semvec/pypi-packages huggingface dataset:
gitlab-personal-issue-board 0.0.3
Manage gitlab issues assigned to yourself locally for all groups and projects
Requires Python: >=3.12

# Gitlab Personal Issue Board

[![PyPI - Version](https://img.shields.io/pypi/v/gitlab-personal-issue-board.svg)](https://pypi.org/project/gitlab-personal-issue-board)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/gitlab-personal-issue-board.svg)](https://pypi.org/project/gitlab-personal-issue-board)

-----

## Table of Contents

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

## Installation

Before using the program, you need to [configure `python-gitlab`](https://python-gitlab.readthedocs.io/en/stable/cli-usage.html#configuration-file-format).

To do this, [create a personal access token](https://docs.gitlab.com/user/profile/personal_access_tokens/#create-a-personal-access-token) with at least *api* permissions and add it to the `~/.python-gitlab.cfg` file like this:

```ini
[global]
default = personal
ssl_verify = true  # alternative path to CA file

[personal]
url = https://gitlab.com
private_token = <your access token>
```

⚠️ Instead of storing your access token in plain text, it is strongly recommended to use a [credential helper](https://python-gitlab.readthedocs.io/en/stable/cli-usage.html#credential-helpers).

It is recommended to use [uv](https://docs.astral.sh/uv/getting-started/installation/) to install and run `gitlab-personal-issue-board`:

```console
uvx gitlab-personal-issue-board
```

## Usage

After launching the application, some debug information is printed. A local web server powered by [NiceGUI](https://nicegui.io/) is started and automatically opened in your browser.

First, click *Add new label board*. This creates a new issue board and opens a configuration page.
While the page is opening, all issues assigned to you are loaded, which may take some time.
This step ensures that all available labels are shown.

All loaded issues are cached. After this initial load, only updated issues are retrieved.

Once the page has loaded, you can drag and drop the desired labels from the right side to the left, between the *Opened* and *Closed* sections.
After selecting the desired labels, click *Save and View* to see your board.

Now you can move issues from one column to another just like in a standard GitLab board.

## License

`gitlab-personal-issue-board` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
teste_lr_eagle_020602025 0.0.0
Implements LangGraph based agents following the CoALA framework.
Requires Python: <3.14,>=3.10

<p align="center">
    <img src="./assets/EAGLE.jpg" alt="EAGLE Logo" />
</p>

# Enhanced Agents for Generative Language Excellence

## Do que se trata este projeto?

Esse projeto implementa a visão do [framework CoALA (Cognitive Architectures for Language Agents)](https://github.com/ysymyth/awesome-language-agents) no contexto do [LangGraph](https://www.langchain.com/langgraph), com agentes, ferramentas e estratégias de integração multiagentes para servirem de exemplo para novas implementações.

## Instalação

### Pré-requisitos (considerando o uso do Conda para gerenciar o ambiente python)

- [Miniforge 3](https://conda-forge.org/download/): O Miniforge é uma distribuição mínima do conda, que é um gerenciador de pacotes e ambientes virtuais. Ele será usado para criar um ambiente virtual para instalar as dependências do projeto.

### Criando o ambiente virtual

1. Uma vez instalado o Conda, abra o terminal e digite o seguinte comando:

```bash
conda create -n eagle python=3.10
```

2. Após a criação do ambiente, ative-o com o comando:

```bash
conda activate eagle
```

3. Instale a versão mais recente do Poetry com o comando:

```bash
pip install poetry==1.8.5
```

1. Instale as dependências do projeto com o comando:

```bash
poetry install
```

## Testes
Para executar os testes, execute os seguintes passos:

1. Ative o ambiente virtual com o comando:

```bash
conda activate eagle
```

2. Copie o arquivo `sample.test.env` para `.test.env` e preencha as variáveis de ambiente com as informações necessárias para o seu amnbiente de testes.

```bash
cp sample.test.env .test.env
```

### Ponto de Atenção

Os testes e exemplos dos notebooks estão baseados nos modelos `AzureChatOpenAI` para os LLMs e `AzureOpenAIEmbeddings` para os embeddings. Caso seja necessário utilizar outros nomes de modelos, tipos ou ajustar as relações com as variáveis de ambiente, essas alterações podem ser feitas na pasta [`tests/models`](tests/models).

