semvec/pypi-packages huggingface dataset:
checklog-odoo 1.0
Check if an odoo log file contains error, with the possibility to ignore some errors based on regular expressions
Requires Python: >=3.7

# checklog-odoo

[![PyPI - Version](https://img.shields.io/pypi/v/checklog-odoo.svg)](https://pypi.org/project/checklog-odoo)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/checklog-odoo.svg)](https://pypi.org/project/checklog-odoo)

-----

<!--- shortdesc-begin -->

Check if an odoo log file contains error, with the possibility to ignore some errors based on regular expressions.

This project replaces the [acsoo](https://pypi.org/project/acsoo)'s checklog command.

<!--- shortdesc-end -->

**Table of Contents**

- [Installation](#installation)
- [Usage](#usage)
- [License](#license)

## Installation

```console
pipx install checklog-odoo
```

## Use examples

```console
checklog-odoo odoo.log
unbuffer odoo -d mydb -i base --stop-after-init | checklog-odoo
checklog-odoo --ignore "WARNING.*blah" odoo.log
```

## Usage

```console
Usage: checklog-odoo [OPTIONS] [FILENAME]

  Check an odoo log file for errors. When no filename or - is provided, read
  from stdin.

Options:
  -i, --ignore REGEX              Regular expression of log records to ignore.
  --echo / --no-echo              Echo the input file (default when reading
                                  from stdin).
  --err-if-empty / --no-err-if-empty
                                  Exit with an error code if no log record is
                                  found (default).
  -v, --verbose
  -c, --config FILE               Configuration file  [default: checklog-odoo.cfg]
  --help                          Show this message and exit.
```

## Example of config file:

The configuration file use the `ini` format:

```ini
[checklog-odoo]
ignore=
   WARNING
   ERROR:.*registry
```

## License

`checklog-odoo` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
catdns 2.0
Create tempmail based on https://catdns.in :D
Requires Python: >=3.6

# Install :
```commandline
pip install -U catdns
```

# How to use :
- 1 - Send email to your custom email, for example: ``test1@catdns.in``
- 2 - Get inbox:

```python
from catdns import get_inbox

inbox = get_inbox("test1@catdns.in")

print(inbox)
```
autodistill-grounding-dino 0.1.4
GroundingDINO module for use with Autodistill
Requires Python: >=3.7

<div align="center">
  <p>
    <a align="center" href="" target="_blank">
      <img
        width="850"
        src="https://media.roboflow.com/open-source/autodistill/autodistill-banner.png?3"
      >
    </a>
  </p>
</div>

# Autodistill Grounding DINO Module

This repository contains the code supporting the Grounding DINO base model for use with [Autodistill](https://github.com/autodistill/autodistill).

[Grounding DINO](https://github.com/IDEA-Research/GroundingDINO) is a zero-shot object detection model developed by IDEA Research. You can distill knowledge from Grounding DINO into a smaller model using Autodistill.

Read the [Grounding DINO Autodistill documentation](https://autodistill.github.io/autodistill/base_models/grounding-dino/).

> [!TIP]
> You can use Autodistill Grounding DINO on your own hardware, or use the [Roboflow hosted version of Autodistill](https://blog.roboflow.com/launch-auto-label/) to label images in the cloud.

## Installation

To use the Grounding DINO base model, you will need to install the following dependency:

```bash
pip3 install autodistill-grounding-dino
```

## Quickstart

```python
from autodistill_grounding_dino import GroundingDINO
from autodistill_yolov8 import YOLOv8


# define an ontology to map class names to our GroundingDINO prompt
# the ontology dictionary has the format {caption: class}
# where caption is the prompt sent to the base model, and class is the label that will
# be saved for that caption in the generated annotations
# then, load the model
base_model = GroundingDINO(ontology=CaptionOntology({"shipping container": "container"}))

# label all images in a folder called `context_images`
base_model.label("./context_images", extension=".jpeg")
```

## License

The code in this repository is licensed under an [Apache 2.0 license](LICENSE).

