semvec/pypi-packages huggingface dataset:
cpputils 1.4.2
CPP-Utils Python Package for string and file operations
Requires Python: >=3.8

CPP-Utils Python Package
===========
[![cpputils](https://gitlab.blubblub.tech/sgeist/cpputils/badges/main/pipeline.svg)](https://gitlab.blubblub.tech/sgeist/cpputils.git)

## Information

This package was created by starting C ++ methods to incorporate into my python implementations.

To make things easier for me, lightweight public libraries were included (especially to carry out string operations):
- hash-library
- strtk

The following methods have currently been implemented:
- ini_load (flexible and ligthweigh ini to dict parser, Faster Than Configparser)
- eval_type (method to parse strings in python-types e.g. int | bool | timestamp
- simple_hmac (vectorized c++ hmac implementation)
- default_ca_path (python function to find a default ssl / ca certificate path)

In the future the following will be implemented:
- more hash methods
- c++ optimized grep methods
- c++ optimized url-tools methods

Currently, the package was only tested for Linux
## Usage

```python
from cpputils import ini_load, default_ca_path, eval_type

ini_load(files={"s3_configs": ["examples/config/aws_config",
                               "examples/config/aws_credentials",
                               "examples/config/.s3cfg"]},
         sections=["default", "qa"],
         keys={"signurl_use_https": ["signurl_use_https"],
               "aws_access_key_id": ["access_key"],
               "aws_secret_access_key": ["secret_key"],
               "endpoint_url": ["endpoint-url", "host_base"],
               "region_name": ["bucket_location", "region", "aws_default_region"],
               "service_name": ["service_name"],
               "verify": ["ca_certs", "aws_ca_bundle", "ca_bundle"],},
         defaults={
             "region_name": "us-east-1",
             "signurl_use_https": True,
             "verify": default_ca_path(),
             "service_name": "s3",
         })



```


## Installation
```bash
pip install cpputils
```

## Development

### Prerequisites

* A compiler with C++17 support
* Pip 10+ or CMake >= 3.4 (or 3.8+ on Windows, which was the first version to support VS 2015)
* Ninja or Pip 3.8+

### Installation

Just clone this repository and pip install. Note the `--recursive` option which is
needed for the pybind11 submodule:

```bash
git clone --recursive https://gitlab.blubblub.tech/sgeist/cpputils.git
pip install .
```

### Publish
```bash
twine upload -r pypi $(ls dist/cpputils-1.0.0-*.whl) --verbose
```
bench-physst 0.0.1
For generating benchmarks
Requires Python: >=3.6

Only works on PHYS cluster 
Only tests up to 4 nodes
Need the topology file in the directory where you execute the script
Benchmark results will be printed under filename **Benchmark_Perfomance.png** in the same directory where script was executed
Check progress by executing squeue -n bingo in terminal (when no jobs are running, results should be available)



NEED TO LOAD ANACONDA/3/2020.2 ON PHYS CLUSTER PRIOR TO USING LIB

If you download all the code on personal comp (best method)
Execute the following:	
module load anaconda/3/2020.02 
python3
from bench_physs import num_nodes
num_nodes("# of nodes you want to test -- 4 nodes max)
exit()
condansis 0.4
Create installers for Python packages using NSIS and Conda
Requires Python: >=3.8, <4
Keywords: packaging,installer,windows

CondaNSIS
==========

[![Test and Release](https://github.com/guilhermebs/CondaNSIS/actions/workflows/main.yml/badge.svg)](https://github.com/guilhermebs/CondaNSIS/actions/workflows/main.yml) [![Conda Recipe](https://img.shields.io/badge/recipe-condansis-green.svg)](https://anaconda.org/conda-forge/condansis) [![](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/) 

[CondaNSIS](https://guilhermebs.github.io/CondaNSIS/) packages Python applications into self-extracting installers for **Windows** by leveraging both [conda-pack](https://conda.github.io/conda-pack/) and [NSIS](https://nsis.sourceforge.io/Main_Page).

This project is inspired by [PyNSIST](https://pynsist.readthedocs.io/en/latest/).

Why?
----
Bundlers such as [PyInstaller](https://www.pyinstaller.org/) are great for small apps, but often have problems packaging complex projects with many dependencies.
Alternativelly, deployment with [Conda](https://docs.conda.io/en/latest/) can be difficult as as it requires an Anaconda or a Miniconda installation.

CondaNSIS solves this problem by packaging your Python app together with a **local** and **isolated** Python environment, such that the target computer does not need neither Python nor a Conda already installed.

Installation
------------
CondaNSIS is avaliable through conda-forge

```
conda install -c conda-forge condansis
```

Usage
------
Please see the [documentation page](http://guilhermebs.github.io/CondaNSIS). Due to limitations of the NSIS dependency, **CondaNSIS does not run from Powershell**.

Developers
-----------
Guilherme Bicalho Saturnino (guisa@orsted.com)
bench-physs 0.0.1
For generating benchmarks
Requires Python: >=3.6

Only works on PHYS cluster 
Only tests up to 4 nodes
Need the topology file in the directory where you execute the script
Benchmark results will be printed under filename **Benchmark_Perfomance.png** in the same directory where script was executed
Check progress by executing squeue -n bingo in terminal (when no jobs are running, results should be available)



NEED TO LOAD ANACONDA/3/2020.2 ON PHYS CLUSTER PRIOR TO USING LIB

If you download all the code on personal comp (best method)
Execute the following:	
module load anaconda/3/2020.02 
python3
from bench_physs import num_nodes
num_nodes("# of nodes you want to test -- 4 nodes max)
exit()
G31-thermometry 1.0.1
A Python package useful to convert thermometer voltage to temperature
Requires Python: >=3.10.5

# G31_thermometry
A Python package useful to convert thermometer readout voltage to temperature for the G31 Cosmology Group at La Sapienza University of Rome.

# Supported thermometers
- Lakeshore DT670 D6068043

# How to add new thermometers
For now it is possible to add only Lakeshore thermometer calibration files, just go to [Lakeshore website](https://www.lakeshore.com/products/categories/temperature-products/cryogenic-temperature-sensors), insert the serial number of a thermometer and download the zip file. Extract the zip file and copy/paste the extracted directory as a subfolder of thermometer model directory.

# How to install
From ipython:
```Python
pip install G31-thermometry
```

# Example
In this example we define a DT670 thermometer with serial number D6068043 and plot its calibration curve.
```Python
import G31_thermometry as G31t

DT670 = G31t.Thermometer(model='DT670', serial_no='D6068043')
DT670.plotCalibrationCurve()
```
The calibration curve is shown below.
<br/>
<img src="https://github.com/federico-cacciotti/G31_thermometry/blob/main/DT670_D6068043.png" alt="DT670_D6068043_calibration_curve" width="500"/>

With the following code instead we want to convert measured voltages into temperatures.
```Python
import G31_thermometry as G31t
import numpy as np

DT670 = G31t.Thermometer(model='DT670', serial_no='D6068043')

voltage = np.array([0.5  , 0.625, 0.75 , 0.875, 1.   ])
DT670.temperature()
```
Output (in kelvin):
```
np.array([324.73716731, 270.61138912, 214.82655846, 156.39544034,
        92.6566496 ])
```

## Updates
- 22/07/2022: added DT670 - D6068043