semvec/pypi-packages huggingface dataset:
qNetTI 0.1.0
Quantum Network Topology Inferrer
Requires Python: >=3.8

# qNetTI: Quantum Network Topology Inferrer

*Python tools and demos for inferring quantum network topology.*

[![Latest](https://img.shields.io/badge/docs-latest-blue.svg)](https://chitambarlab.github.io/qNetTI/index.html)[![Tests](https://github.com/ChitambarLab/qNetTI/actions/workflows/run_tests.yml/badge.svg?branch=main)](https://github.com/ChitambarLab/qNetTI/actions/workflows/run_tests.yml)[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)[![DOI](https://zenodo.org/badge/581250970.svg)](https://zenodo.org/badge/latestdoi/581250970)

See our preprint titled "Inferring Quantum Network Topology using Local Measurements" for details [https://arxiv.org/abs/2212.07987](https://arxiv.org/abs/2212.07987).

Please review the [documentation](https://chitambarlab.github.io/qNetTI/index.html) for details regarding this project.  


### Project Structure

* `./src/qnetti` - Application code.
* `./test` - Unit tests for application code.
* `./script` - Scripts for numerical experiments, data collection, and plotting.
* `./data` - Stored data from numerical experiments.
* `./demos` - User oriented notebooks demoing the application of our code. 
* `./docs` - Source code for generating the static documentation pages.
spark-dql-mvp-tools 0.9.8
spark_dql_mvp_tools
Keywords: spark,dql,rules,hammurabies,haas,mvp

# spark_dql_mvp_tools

[![Github License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Updates](https://pyup.io/repos/github/woctezuma/google-colab-transfer/shield.svg)](pyup)
[![Python 3](https://pyup.io/repos/github/woctezuma/google-colab-transfer/python-3-shield.svg)](pyup)
[![Code coverage](https://codecov.io/gh/woctezuma/google-colab-transfer/branch/master/graph/badge.svg)](codecov)

spark_dql_mvp_tools is a Python library that implements quality rules in sandbox

## Installation

The code is packaged for PyPI, so that the installation consists in running:

## Usage

wrapper create hammurabies MVP

## Sandbox

## Installation

```sh
!yes| pip uninstall spark-dql-mvp-tools
```

```sh
pip install spark-dql-mvptools --user --upgrade
```

## IMPORTS

```sh
import os
import pyspark
from pyspark.sql import functions as func
from spark_generated_rules_tools import dq_path_workspace
from spark_generated_rules_tools import dq_generated_mvp
import spark_dataframe_tools 

```

## Variables

```sh
user_sandbox="P030772"
```

## Creating Workspace

```sh
dq_path_workspace(user_sandbox=user_sandbox)
```

## Run

```sh
table_raw_name = 't_klau_moe_adj_id_mthly_info'
table_master_name = 't_pmfi_moe_adj_id_mthly_info'
periodicity = 'Daily'
target_staging_path = '/in/staging/datax/klau/my_file_{?YEAR_MONTH}.csv'
is_uuaa_tag = False

dq_generated_mvp(table_master_name=table_master_name,
                 table_raw_name=table_raw_name,
                 periodicity=periodicity,
                 target_staging_path=target_staging_path,
                 is_uuaa_tag=is_uuaa_tag)
               
```

## License

[Apache License 2.0](https://www.dropbox.com/s/8t6xtgk06o3ij61/LICENSE?dl=0).

## New features v1.0

## BugFix

- choco install visualcpp-build-tools

## Reference

- Jonathan Quiza [github](https://github.com/jonaqp).
- Jonathan Quiza [RumiMLSpark](http://rumi-ml.herokuapp.com/).