## 🏆 Contributing

We love your input! Please see the core Autodistill [contributing guide](https://github.com/autodistill/autodistill/blob/main/CONTRIBUTING.md) to get started. Thank you 🙏 to all our contributors!
voice-toolbox 1.0.0
Convenient wrappers for audio signal processing in Python
Requires Python: >=3.5
Keywords: audio, audio analysis

# Voice Toolbox <img align="left" width="90" height="90" src="soundwave.jpeg">
The place to solve all your audio signal processing needs. 

The current repo is under **construction**. Goal is to create a repository that contains all voice signal processing functions available from different open source projects and libraries, such as parsel mouth and librosa. 

## Files
**To start**: Setup a conda environment and run 'pip3 install -r requirements.txt' before running the available scripts. 
>> **Important**: if you get an error with parselmouth make sure the installation is 'pip3 install praat-parselmouth'

________________________________________________________________________________________________________________________
The script for extracting features is parsel_process.py. 
 * **To run**: "python3 feature_extraction.py [sampling rate] [filepath] [output filepath] --[feature flag]"
 
 > **feature flags**: formants, ZCR, harmonics, rate_of_speech, loudness, pitch_features, spectral_features, energy

### **Features currently availabe**:
1. *Spectral Features*:
* pitch
* pitch range
* spectral slope
* mel-frequency cepstral coefficients (MFCC)
* mean spectral roll-off
* median F0 (fundamental frequency)

2. *Rate of Speech* and *loudness*:
* max intensity
* mean intensity
* syllables per second
* pause rate
* energy

3. *Harmonics*
* harmonics to noise (HNR)
* Formants: f1,f2, f3, f4
* number of zero crossings (ZCR)

### Extra Scripts for processed features
For visualization:
 1. visualize_voice.py for all scatter plots along with other plotting features from praat. 
 * To run: 'python3 visualize_voice.py'
 2. radar_plot.py for all radar plots
 * To run: 'python3 radar_plot.py'

For PCA analysis of voice data:
 voice_pca.py is for PCA, RFE and Correlation plot:
* - To run: 'voice_pca.py'

________________________________________________________________________________________________________________________
clinica-pydra-ants 0.1.1
Pydra tasks for ANTs designed for Clinica
Requires Python: >=3.8
Keywords: ants, neuroimaging, pydra, registration

# clinica-pydra-ants

[![PyPI - Version][pypi-version]][pypi-project]
[![PyPI - Python Version][pypi-pyversions]][pypi-project]
![][status-test]

-----

Pydra tasks for ANTs designed for Clinica

[Pydra][pydra] is a dataflow engine which provides
a set of lightweight abstractions for DAG
construction, manipulation, and distributed execution.

[ANTs][ants] is a toolbox for multi-variate image registration,
segmentation and statistical analysis.

[Clinica][clinica] is a software platform for clinical neuroimaging studies.

**Table of Contents**

- [Available Tasks](#available-tasks)
- [Installation](#installation)
- [Development](#development)
- [License](#license)

## Available Tasks

- ApplyTransforms
- CreateJacobianDeterminantImage
- N4BiasFieldCorrection
- Registration, registration_syn, registration_syn_quick

## Installation

```console
pip install clinica-pydra-ants
```

A separate installation of ANTs is required to use this package.

An official conda package is available through conda-forge:

```console
conda install -c conda-forge ants
```

## Development

This project is managed with [Hatch][hatch]:

```console
pipx install hatch
```

To run the test suite:

```console
hatch run test
```

To fix linting issues:

```console
hatch fmt
```

## License

This project is distributed under the terms of the [Apache License, Version 2.0][license].

[ants]: https://github.com/ANTsX/ANTs

[hatch]: https://hatch.pypa.io/

[license]: https://spdx.org/licenses/Apache-2.0.html

[pydra]: https://pydra.readthedocs.io/

[pypi-project]: https://pypi.org/project/clinica-pydra-ants

[pypi-pyversions]: https://img.shields.io/pypi/pyversions/clinica-pydra-ants.svg

[pypi-version]: https://img.shields.io/pypi/v/clinica-pydra-ants.svg

[status-test]: https://github.com/aramis-lab/clinica-pydra-ants/actions/workflows/test.yaml/badge.svg

[clinica]: https://www.clinica.run/