Metadata-Version: 2.4
Name: beapro-state-machine
Version: 0.1.0
Summary: State machine framework for BotCity automation bots
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Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: botcity-maestro-sdk==0.9.0
Requires-Dist: python-statemachine<4.0.0,>=3.0.0
Requires-Dist: python-dotenv>=1.0.0
Requires-Dist: mss>=9.0.0
Dynamic: license-file

# beapro-state-machine

BeaPro (BotCity Enterprise Automation Process) é uma biblioteca Python de automação baseada em **máquina de estados** para construir bots de processamento de dados com integração nativa à plataforma **BotCity Maestro**.

Fornece uma arquitetura declarativa com quatro estados padrão e um pipeline de tratamento de erros embutido, deixando ao desenvolvedor apenas a responsabilidade de implementar a lógica de negócio no estado `PROCESS`.

## Instalação

```bash
pip install beapro-state-machine
```

## Configuração de Credenciais

Chame `beapro.configure()` **antes** de instanciar `ExecutionContext`. Ela carrega as credenciais do Maestro a partir de um arquivo `.env` (por padrão) ou de parâmetros explícitos, sem sobrescrever variáveis já definidas no ambiente de processo.

```python
import beapro
beapro.configure()  # lê do .env sem sobrescrever vars já definidas no ambiente

from beapro import BeaproStateMachine, ExecutionContext, ContextProvider
```

### Parâmetros de `configure()`

| Parâmetro | Padrão | Descrição |
|-----------|--------|-----------|
| `server` | `""` | URL do servidor Maestro — sobrescreve `DEFAULT_SERVER` |
| `login` | `""` | UUID de login — sobrescreve `DEFAULT_LOGIN` |
| `key` | `""` | Chave de API — sobrescreve `DEFAULT_KEY` |
| `dotenv_path` | `".env"` | Caminho do arquivo `.env` a carregar |

Para passar credenciais diretamente sem `.env`:

```python
beapro.configure(
    server="https://developers.botcity.dev",
    login="<uuid>",
    key="<chave>",
    dotenv_path="",  # desativa o carregamento do .env
)
```

**Precedência** (maior para menor): parâmetros explícitos → variáveis de ambiente → arquivo `.env`.

## Variáveis de Ambiente

```env
DEFAULT_SERVER='https://developers.botcity.dev'
DEFAULT_LOGIN='<uuid-do-login>'
DEFAULT_KEY='<chave-api>'
TASK_ID='<id-da-task>'      # opcional — usado apenas em execução local sem runner
BEAPRO_LOG_DIR='/caminho'   # opcional — diretório de logs (padrão: output/)
```

`DEFAULT_SERVER`, `DEFAULT_LOGIN` e `DEFAULT_KEY` são obrigatórios.

## Fluxo de Estados

```
INIT → GET_DATA → PROCESS → END
  ↓        ↓          ↓
  └──────→ ErrorHandler (retry → fallback → abort)
```

| Estado | Responsabilidade |
|--------|-----------------|
| `INIT` | Valida ambiente e prepara serviços |
| `GET_DATA` | Fornece o próximo item para processamento |
| `PROCESS` | Lógica de negócio — **ponto de extensão principal** |
| `END` | Reporta contagens ao Maestro e finaliza a task |
| `ErrorHandler` | Captura exceções, executa retries e envia alertas em fallback |

## Modos de Operação

`BeaproStateMachine` suporta dois modos, definidos pelo parâmetro `mode`:

| Modo | `mode=` | Fonte dos dados | Iteração |
|------|---------|-----------------|----------|
| **datapool** (padrão) | `"datapool"` | Itens do DataPool do Maestro | Loop até esgotar todos os itens |
| **task** | `"task"` | Parâmetros da task atual | Processa uma única vez |

No modo **task** não é necessário definir `datapool_label`. Os parâmetros configurados na Automação do Maestro ficam disponíveis em `context.item.data` dentro do `ProcessState`, com o mesmo contrato do modo datapool.

> Passar `get_data_state` explicitamente tem prioridade sobre `mode`.

