semvec/pypi-packages huggingface dataset:
pinkrst 0.0.1.post2
Opinionated ReStructured Text (.rst) Formatter
Requires Python: >=3.6

# Pink RST 🩷
![GitHub Release](https://img.shields.io/github/v/release/biosafetylvl5/pinkrst)
![PyPI - Version](https://img.shields.io/pypi/v/pinkrst)
![Pepy Total Downloads](https://img.shields.io/pepy/dt/pinkrst)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pinkrst)


Opinionated ReStructured Text (.rst) Formatter inspired by [Black](https://github.com/psf/black). 

Remember: [RST Files wear pink EVERY day of the week.](https://www.youtube.com/watch?v=xBbOAVSBvpE)

Works well with [doc8](https://github.com/PyCQA/doc8)

There's only one [file](pinkrst/pinkrst.py), so read it if you want the docs.

## Install

``` bash
pip3 install pinkrst
```

or

``` bash
pip install pinkrst
```

## Usage

``` bash
pink file.rst # to process individual file
```

``` bash
pink --max-line-length 100 file.rst # set max line length
```

``` bash
pink # to process files in dir and recursively processes sub-folder files
```

``` bash
pink --no-recurse # to process files in dir WITHOUT recusion
```

``` bash
# to process files recursively in dir WITHOUT ensuring there's a trailing newline at the end of files
pink --disable-trailing-newline 
```

``` bash
 # or go crazy, see next section
pink --no-recurse --disable-replace-tabs --spaces-per-tab 4 --disable-smart-wrap --max-line-length 100 directory/
```

### CLI Arguments

| Argument                          | Description                                                               |
|-----------------------------------|---------------------------------------------------------------------------|
| `-h, --help`                      | Show help message and exit.                                               |
| `-rx, --no-recurse`               | Turns off recursively parsing subdirectories. Recursion is enabled by default. |
| `--disable-no-trailing-whitespace`| Disables the removal of trailing whitespace on each line                  |
| `--disable-replace-tabs`          | Disables replacing tabs with spaces                                        |
| `--spaces-per-tab SPACESPERTAB`   | Specifies the number of spaces to replace each tab with. Default is 4 spaces. |
| `--disable-trim-excess-empty-lines` | Disables trimming excess empty lines from files.                        |
| `--disable-trailing-newline`      | Disable ensuring that files end with a newline character.                 |
| `--disable-smart-wrap`            | Disable intelligently wraping long lines that exceed a specified width.   |
| `--max-line-length LINELENGTH`    | Sets the maximum line length after which wrapping should occur. Default is 120 characters. |
qcir-sim 0.1.0
Quantum circuit simulation
Requires Python: >=3.12

# qcir_sim

Quantum circuit simulation using Vector and Tensor simulations

**Note:** Examples for using are provided in the `examples/` folder. Examples include:

1. Benchmarking how many qubits can we simulate using Vector and Tensor simulation
2. Sampling the Qubits from a Quantum simulation
3. Calculating the expectation values of `<Ψ| Op |Ψ>`

## Setting up

### Using uv ([Installation](https://docs.astral.sh/uv/getting-started/installation/))

1. Create a virtual environment

```sh
uv venv .venv
```

2. Activate the virtual environment

```sh
source .venv/bin/activate
```

3. Install the dependencies

```sh
uv sync
uv pip install pandas # required in benchmark.py
```

### Legacy virtual environments

1. Create virtual environment

```sh
python3 -m venv .venv
```

2. Activate the virtual environment

```sh
source .venv/bin/activate
```

3. Install dependencies

```sh
pip install -e . # -e to develop while using
```
SortedCounterCPP 0.1.0
Sorted version of collections.Counter, implemented in C++
Requires Python: <3.14,>=3.9

# SortedCounterCPP

## What's this?

A Python package that's like the built-in [`collections.Counter`](https://docs.python.org/3/library/collections.html#collections.Counter), but sorted.
Access to min/max elements is guaranteed to have $O(\log n)$ time complexity.

## Compatibility

CPython only for now.

The API currently supports only elements of C++ type `double` (equivalent to Python's `float`).

## License

See [LICENSE](./LICENSE).
SLHPDataWarehousing 0.3.0
This package is used by the SLHP Data Warehousing Team for their day to day work
Requires Python: >=3.9

# SLHP Data Warehousing

## database_connector
This module contains the connectors neccessary to connecto to either databricks or Sql Server. 

## environment_setup
This module contains a function which will setup a sample folder structure and files of how a flask application should interact.
puremote 0.1.2
Add your description here
Requires Python: >=3.12

# Puremote

puremote is a remote experiment status monitoring software designed based on RESTFUL API. It was originally designed to provide remote monitoring for the Incage project of PsychoUnity, but due to the use of web technology, it can now be used for various experimental design frameworks, such as: PyshoToolBox, PsychoPy or MonkeyLogic, etc.