## Exemplos de uso das funcionalidades

A pasta `notebooks` contém exemplos de uso das ferramentas. Para executar os exemplos:

1. Ative o ambiente virtual com o comando:

```bash
conda activate eagle
```

2. Ative a extensão de widgets do jupyter com o comando:

```bash
jupyter nbextension enable --py widgetsnbextension
```

3. Ative o jupyter lab com o comando:

```bash
jupyter lab
```

4. Abra o browser e execute os notebooks da pasta `notebooks`.
boreholeio 0.1.0
A library for interacting with borehole.io, a subsurface data management, delivery and visualisation platform.
Requires Python: >=3.8

# boreholeio

A [Python](https://www.python.org/) library for interacting with [borehole.io](https://borehole.io/), a subsurface data management, delivery and visualisation platform developed by [ALT](https://www.alt.lu/).

> [!CAUTION]
> This package is not yet ready for general consumption. If you'd like more information or to get involved in the development, please get in touch.

## Getting Started

Python developers can install the [boreholeio](https://pypi.org/project/boreholeio) package using [pip](https://pip.pypa.io/en/stable/). From the command line, run `pip install boreholeio` to pull the package into your current Python environment.

The package contains an API client and functionality to interact with data using standard scientific data libraries such as [NumPy](https://numpy.org/), [SciPy](https://scipy.org/) and [Matplotlib](https://matplotlib.org/).

```python
import boreholeio as bio
import matplotlib.pyplot as plt
import itertools

client_settings = bio.JsonClientSettings('~/borehole.io_client.json')
client = bio.Client(client_settings)

# Find ABI logging runs close to ALT HQ
logging_runs = client.logging_runs(
    filter={
        "tool": "ABI",
        "channel": "Amplitude-MN,TravelTime"
        "near": "49.75844052,5.894923998"
    },
    sort={
        "by": "started"
        "order": "descending"
    }
)

# Create a plot of the first 10 logs
figure = plt.figure()
subplots = figure.subplots(1, 10, sharex=True, sharey=True)
for subplot, run in zip(subplots, itertools.islice(logging_runs, 10)):
    # Plot the amplitude map
    amplitude = run.channels['Amplitude-MN'].data
    subplot.pcolormesh(
        bio.data.helpers.centers_to_edges(amplitude.axes[1].coordinates),
        bio.data.helpers.centers_to_edges(amplitude.axes[0].coordinates),
        amplitude
    )

    # Set the title of each plot to metadata from the logging run
    borehole = (run.borehole or {}).get("name")
    user = (run.device or {}).get("user")
    started = run.started.date().isoformat()
    subplot.set_title(f"{borehole}\n{user}\n{started}")

    # Set axis labels
    subplot.set_xlabel(f"{amplitude.axes[1].name} ({amplitude.axes[1].units})")
    subplot.set_ylabel(f"{amplitude.axes[0].name} ({amplitude.axes[0].units})")
```
leica-scripts 0.0.3
Leica Scripts
Requires Python: <3.13,>=3.12

# Leica_ROI_finder
Automatic ROI finder for Leica Stellaris 8
- Automatic segmentation using cellpose 3
- ROI filtering using intensity, size and circularity
- Exports ROIs to Leica .rgn files, can be imported into LAS X navigator

![](./assets/images/usage.gif)

## Installation and usage
Leica ROI finder is available on PyPi and can be installed as follows:
```shell
pip install leica-scripts
```

Activate the GUI using:
```shell
python -m leica_scripts
```

# Workflow
Load LIF image into ROI finder:

![](./assets/images/image_loaded.png)

Perform segmentation using cellpose, filter ROIs using intensity, size and circularity:

![](./assets/images/segmentation.png)

Ron Scripts:

![](./assets/images/regions_loaded.png)

Perform imaging on all regions:

![](./assets/images/experiment.png)