge/python-3.10-blue)


This project provides interactive visualizations of JAX computations.
Composite nodes can be expanded using left-click and contracted using right-click.
Space pauses the simulation.

## Usage Example

```python
import jax.numpy as jnp

from jax import make_jaxpr
from jax.core import ClosedJaxpr

import jaxprvis as jvis

def visualize_loop_unroll_jaxpr(iter: int) -> ClosedJaxpr:
    example_args = jnp.zeros((2, 2))

    def f(x, y):
        z = x
        for i in range(iter):
            z = (z + y) / x
        return z

    closed_jaxpr: ClosedJaxpr = make_jaxpr(f)(example_args, example_args)
    jvis.visualize(closed_jaxpr)
```


## Installation

<details>
<summary align="center">For Users</summary>

### Install from Pypi:
```bash
#Create and activate virtual environment (if not present yet)
python -m venv --upgrade-deps ./venv
source ./venv/bin/activate
pip install --upgrade build
# Install your JAX version
#e.g. pip install --upgrade "jax[cpu]"

pip install --upgrade jaxprvis
```
### Install from source:
```bash
# Clone
git clone https://github.com/PSilvestre/jaxprvis
cd jaxprvis

#Create and activate virtual environment
python -m venv --upgrade-deps ./venv
source ./venv/bin/activate
pip install --upgrade build

python -m build
pip install -e .

```

</details>

<details>
<summary align="center">For Developers</summary>

Similar to the above, but instead install the dev requirements.
Run the following to install:

```bash
# Clone
git clone https://github.com/PSilvestre/jaxprvis
cd CORAL

#Create and activate virtual environment
python -m venv --upgrade-deps ./venv
source ./venv/bin/activate
pip install --upgrade build

python -m build
pip install -e ".[dev]"

#Run the tests
pytest
```

</details>
datanalyse 0.0.8
A data analysis package.
Requires Python: >=3.11

# datanalyse

The package name datanalyse is a suitcase word for data and analyse - mainly of experimental data from the Combined Energy Lab at TU Dresden, but perhaps useful for others as well. However, due to its absolute alpha status, I cannot recommend it to anybody in the world but me.

It is more or less a tool-kit for my daily work as an experimentalist and data scientist and makes use of the fantastic packages pandas, pathlib and matplotlib.
pshlib 0.1.1
Causal embedding of shell commands into python code.
Requires Python: >=3.9,<4.0

# pshlib

Causal embedding of shell commands into python code.

## Example

You can break single long bash lines into nested python like multi-line statements:

```python
    res = psh(
    'VAR=world',
    """
        echo This is
            a multiline hello
            $VAR!
    """,
    ).output
    print(res)
    excepted = 'This is a multiline hello world!\n'
    assert excepted == res
```

## Installation

with pip:

    pip install pshlib

with poetry:

    poetry add git+https://gitlab.com:ewiger/pshlib.git

## License

Licensed under MIT. See LICENSE for details.


## Publish

    poetry publish --build
pymender 0.2.0
Mend your Python projects with reproducible refactors
Requires Python: >=3.10

# 👷‍♀️ PyMender

Perform entire codebase refactors in a way that is _reproducible_, _testable_ and _reviewable_. Obeys `.gitignore` by default.

## Usage

```bash
pip install pymender==0.2.0

pymender <codemod> <path_to_project>
```

## What codemods are available?

### ⚡ `FastAPIAnnotated`

Converts FastAPI endpoints to use the preferred `Annotated[<type>, Depends(<dependency>)]` syntax rather than `: <type> = Depends(<dependency>)`.

**Why?**

- *Default* value of the function parameter is the *actual default* value.
- *Reuse* of the function is now possible.
- *Type-safe* usage of the functions, previously 'default' values where not type checked.
- *Multi-purpose* e.g. `Annotated[str, fastapi.Query(), typer.Argument()]` is now possible.

```bash
pymender FastAPIAnnotated <folder-to-upgrade>
```

| Before | After |
| --- | --- |
| <pre>@router.get('/example')<br/>def example_function(<br/>    value: int,<br/>    query: str = Query("foo"),<br/>    zar: str = Query(default="bar", alias="z"),<br/>    foo: str = Depends(get_foo),<br/>    *,<br/>    bar: str = Depends(get_bar),<br/>    body: str = Body(...),<br/>) -> str:<br/>    return 'example'</pre> | <pre>@router.get('/example')<br/>def example_function(<br/>    value: int,<br/>    foo: Annotated[str, Depends(get_foo)],<br/>    query: Annotated[str, Query()] = "foo",<br/>    zar: Annotated[str, Query(alias="z")] = "bar",<br/>    *,<br/>    bar: Annotated[str, Depends(get_bar)],<br/>    body: Annotated[str, Body()],<br/>) -> str:<br/>    return 'example'</pre> |

## Developer Guide

```bash
# Run a particular codemod
python3 -m pymender <codemod> <path_to_project>
# e.g.
python3 -m pymender FastAPIAnnotated <path_to_project>

# Run the codemod directly
python3 -m libcst.tool codemode fastapi_annotated.FastAPIAnnotated <path_to_project>

# Run tests
pytest -vv

```

## Thanks to:

- [libCST](https://github.com/Instagram/LibCST) which does a lot of the hardwork for this.
- [autotyping](https://github.com/JelleZijlstra/autotyping) for showing what was possible.