## install

### install with uv

```bash
# clone this repo
git clone https://github.com/Ccccraz/puremote.git

cd puremote
```

```bash
# setup env
uv sync

# run app
uv run main
```

### install with conda
```bash
# clone this repo
git clone https://github.com/Ccccraz/puremote.git

cd puremote
```

```bash
# setup env
conda create -n puremote python=3.12
conda activate puremote

# install dependency
pip install .

# run app
python ./src/puremote/__init__.py
```

# Contribution
> *This project is built with PySide6, but it is planned to be refactored with Tauri in the future*
tlverifier 0.0.28
Tool for transparent logs
Requires Python: >=3.7

# tlverifier

### documentation
https://tlverifier.readthedocs.io/en/latest/

#### installation: 
pip install --extra-index-url https://test.pypi.org/simple/ tlverifier

#### installation of specific version:
pip install --extra-index-url https://test.pypi.org/simple/ tlverifier==x.y.z

#
#

## Environment:
#### dev: python==3.9
#### required: python>=3.7
#### libs required: pymerkle-logsTransparentes~=0.0.3 [https://pypi.org/project/pymerkle-logsTransparentes/]

#
#

### Functions:
- verify_inclusion_proof
- verify_consistency_proof
- verify_data_entry
- verify_local_tree_history_consistency
- verify_global_tree_history_consistency

#

### Functions details:

###### verify_inclusion_proof(proof, root, data, expected_index=None)
- proof: dictionary
- root: string
- data: bytes
- return: dictionary
  - {"success": True}
  - {"success": False, "exception": InvalidProof}
  - {"success": False, "exception": InvalidChallenge} 
  - {"success": False, "exception": Other}

###### verify_consistency_proof(first_root, second_root, proof)
- first_root: bytes
- second_root: bytes
- proof: MerkleProof (pymerkle_logsTransparentes.proof.MerkleProof)
- return: dictionary
  - {"success": True}
  - {"success": False, "exception": InvalidProof}
  - {"success": False, "exception": InvalidChallenge} 
  - {"success": False, "exception": Other}

###### verify_data_entry(proof, global_root, data)
- proof: dictionary
- global_root: string
- data: bytes
- return: dictionary
  - {"success": True}
  - {"success": False, "exception": inclusion_proof_local}
  - {"success": False, "exception": inclusion_proof_global}

###### verify_local_tree_history_consistency(global_tree_data, consistency_proofs, trusted_global_root, tree_name)
- global_tree_data: dictionary
- consistency_proofs: dictionary
- trusted_global_root: string
- tree_name: string
- return: dictionary
  - {"success": True}
  - {"success": False, "exception": "Global roots don't match"}
  - {"success": False, "exception": "Global tree data and Consistency proofs do not match"}
  - {"success": False, "exception": "Consistency proof is false"}

###### verify_global_tree_history_consistency(consistency_proofs, stored_global_roots=None)
- consistency_proofs: dictionary
- trusted_global_root: dictionary
- return: dictionary
  - {"success": True}
  - {"success": False, "exception": "Consistency proof is false"}

#
#

### Testing with testers.py and data_access.py
#### - testers.py 
##### has 5 functions, each one gets data from "data_access.py" and calls only one function of tl_functions
#### - data_access.py
##### gets mocked data, you can change data here to create to test for failure, or to add your own mocked data
gtap-extractor 0.1.1
Extract GTAP data from .har files and save it as .nc file.
Keywords: GTAP, MRIO, Input-Output, Economics, Industrial Ecology, netcdf, International Trade

# gtap_extractor

GTAP is a licensed database for international economics.
It is widely used for calibrating Computable General Equilibrium (CGE).
GTAP is distributed as unusual .har files, usable with the proprietary GTAPAgg software.
This package aims at simplifying the access to GTAP data, by transferring GTAP data into the standard netCDF data format.

---

## Installation

You can install the package by typing `pip install gtap-extractor`

## Usage

The *extract_gtap()* method takes three optional arguments:

**source** *(path-like)*
   : Path to the raw GTAP .har files.
   : You will find these files in your GTAP installation.
   : By default, the current working directory.

**name** *str*
    : Name under which the resulting .nc file is stored


**destination** *(path-like)*
   : Path where the netCDF file will be saved.
   : By default, the current working directory.

**files** *(list of str)*
   : List of GTAP files to be extracted.
   : By default, all GTAP files are extracted.

**build_mrio** *(bool)*
    : If True, GTAP data are converted into a simple MRIO table, in basic prices.


>The built table is saved under <name>_mrio.nc.
>
>The table consists in three parts:
> - The inter-industry matrix t, built from the VDFB and VMFB variables.
> - The final demand matrix y, built from VMPB, VDPB, VMGB, VDGB, VMIB, VDIB.
> - The value added matrix va, built from EVFB and VTWR.
>
>The construction of t and y relies on the import proportionality assumption: trade shares for each imported good are kept constant across imported sectors.
>
>As imports (VMSB) and exports (VXSB) diverge, trade shares are computed as the arithmetic average of both.
>
>These trade shares are used to ventilate intermediate and final imports.
>
> The value added array includes:
> - Primary endownments (EVFB)
> - The sum of margins and export tariffs (VTWR + XTRV)
> - Net output taxes and subsidies, estimated as the residual value to balance the table.
    


---

## Dependencies 

The package builds on the [HARPY](https://github.com/GEMPACKsoftware/HARPY), [xarray](https://xarray.pydata.org/en/v2024.07.0/index.html), [netcdf4](http://unidata.github.io/netcdf4-python/) and [MRIO_toolbox](https://gitlab.pik-potsdam.de/beaufils/mrio-toolbox) libraries.

Note that the HARPY version on pip is outdated.
Instead, you can clone the HARPY repository directly using the following command in your terminal:

git clone https://github.com/GEMPACKsoftware/HARPY