src/README.md

# `gradio_logsview`
<img alt="Static Badge" src="https://img.shields.io/badge/version%20-%200.0.1%20-%20orange">  

Visualize logs in your Gradio app

## Installation

```bash
pip install gradio_logsview
```

## Usage

```python
import logging
import random
import time

import gradio as gr
from gradio_logsview import LogsView


def random_values(failing: bool = False):
    for i in range(10):
        logging.log(
            random.choice(
                [  # Random levels
                    logging.INFO,
                    logging.DEBUG,
                    logging.WARNING,
                    logging.ERROR,
                    logging.CRITICAL,
                ]
            ),
            f"Value {i+1}",  # Random values
        )
        time.sleep(random.uniform(0, 1))
        if failing and i == 5:
            raise ValueError("Failing!!")


def fn_process_success():
    yield from LogsView.run_process(["python", "-u", "demo/script.py"])


def fn_process_failing():
    yield from LogsView.run_process(["python", "-u", "demo/script.py", "--failing"])


def fn_thread_success():
    yield from LogsView.run_thread(random_values, log_level=logging.INFO, failing=False)


def fn_thread_failing():
    yield from LogsView.run_thread(random_values, log_level=logging.INFO, failing=True)


markdown_top = """
# LogsView Demo

This demo shows how to use the `LogsView` component to display logs from a process or a thread in real-time.

Click on any button to launch a process or a thread and see the logs displayed in real-time.
In the thread example, logs are generated randomly with different log levels.
In the process example, logs are generated by a Python script but any command can be executed.
"""


markdown_bottom = """
## How to run in a thread?

With `LogsView.run_thread`, you can run a function in a separate thread and capture logs in real-time.
You can configure which logs to capture (log level and logger name).

```py
from gradio_logsview import LogsView

def fn_thread():
    # Run `my_function` in a separate thread
    # All logs above `INFO` level will be captured and displayed in real-time.
    yield from LogsView.run_thread(my_function, log_level=logging.INFO, arg1="value1")

with gr.Blocks() as demo:
    logs = LogsView()
    btn = gr.Button("Run thread")
    btn.click(fn_thread, outputs=logs)
```

## How to run in a process?

With `LogsView.run_process`, you can run a command in a separate process and capture logs from the process in real-time.
    
```py
from gradio_logsview import LogsView

def fn_process():
    # Run a process and capture all logs from the process
    yield from LogsView.run_process(
        cmd=[mergekit-yaml", "config.yaml", "merge", "--copy-", "--cuda", "--low-cpu-memory"]
    )

with gr.Blocks() as demo:
    logs = LogsView()
    btn = gr.Button("Run process")
    btn.click(fn_process, outputs=logs)
```
"""

with gr.Blocks() as demo:
    gr.Markdown(markdown_top)

    with gr.Row():
        btn_thread_success = gr.Button("Run thread (success)")
        btn_thread_failing = gr.Button("Run thread (failing)")
    with gr.Row():
        btn_process_success = gr.Button("Run process (success)")
        btn_process_failing = gr.Button("Run process (failing)")
    logs = LogsView()

    gr.Markdown(markdown_bottom)

    btn_thread_failing.click(fn_thread_failing, outputs=logs)
    btn_thread_success.click(fn_thread_success, outputs=logs)
    btn_process_failing.click(fn_process_failing, outputs=logs)
    btn_process_success.click(fn_process_success, outputs=logs)


if __name__ == "__main__":
    demo.launch()

```

## `LogsView`

### Initialization

<table>
<thead>
<tr>
<th align="left">name</th>
<th align="left" style="width: 25%;">type</th>
<th align="left">default</th>
<th align="left">description</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><code>value</code></td>
<td align="left" style="width: 25%;">

```python
str | Callable | tuple[str] | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">Default value to show in the code editor. If callable, the function will be called whenever the app loads to set the initial value of the component.</td>
</tr>

<tr>
<td align="left"><code>every</code></td>
<td align="left" style="width: 25%;">

```python
float | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.</td>
</tr>

<tr>
<td align="left"><code>lines</code></td>
<td align="left" style="width: 25%;">

```python
int
```

</td>
<td align="left"><code>5</code></td>
<td align="left">None</td>
</tr>

<tr>
<td align="left"><code>label</code></td>
<td align="left" style="width: 25%;">

```python
str | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">The label for this component. Appears above the component and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.</td>
</tr>

<tr>
<td align="left"><code>show_label</code></td>
<td align="left" style="width: 25%;">

```python
bool | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">if True, will display label.</td>
</tr>

<tr>
<td align="left"><code>container</code></td>
<td align="left" style="width: 25%;">

```python
bool
```

</td>
<td align="left"><code>True</code></td>
<td align="left">If True, will place the component in a container - providing some extra padding around the border.</td>
</tr>

<tr>
<td align="left"><code>scale</code></td>
<td align="left" style="width: 25%;">

```python
int | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.</td>
</tr>

<tr>
<td align="left"><code>min_width</code></td>
<td align="left" style="width: 25%;">

```python
int
```

</td>
<td align="left"><code>160</code></td>
<td align="left">minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.</td>
</tr>

<tr>
<td align="left"><code>visible</code></td>
<td align="left" style="width: 25%;">

```python
bool
```

</td>
<td align="left"><code>True</code></td>
<td align="left">If False, component will be hidden.</td>
</tr>

<tr>
<td align="left"><code>elem_id</code></td>
<td align="left" style="width: 25%;">

```python
str | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.</td>
</tr>

<tr>
<td align="left"><code>elem_classes</code></td>
<td align="left" style="width: 25%;">

```python
list[str] | str | None
```

</td>
<td align="left"><code>None</code></td>
<td align="left">An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.</td>
</tr>

<tr>
<td align="left"><code>render</code></td>
<td align="left" style="width: 25%;">

```python
bool
```

</td>
<td align="left"><code>True</code></td>
<td align="left">If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.</td>
</tr>
</tbody></table>


### Events

| name | description |
|:-----|:------------|
| `change` | Triggered when the value of the LogsView changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input. |
| `input` | This listener is triggered when the user changes the value of the LogsView. |
| `focus` | This listener is triggered when the LogsView is focused. |
| `blur` | This listener is triggered when the LogsView is unfocused/blurred. |



### User function

The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).

