semvec/pypi-packages huggingface dataset:
DROPStomo 0.0.6
Package for performing Wigner state and process tomography on a simulator or on a quantum hardware.
Keywords: python,quantum physics,quantum computing,quantum information processing,quantum tomography,quantum state tomography,quantum process tomography,Wigner tomography


# What is DROPStomo?
DROPStomo is a Python package for performing state and process tomography in the context of finite-dimensional Wigner representations on near-term quantum devices. This is a phase-space tomography approach to recovering the finite-dimensional Wigner type representations of quantum states and processes, with a particular focus on the [DROPS](https://spindrops.org/) (Discrete Representation of OPeratorS) representation. The package is based on the paper: [Wigner State and Process Tomography on Near-Term Quantum Devices](https://arxiv.org/abs/2302.12725).

This package is based on the Qiskit framework and can be easily adapted for other frameworks. The package can be plugged directly into quantum simulators or quantum devices.  

## Installation
```bash
pip install DROPStomo
```
## How to use
Currently, Wigner state tomography is available for single and two qubit systems, whereas Wigner process tomography is available for single qubit systems. For detailed examples on how to use Wigner tomography, please check out the Examples folder in our [Git repository](https://github.com/amitQC/DROPStomo).  

## Citation
If you use the DROPS tomography tool in your work, cite it as follows:
```bash
@misc{https://doi.org/10.48550/arxiv.2302.12725,
  doi = {10.48550/ARXIV.2302.12725},
  url = {https://arxiv.org/abs/2302.12725},
  author = {Devra, Amit and Glaser, Niklas J. and Huber, Dennis and Glaser, Steffen J.},
  keywords = {Quantum Physics (quant-ph), FOS: Physical sciences, FOS: Physical sciences},
  title = {Wigner State and Process Tomography on Near-Term Quantum Devices},
  publisher = {arXiv},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International}
}
```
cqi 0.1.7
A Python library for the IMS Open Corpus Workbench (CWB) corpus query interface (CQi) API.
Requires Python: >=3.5

# CQi SDK for Python

A Python library for the [IMS Open Corpus Workbench](http://cwb.sourceforge.net/) (CWB) [Corpus Query Interface](https://cwb.sourceforge.io/documentation.php#cqi) (CQi) API.

## Installation

The latest stable version [is available on PyPI](https://pypi.python.org/pypi/cqi/). Either add `cqi` to your `requirements.txt` file or install with pip:

```
pip install cqi
```

## Version compatibility

| Package version | Protocol version |
|-----------------|------------------|
| 0.1.0 - 0.1.7   | 0.1              |

## Usage

```python
import cqi


client = cqi.CQiClient('127.0.0.1')
client.connect(username='anonymous', password='') # <class 'cqi.status.StatusConnectOk'>
client.ping() # <class 'cqi.status.StatusPingOk'>
corpus = client.corpora.get('CORPUS') # <Corpus: CORPUS>
corpus.query('"and" []* "the";', 'Results') # <class 'cqi.status.StatusOk'>
results = corpus.subcorpora.get('Results') # <Subcorpus: CORPUS:Results>
client.disconnect() # <class 'cqi.status.StatusByeOk'>
```
pyhip-interface 0.1.2
Python Interface to HIP and hiprtc Library
Keywords: HIP GPU parallel computing scientific computing Python wrapper

# PyHIP - Python Interface of [HIP](https://github.com/ROCm-Developer-Tools/HIP) and [hip-on-nv](https://github.com/jatinx/hip-on-nv)

## Introduction

This small python lib which hooks into HIP library and provides pythonic interface to it.

There are two parts of it, hip library and hiprtc library.

This also works with [hip-on-nv](https://github.com/jatinx/hip-on-nv).

## Installation

### Prerequisites

Before installing pyhip-interface, please make sure you have the following prerequisites installed:

* The Heterogeneous Interface for Portability - [HIP Installation Guide](https://docs.amd.com/bundle/HIP-Installation-Guide-v5.3/page/Introduction_to_HIP_Installation_Guide.html)

### Install with pip

PyHIP can be installed using pip, a package manager for Python. Run the following command in your terminal to install:

`pip install pyhip-interface`

### Install from source

Alternatively, you can install PyHIP from the source code. First, clone the repository from GitHub:

`git clone https://github.com/jatinx/PyHIP`

Then, navigate to the repository directory and run the following command to install:

`python setup.py install`

## Example Usage

```python
import ctypes
from pyhip import hip, hiprtc
source = """
extern "C" __global__ void set(int *a) {
  *a = 10;
}
"""
prog = hiprtc.hiprtcCreateProgram(source, 'set', [], [])
device_properties = hip.hipGetDeviceProperties(0)
print(f"Compiling kernel for {device_properties.gcnArchName}")
if hip.hipGetPlatformName() == 'amd': # offload arch is amd only
  hiprtc.hiprtcCompileProgram(prog, [f'--offload-arch={device_properties.gcnArchName}'])
else:
  hiprtc.hiprtcCompileProgram(prog, [])
code = hiprtc.hiprtcGetCode(prog)
module = hip.hipModuleLoadData(code)
kernel = hip.hipModuleGetFunction(module, 'set')
ptr = hip.hipMalloc(4)

class PackageStruct(ctypes.Structure):
  _fields_ = [("a", ctypes.c_void_p)]

struct = PackageStruct(ptr)
hip.hipModuleLaunchKernel(kernel, 1, 1, 1, 1, 1, 1, 0, 0, struct)
res = ctypes.c_int(0)
hip.hipMemcpy_dtoh(ctypes.byref(res), ptr, 4)
print(res.value)
```

## Testing

Testing is in it's infancy. I'll try to add more as and when I get some time. Any help here is appreciated :)

### How to run tests

Make sure you have ```pytest``` package installed.

From the project folder run ```pytest ./tests/* -v -r A```

## Help needed

If you are an opensource developer and want to contribute to this project, I can use your help in several places depending on your skillset.

- Adding more tests to the project
- Adding API documentation and samples
- Improving HIP API coverage - adding meaningful APIs instead of direct mapping.

## Common Problems

- Unable to load hip or hiprtc library - OSError: libamdhip64.so: cannot open shared object file: No such file or directory.

  - Make sure that LD_LIBRARY_PATH has hip path on it (/opt/rocm/lib or a custom installation path)

- Getting error and need to debug

  - Set AMD_LOG_LEVEL=7 for maximum verbosity of HIP APIs (this only works on amd platform).
pimo-sharing-info 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
peng-env-report 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
orero-api 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
normanlib 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
nabeva 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mupeingabe 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mupauto 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mobistation 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mobi-connect 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mlflow-token-plugin 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mlflow-plugin 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
mia-template-py 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
matsimba 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
loclab-lib 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
lizenzwechsler 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
lib-gis-helpers 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
flowbundles 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
fault-matcher 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
esta-tekton-python-sample 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.
esta-python-tekton-sample 0.0.1rc1
Dummy package to prevent any kind of dependency confusion attacks against internal python packages
Requires Python: >=3.6,<4.0

This is a dummy package intended to prevent any dependency confusion attacks against our internal Python packages at [SBB](https://www.sbb.ch/). For now this is the only foolproof way to prevent some dependency confusion attacks until the following PEP has been implemented: [PEP-708](https://peps.python.org/pep-0708/)

For any questions regarding this package feel free to reach out to <application-security@sbb.ch>.