## Uso Básico

### 1. Implemente o estado PROCESS

```python
from beapro.state_templates import ProcessState

class MeuProcessState(ProcessState):
    def execute(self):
        item = self.context.item
        self.services.log(f"Processando: {item.data}")
        # lógica de negócio aqui
        return "SUCCESS"
```

Valores de retorno aceitos por `execute()`:

| Retorno | Efeito |
|---------|--------|
| `"SUCCESS"` | Item marcado como sucesso no DataPool; avança para o próximo |
| `"BUSINESS_ERROR"` | Item marcado como erro de negócio; avança para o próximo |
| qualquer outro / exceção | Aciona pipeline de retry → fallback → abort |

### 2. Inicialize e execute — modo datapool

```python
import beapro
beapro.configure()

from beapro import BeaproStateMachine, ExecutionContext, ContextProvider

context = ExecutionContext(datapool_label="meu-datapool")
ContextProvider.initialize(context)

try:
    machine = BeaproStateMachine(process_state=MeuProcessState())
    machine.activate_initial_state()
finally:
    ContextProvider.reset()
```

### 3. Inicialize e execute — modo task

Ideal para bots acionados diretamente pelo Maestro com parâmetros configurados na Automação. Não requer DataPool.

```python
import beapro
beapro.configure()

from beapro import BeaproStateMachine, ExecutionContext, ContextProvider

context = ExecutionContext()
ContextProvider.initialize(context)

try:
    machine = BeaproStateMachine(mode="task", process_state=MeuProcessState())
    machine.activate_initial_state()
finally:
    ContextProvider.reset()
```

`ContextProvider.reset()` no bloco `finally` limpa o singleton ao final de cada execução.

## Tratamento de Erros

Lance as exceções da lib para acionar comportamentos específicos do pipeline:

```python
from beapro import BusinessException, SystemException, StopProcessException
from beapro.state_templates import ProcessState

class MeuProcessState(ProcessState):
    def execute(self):
        item = self.context.item

        if not item.data.get("cpf"):
            raise BusinessException("CPF ausente — item inválido")

        if not self._conectar_erp():
            raise SystemException("Timeout ao conectar ao ERP")

        return "SUCCESS"
```

| Exceção | Efeito |
|---------|--------|
| `BusinessException` | Item marcado como erro de negócio; sem retry |
| `SystemException` | Aciona retry; em abort, reinicia a task automaticamente |
| `StopProcessException` | Parada controlada sem registrar erro |
| `InterruptRequested` | Interrupção via Maestro; relançada sem retry |

Pipeline completo:
1. Exceção não tratada → `fail()` → `ErrorHandler.retry`
2. Retries esgotados → `fallback` → log crítico + alerta enviado
3. `abort` → executa `END` para limpeza final

## Logging

O logger escreve simultaneamente em três destinos:

1. **Console** — `INFO` e acima
2. **Arquivo local** — `output/<timestamp>.log` (todos os níveis)
3. **BotCity Maestro** — via SDK (falha silenciosa se indisponível)

```env
BEAPRO_LOG_DIR=/caminho/para/logs   # padrão: output/
```

## API Pública

```python
import beapro
beapro.configure()

from beapro import (
    BeaproStateMachine,   # orquestrador principal
    ExecutionContext,     # estado compartilhado da execução
    TransactionItem,      # item de dados atual
    ContextProvider,      # singleton de contexto global
    BusinessException,
    SystemException,
    StopProcessException,
    InterruptRequested,
)

from beapro.state_templates import ProcessState  # base para extensão
```

## Estrutura da Biblioteca

```
beapro/
├── __init__.py               # API pública + configure()
├── core/
│   ├── state_machine.py      # BeaproStateMachine
│   ├── base_state.py         # BaseState (abstrata)
│   ├── context_provider.py   # ContextProvider (singleton)
│   ├── execution.py          # ExecutionContext + TransactionItem
│   ├── container.py          # ServicesContainer (DI)
│   ├── exceptions.py         # Hierarquia de exceções
│   └── settings.py           # Leitura de variáveis de ambiente
├── services/
│   ├── logger.py             # MaestroLogger
│   ├── datapool.py           # DataPool (lazy init)
│   ├── alert.py              # Alert
│   └── screenshot.py         # ScreenshotService
└── state_templates/
    ├── init.py               # InitState
    ├── get_data.py           # GetDataState (modo datapool)
    ├── get_task.py           # GetTaskState (modo task)
    ├── process.py            # ProcessState (ponto de extensão)
    └── end.py                # EndState
```

## Dependências

| Pacote | Versão |
|--------|--------|
| `botcity-maestro-sdk` | ==0.9.0 |
| `python-statemachine` | >=3.0.0,<4.0.0 |
| `python-dotenv` | >=1.0.0 |
| `mss` | >=9.0.0 |

## Padrões de Design

| Padrão | Onde |
|--------|------|
| **Singleton** | `ContextProvider` |
| **Template Method** | `BaseState.execute()` |
| **Dependency Injection** | `ServicesContainer` |
| **Iterator** | `DataPool` |
| **Strategy** | Estados concretos substituem comportamento padrão |
