semvec/pypi-packages huggingface dataset:
make-aggrid 0.1.8
Configura automaticamente o AgGrid no Streamlit com base em um DataFrame
License: MIT
Requires Python: <4.0,>=3.10
Keywords: streamlit, aggrid, pandas, dataframe

# make-aggrid

[![PyPI version](https://img.shields.io/pypi/v/make-aggrid.svg)](https://pypi.org/project/make-aggrid/)
[![Python versions](https://img.shields.io/pypi/pyversions/make-aggrid.svg)](https://pypi.org/project/make-aggrid/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![GitHub Repo stars](https://img.shields.io/github/stars/edwdev-oficial/make-aggrid?style=social)](https://github.com/edwdev-oficial/make-aggrid)


`make-aggrid` é uma biblioteca Python que facilita a configuração avançada do componente AgGrid para uso com Streamlit. Basta passar um DataFrame e ela automaticamente aplica filtros, formatações e estilos adequados com base nos tipos de dados.

## 📦 Instalação

### Com pip

```bash
pip install make-aggrid streamlit-aggrid==1.1.2
```

### com poetry
```bash
poetry add make-aggrid streamlit-aggrid@1.1.2
```

⚠️ O `make-aggrid` requer Python 3.10 ou superior (mas abaixo de 4.0) devido à dependência do `streamlit-aggrid` versão 1.1.2.

### Uso Básico
```python
import pandas as pd
import streamlit as st
from st_aggrid import AgGrid
from make_aggrid import make_grid

df = pd.read_csv("dados.csv")

grid_options = make_grid(df)

grid_response = AgGrid(
    st.session_state.df,
    gridOptions=grid_options,
    enable_enterprise_modules=False,
    fit_columns_on_grid_load=True,
    allow_unsafe_jscode=True,
    height=400
)
```

## 🎯 Recursos incluídos

- Filtros automáticos para texto, número e datas
- Formatação brasileira para números e datas (`pt-BR`)
- Alinhamento de colunas conforme tipo
- Edição inline
- Paginação e animações

### 🧪 Exemplo Avançado com Streamlit

```python
import streamlit as st
import pandas as pd
from st_aggrid import AgGrid
from make_aggrid import make_grid

data = {
    "Nome": ["Ana", "João", "Carlos"],
    "Idade": [23, 35, 29],
    "Salário": [3000.50, 5000.00, 4200.75],
    "Data de Admissão": pd.to_datetime(["2020-01-15", "2019-03-10", "2021-07-22"])
}

df = pd.DataFrame(data)

st.title("Tabela Interativa com AgGrid")

grid_options = make_grid(df)
AgGrid(df, gridOptions=grid_options, editable=True, fit_columns_on_grid_load=True)
```

### 🤝 Contribuir

Contribuições são muito bem-vindas! Para contribuir:
1. Faça um fork do repositório

2.  Crie uma branch (git checkout -b nova-funcionalidade)

3.  Faça suas alterações e commit (git commit -am 'Adiciona nova funcionalidade')

4.  Push para a branch (git push origin nova-funcionalidade)

5.  Abra um Pull Request

Sinta-se à vontade para abrir issues com ideias, sugestões ou bugs que encontrar.

## 📝 Changelog

Todas as mudanças relevantes são listadas no CHANGELOG.md

## Licença
MIT
pokime 0.1.1
MCP server that gives information on Anime and Pokemon
License: MIT
Requires Python: >=3.10

# Pokime 🎮📺

**Pokime** is an MCP (Model Context Protocol) server that allows LLMs to retrieve rich information about **Pokémon** and **anime** titles in real-time. You can get detailed Pokémon stats, compare two Pokémon, and explore multi-season anime metadata from AniList.

---

## ✨ Features

- 🔍 **Pokémon Lookup** – Type, abilities, base stats, height, and weight.
- ⚔️ **Pokémon Comparison** – Side-by-side detail of two Pokémon.
- 📺 **Anime Info (via AniList)** – Format, episodes, genres, ratings, descriptions across all seasons and formats.

---

## 🧱 Tech Stack

- [PokéAPI](https://pokeapi.co/) for Pokémon data
- [AniList GraphQL API](https://anilist.gitbook.io/) for anime data
- Python 3.10+
- `.env` config support with `python-dotenv`

---
## How to add 
```
"pokime": {
    "command": "uvx",
    "args": [
        "pokime"
      ]
    }
```
agentk 0.3.2
"AGENT" K is a complete minimalistic kubectl "doner"-wrap
License: MIT
Requires Python: <4.0,>=3.6
Keywords: kubectl, tool, kubernetes

# "k"

## TLDR;

Install the "k" by either doing: 

	pip install agentk

(Yes, ^^ it is written in python and your OS needs to have recent version 2 or 3)

or copying it in some bin folder on your PATH and running `pip install -r requirements.txt`


---

 > "A person is smart. People are dumb, panicky, dangerous animals, and you know it." -- Agent K

#### "AGENT" K is a complete minimalistic kubectl "doner"-wrap

Obviously, as a short-hand wrapper, **k** can do everything **kubectl** already can, but it is (a) shorter and (b) adds few tricks like merging configs and switching contexts .. (k) feeds back to the *kubectl* command-line those args which it does not want to intercept or handle.

## Usage

The following is equivalent:

	kubectl get pods --all-namespaces
	k get pods -A
	k p -A


### Switching context

Argument-free invocation prompts for context switch options between multiple cluster contexts found in `~/.kube/config`:

	k


### Switching namespaces

One can change the default namespace on the currently active context (`namespace` key in `~/.kube/config`) using either of two equivalent commands:

	kubectl config set-context $(kubectl config current-context) --namespace foo
	k sn foo

The last command is a `k` shortcut.


### Shortcuts to get resources

You can find the full list of shortcuts defined as the dictionary inside the `k` script. In particular that would be:

    # resource
    "ev": "event",
    "ep": "endpoints",
    "p": "pod",
    "s": "service",
    "v": "volume",
    "n": "node",
    "dp": "deployment",
    "st": "statefulset",
    "in": "ingress",
    "ns": "namespace",

At the end of the list there are one letter action-shortcuts:

    # actions
    "c": "create",
    "a": "apply",
    "d": "delete",

This means that the following is equivalent:

	kubectl apply -f <foo-k8s-manifest.yaml>
	k a -f <foo-k8s-manifest.yaml>


## Develop

To remind, you can do `pip install -e .` in order to utilize developer mode.

## Installation in the cloud

If you work with `kubectl` without a privileged or super-user access, for example inside a corporate network or in a cloud-shell (but you still have access to python), then your installation will look like:

	pip install --user agentk

This will install the script in your local `$HOME` folder.

Don't forget to append your `~/.bashrc` or `~/bash_profile` or other shell-rc file with:

	export PATH="$HOME/.local/bin:$PATH"

## Command completion

You can put this into your `.bashrc` to get alias and auto completion for `k` similar as for `kubectl`:

```
source <(kubectl completion bash | sed s/kubectl/k/g)
```

Similar works well for **zsh**.
python-generate-xlsx-report 0.0.10
Um gerador de relatório de análise quantitativa e qualitativa
License: MIT
Requires Python: >=3.12

# python-xlsx-autoreport
Um pacote usado para facilitar a criação de relatórios de análise quantitativa.


Você encontrará dados inválidos com mais facilidade
![Validador](python_xlsx_autoreport/src/assets/vigilante_bob_esponja.png)