- When used as an Input, the component only impacts the input signature of the user function.
- When used as an output, the component only impacts the return signature of the user function.

The code snippet below is accurate in cases where the component is used as both an input and an output.

- **As output:** Is passed, passes the code entered as a `str`.
- **As input:** Should return, expects a list of `Log` logs.

 ```python
 def predict(
     value: LogsView
 ) -> list[Log]:
     return value
 ```
 

## `Log`
```python
@dataclass
class Log:
    level: Literal[
        "INFO", "DEBUG", "WARNING", "ERROR", "CRITICAL"
    ]
    message: str
    timestamp: str
```

## `LogsView`
```python
class LogsView(Component):
    EVENTS = [
        Events.change,
        Events.input,
        Events.focus,
        Events.blur,
    ]

    def __init__(
        self,
        value: str | Callable | tuple[str] | None = None,
        *,
        every: float | None = None,
        lines: int = 5,
        label: str | None = None,
        show_label: bool | None = None,
        container: bool = True,
        scale: int | None = None,
        min_width: int = 160,
        visible: bool = True,
        elem_id: str | None = None,
        elem_classes: list[str] | str | None = None,
        render: bool = True,
    ):
        self.language = "shell"
        self.lines = lines
        self.interactive = False
        super().__init__(
            label=label,
            every=every,
            show_label=show_label,
            container=container,
            scale=scale,
            min_width=min_width,
            visible=visible,
            elem_id=elem_id,
            elem_classes=elem_classes,
            render=render,
            value=value,
        )

    def preprocess(self, payload: str | None) -> "LogsView":
        raise NotImplementedError(
            "LogsView cannot be used as an input component."
        )

    def postprocess(self, value: List[Log]) -> List[Log]:
        return value

    def api_info(self) -> dict[str, Any]:
        return {
            "items": {
                "level": "string",
                "message": "string",
                "timestamp": "number",
            },
            "title": "Logs",
            "type": "array",
        }

    def example_payload(self) -> Any:
        return [
            Log(
                "INFO",
                "Hello World",
                datetime.now().isoformat(),
            )
        ]

    def example_value(self) -> Any:
        return [
            Log(
                "INFO",
                "Hello World",
                datetime.now().isoformat(),
            )
        ]

    @classmethod
    def run_process(
        cls,
        command: List[str],
        date_format: str = "%Y-%m-%d %H:%M:%S",
    ) -> Generator[List[Log], None, None]:
        process = subprocess.Popen(
            command,
            stdout=subprocess.PIPE,
            stderr=subprocess.STDOUT,
            text=True,
        )

        if process.stdout is None:
            raise ValueError("stdout is None")

        logs = []

        def _log(level: str, message: str):
            log = Log(
                level=level,
                message=message,
                timestamp=datetime.now().strftime(
                    date_format
                ),
            )
            logs.append(log)
            return logs

        _log("INFO", f"Running {' '.join(command)}")
        for line in process.stdout:
            yield _log("INFO", line.strip())

        # TODO: what if task is cancelled but process is still running?

        process.stdout.close()
        return_code = process.wait()
        if return_code:
            yield _log(
                "ERROR",
                f"Process exited with code {return_code}",
            )
        else:
            yield _log(
                "INFO", "Process exited successfully"
            )

    @classmethod
    def run_thread(
        cls,
        fn: Callable,
        log_level: int = logging.INFO,
        logger_name: str | None = None,
        date_format: str = "%Y-%m-%d %H:%M:%S",
        **kwargs,
    ) -> Generator[List[Log], None, None]:
        logs = [
            Log(
                level="INFO",
                message=f"Running {fn.__name__}({', '.join(f'{k}={v}' for k, v in kwargs.items())})",
                timestamp=datetime.now().strftime(
                    date_format
                ),
            )
        ]
        yield logs

        thread = Thread(
            target=non_failing_fn(fn), kwargs=kwargs
        )

        def _log(record: logging.LogRecord) -> bool:
            if record.thread != thread.ident:
                return False  # Skip if not from the thread
            if logger_name and not record.name.startswith(
                logger_name
            ):
                return False  # Skip if not from the logger
            if record.levelno < log_level:
                return False  # Skip if too verbose
            log = Log(
                level=record.levelname,
                message=record.getMessage(),
                timestamp=datetime.fromtimestamp(
                    record.created
                ).strftime(date_format),
            )
            logs.append(log)
            return True

        with capture_logging(log_level) as log_queue:
            thread.start()

            # Loop to capture and yield logs from the thread
            while thread.is_alive():
                while True:
                    try:
                        if _log(log_queue.get_nowait()):
                            yield logs
                    except queue.Empty:
                        break
                thread.join(
                    timeout=0.1
                )  # adjust the timeout as needed

        # After the thread completes, yield any remaining logs
        while True:
            try:
                if _log(log_queue.get_nowait()):
                    yield logs
            except queue.Empty:
                break

        logs.append(
            Log(
                level="INFO",
                message="Thread completed successfully",
                timestamp=datetime.now().strftime(
                    date_format
                ),
            )
        )
```