semvec/pypi-packages huggingface dataset:
torchist 1.0.1
NumPy-style histograms in PyTorch
Requires Python: >=3.8
Keywords: torch, histogram

# NumPy-style histograms in PyTorch

The `torchist` package implements NumPy's [`histogram`](https://numpy.org/doc/stable/reference/generated/numpy.histogram.html) and [`histogramdd`](https://numpy.org/doc/stable/reference/generated/numpy.histogramdd.html) functions in PyTorch with CUDA support. The package also features implementations of [`ravel_multi_index`](https://numpy.org/doc/stable/reference/generated/numpy.ravel_multi_index.html), [`unravel_index`](https://numpy.org/doc/stable/reference/generated/numpy.unravel_index.html) and some useful functionals like `entropy` or `kl_divergence`.

## Installation

The `torchist` package is available on [PyPI](https://pypi.org/project/torchist), which means it is installable with `pip`.

```
pip install torchist
```

Alternatively, if you need the latest features, you can install it from the repository.

```
pip install git+https://github.com/francois-rozet/torchist
```

## Getting Started

```python
import torch
import torchist

x = torch.rand(100, 3).cuda()

hist = torchist.histogramdd(x, bins=10, low=0.0, upp=1.0)

print(hist.shape)  # (10, 10, 10)
```

## Benchmark

The implementations of `torchist` are on par or faster than those of `numpy` and `torch` on CPU. On GPU (CUDA), they are much faster.

```console
$ torchist-benchmark
CPU
---
np.histogram                      0.8917 s
np.histogram (edges)              0.5993 s
np.histogramdd                   16.8441 s
np.histogramdd (edges)           13.7680 s
torch.histogram                   0.3251 s
torch.histogram (edges)           0.4217 s
torch.histogramdd                 1.0528 s
torch.histogramdd (edges)         1.1955 s
torchist.histogram                0.4250 s
torchist.histogram (edges)        0.6372 s
torchist.histogramdd              1.6266 s
torchist.histogramdd (edges)      3.8619 s

CUDA
----
torchist.histogram                0.1045 s
torchist.histogram (edges)        0.0672 s
torchist.histogramdd              0.0906 s
torchist.histogramdd (edges)      0.1170 s
```
nomad-camels-driver-keithley-197a 0.1.0
Instrument driver for keithley_197a for NOMAD CAMELS
Requires Python: >=3.9.6

# NOMAD Camels driver for keithley_197a

Driver for keithley_197a written for the measurement software [NOMAD Camels](https://fau-lap.github.io/NOMAD-CAMELS/).


## Documentation

For more information and instruments visit the [documentation](https://fau-lap.github.io/NOMAD-CAMELS/doc/instruments/instruments.html).

## Changelog

### 0.1.0

Initial release. Basic reading of DV & AC voltage and  current.
lynxlynx 0.1.1
Personal library for my scripts
Requires Python: >=3.12

# python-lynxlynx

## About

Shared Python library used by my scripts.

## Installation

## Development docs

https://packaging.python.org/en/latest/tutorials/packaging-projects/

### Build

```shell
python -m build
```

### Install dev version

```shell
python -m pip install --user --break-system-packages .
```

### Upload to PyPI

First build the package as per Build.

Then create the config file `~/.pypirc`:
```ini
[pypi]
	username = __token__
	password = pypi-ABCDEFGHTOKEN
```

Then upload the package:
```shell
# Testing PyPI
python -m twine upload --repository testpypi dist/*
# Prod PyPI
python -m twine upload dist/*
```
## License

AGPL-3.0-only, contact me if you need other licensing.
y360-orglib 0.0.13
Unofficial Collection library for Y360 API
Requires Python: >=3.9

## Unofficial library collection for Y360 API

#### Installation

```bash
pip install y360-orglib

```
#### Import
```
import y360_orglib
```

### Available Modules:

- `serviceapp`: ServiceApps module for interacting with the Y360 Service Applications.
- `disk`: Disk Client module for interacting with the Y360 Disk REST API.
- `directory`: Directory API module for interacting with the Y360 Directory API.
- `audit`: Audit Log module for interacting with the Y360 Audit Log API.


### Documentation

https://y360-orglib.readthedocs.io/en/latest/
ecl-logging-utility 1.0.18
Internal structured logging utility for ECL microservices
Requires Python: >=3.8

# Structured Logging Utilities for ECL microservices

![Python Version](https://img.shields.io/badge/python-3.8%2B-blue)
![License](https://img.shields.io/badge/license-Proprietary-lightgrey)

Internal package for consistent structured logging across ECL microservices. Features JSON formatting, automatic metadata capture, and environment-based configuration. Utility will also handle pushing logs to OpenSearch if the OpenSearch related environment variables are set.

## Features

- 📝 **Structured JSON logs** with consistent schema
- 🕒 **Automatic timestamping** in ISO 8601 format
- 📍 **Complete source location** (file path, line number, module, function)
- 🔍 **Query-ready fields** (transaction_id, request_ip, service_name)
- ⚙️ **Environment-controlled** log levels
- 🔗 **Request context propagation** across services
- ☁️ **Push logs to OpenSearch enterprise-grade search and observability suite that brings order to unstructured data at scale.**
- 👖 **Push error and critical logs to Slack**
- 🛡 **Private package** for internal use of ECL

## Environment Variables
- **ECL_LOGGING_UTILITY_LOG_LEVEL**: Set the log level, default: *INFO*
- **ECL_LOGGING_UTILITY_APP_VERSION**: Denotes the app version which will be displayed in the log, default: *AMBIVALENT_APP_VERSION*
- **ECL_LOGGING_UTILITY_SERVICE_NAME**: Denotes the service name which will be displayed in the log, default: *AMBIVALENT_SERVICE_NAME*
- **ECL_LOGGING_UTILITY_OPENSEARCH_ENABLED**: Flag to enable/disable pushing logs to OpenSearch endpoint, default: *False*
- **ECL_LOGGING_UTILITY_OPENSEARCH_HOST**: OpenSearch endpoint's host, default: *localhost*
- **ECL_LOGGING_UTILITY_OPENSEARCH_PORT**: OpenSearch endpoint's port, default: *9200*
- **ECL_LOGGING_UTILITY_OPENSEARCH_USERNAME**: Basic Auth username, default: *None*
- **ECL_LOGGING_UTILITY_OPENSEARCH_PASSWORD**: Basic Auth password, default: *None*
- **ECL_LOGGING_UTILITY_SLACK_WEBHOOK_URL**: Webhook URL of Slack channel to push notification in case of `error` & `critical` logs
- **ECL_LOGGING_UTILITY_INDEX_PATTERN_UUID**: UUID of the OpenSearch index pattern with which the log is discovered. It is used to generate the OpenSearch dashboard link.

## Installation

```bash
pip install ecl-logging-utility
```

## Usage
```python
from ecl_logging_utility import logger
logger.info("You have hit heartbeat", custom_1="1234", custom_2=500.0)
```

## Version History  
See [CHANGELOG.md](CHANGELOG.md) for release notes.