semvec/pypi-packages huggingface dataset:
realtime-visualization 1.0.8
A general purpose realtime visualization
Requires Python: >=3.7

# Real time visualization
This program enables users to conveniently visualize their data in a real-time manner using the power of Dash and Plotly. The program reads the data from CSV files and generates graphs on a web browser. The graphs will be updated automatically upon changes to the files.

### Quick start
```
pip install realtime_visualization
```
***Usage type 1, build-in plots***: in this approach, all you need is to format the CSV files as instructed, determine the type of plot together with some other options and run the program.
```python
from realtime import monitor
settings = {
    "plot1": {
            "graph_dir" = "path/to/CSV/file1.csv",
            "graph_type" = "scatter",
            "graph_size" = 600
           },
    "plot2":{
            "graph_dir" = "path/to/CSV/file2.csv",
            "graph_type" = "lines",
            "graph_size" = 500,
            "x-axis-moves" = True,
            "x-axis-length" = 50
    }
}
monitor.watch(settings).run()
```
***Usage type 2, custom plots***: this approach enables the user to construct the plot in a desired way and pass it to the program together with CSV file address and some other options.
```python
from realtime import monitor
def figure1(data):
    fig = px.scatter(
        data,
        x=data["x"],
        y=data["y"],
        size=data["size"]
    )
    return fig
def figure2(data):
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=data["x1"], y=data["y1"],
                        mode='lines',
                        name='lines'))
    fig.add_trace(go.Scatter(x=data["x2"], y=data["y2"],
                        mode='lines+markers',
                        name='lines+markers'))
    return fig

settings = {
    "plot1": {
            "graph_dir" = "path/to/CSV/file1.csv",
            "graph_type" = custom,
            "figure" = figure1
           },
    "plot2":{
            "graph_dir" = "path/to/CSV/file2.csv",
            "graph_type" = custom,
            "figure" = figure2
    }
}
monitor.watch(settings).run()
```
See [Documentation](https://janursa.github.io/realtime_visualization/) for further information and examples.

### Installation
This package can be installed using pip:
```
pip install realtime_visualization
```
or conda:
```
conda install -c realtime_visualization
```
or download the package and command:
```
python install setup.py
```
### License
This project is licensed under the MIT License - see the LICENSE.md file for details

### Authors
* Jalil Nourisa

See also the list of contributors who participated in this project.

### Acknowledgments
Inspired by [sentdex](https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ)