Rendering and Output

class ChartRenderMethods:
    def render(self, path="render.html"):
        """
        Render chart to HTML file.
        
        Args:
            path (str): Output file path
            
        Returns:
            str: Generated HTML content
        """

    def render_embed(self):
        """
        Render chart as embeddable HTML fragment.
        
        Returns:
            str: HTML fragment without full page structure
        """

    def render_notebook(self):
        """
        Render chart for Jupyter notebook display.
        
        Returns:
            HTML: Jupyter notebook HTML display object
        """

    def dump_options(self):
        """
        Export chart configuration as JSON.
        
        Returns:
            str: JSON string of chart options
        """

    def dump_options_with_quotes(self):
        """
        Export chart configuration as JSON with quoted keys.
        
        Returns:
            str: JSON string with quoted keys
        """

    def get_js_dependencies(self):
        """
        Get JavaScript dependencies for the chart.
        
        Returns:
            list: List of required JavaScript files
        """

def make_snapshot(driver, file_content, output_name, delay=1, pixel_ratio=1, is_remove_html=False, **kwargs):
    """
    Generate static image snapshot of chart.
    
    Args:
        driver: Browser driver instance (selenium, pyppeteer, phantomjs)
        file_content (str): HTML content or file path
        output_name (str): Output image file path
        delay (int): Delay before screenshot in seconds  
        pixel_ratio (int): Device pixel ratio for high-DPI displays
        is_remove_html (bool): Remove temporary HTML file after generation
        **kwargs: Additional driver-specific options
        
    Returns:
        str: Output file path
    """

from pyecharts.charts import Bar
from pyecharts.render import make_snapshot
from snapshot_selenium import snapshot as driver

# Create chart
bar = Bar().add_xaxis(["A", "B", "C"]).add_yaxis("Series", [1, 2, 3])

# Generate image
make_snapshot(driver, bar.render(), "chart.png")

# Install: pip install snapshot-selenium
from snapshot_selenium import snapshot as selenium_driver

make_snapshot(selenium_driver, chart.render(), "output.png", delay=2)

# Install: pip install snapshot-pyppeteer
from snapshot_pyppeteer import snapshot as pyppeteer_driver

make_snapshot(pyppeteer_driver, chart.render(), "output.png")

# Install: pip install snapshot-phantomjs
from snapshot_phantomjs import snapshot as phantomjs_driver

make_snapshot(phantomjs_driver, chart.render(), "output.png")

class JupyterIntegration:
    def render_notebook(self):
        """
        Display chart in Jupyter notebook cell output.
        
        Returns:
            HTML: IPython HTML display object
        """

    def load_javascript(self):
        """
        Load required JavaScript libraries in notebook.
        
        Note: Usually handled automatically
        """

# Basic notebook display
from pyecharts.charts import Bar

bar = Bar().add_xaxis(["A", "B", "C"]).add_yaxis("Series", [1, 2, 3])
bar.render_notebook()  # Displays chart inline

# JupyterLab support
# Charts display natively in JupyterLab cells

# Notebook theming
from pyecharts import options as opts

bar = Bar(init_opts=opts.InitOpts(theme="dark"))
# Theme automatically adapts to notebook environment

from flask import Flask, render_template
from pyecharts.charts import Bar
from pyecharts import options as opts
from pyecharts.globals import CurrentConfig

app = Flask(__name__)

# Configure pyecharts for Flask
CurrentConfig.GLOBAL_ENV = Environment(loader=FileSystemLoader("./templates"))

@app.route("/")
def index():
    bar = (
        Bar()
        .add_xaxis(["A", "B", "C", "D"])
        .add_yaxis("Series", [1, 2, 3, 4])
        .set_global_opts(title_opts=opts.TitleOpts(title="Flask Chart"))
    )
    return render_template("index.html", chart=bar.render_embed())

from django.shortcuts import render
from pyecharts.charts import Line

def chart_view(request):
    line = (
        Line()
        .add_xaxis(["Jan", "Feb", "Mar", "Apr"])
        .add_yaxis("Revenue", [100, 200, 150, 300])
    )
    
    context = {"chart": line.render_embed()}
    return render(request, "chart.html", context)

from sanic import Sanic, response
from pyecharts.charts import Pie

app = Sanic("ChartApp")

@app.route("/chart")
async def chart_handler(request):
    pie = (
        Pie()
        .add("", [("A", 25), ("B", 35), ("C", 40)])
    )
    
    html_content = f"""
    <!DOCTYPE html>
    <html>
    <head><title>Chart</title></head>
    <body>{pie.render_embed()}</body>
    </html>
    """
    return response.html(html_content)

# Global configuration options
class CurrentConfig:
    ONLINE_HOST = "https://assets.pyecharts.org/assets/"  # CDN host
    NOTEBOOK_TYPE = "jupyter_notebook"  # Notebook type
    
# Asset management functions
def configure_assets(host=None, **kwargs):
    """
    Configure asset loading settings.
    
    Args:
        host (str): Custom asset host URL
        **kwargs: Additional configuration options
    """

def get_js_dependencies():
    """
    Get list of JavaScript dependencies.
    
    Returns:
        list: Required JavaScript files
    """

from pyecharts.globals import CurrentConfig

# Use local assets
CurrentConfig.ONLINE_HOST = "http://localhost:8000/assets/"

# Use custom CDN
CurrentConfig.ONLINE_HOST = "https://cdn.jsdelivr.net/npm/echarts@5/dist/"

class TemplateEngine:
    def render_chart_to_file(self, chart, template_name, output_path, **context):
        """
        Render chart using custom template.
        
        Args:
            chart: Chart instance
            template_name (str): Template file name
            output_path (str): Output file path
            **context: Additional template context variables
        """

    def render_charts_to_file(self, charts, template_name, output_path, **context):
        """
        Render multiple charts using custom template.
        
        Args:
            charts (list): List of chart instances
            template_name (str): Template file name
            output_path (str): Output file path
            **context: Additional template context variables
        """

<!-- templates/custom_chart.html -->
<!DOCTYPE html>
<html>
<head>
    <title>{{ title }}</title>
    <script src="https://cdn.jsdelivr.net/npm/echarts@5/dist/echarts.min.js"></script>
</head>
<body>
    <h1>{{ title }}</h1>
    <div id="chart" style="width: 100%; height: 400px;"></div>
    {{ chart_script }}
</body>
</html>

# Enable lazy loading for large datasets
from pyecharts import options as opts

bar = (
    Bar(init_opts=opts.InitOpts(renderer="canvas"))  # Use canvas for better performance
    .add_xaxis(large_dataset_x)
    .add_yaxis("Series", large_dataset_y, is_large=True, large_threshold=1000)
)

# Progressive rendering for large datasets
bar = (
    Bar()
    .add_xaxis(data_x)
    .add_yaxis("Series", data_y, progressive=5000, progressive_threshold=10000)
)

# Optimize memory usage for batch rendering
charts = []
for data_chunk in large_dataset_chunks:
    chart = create_chart(data_chunk)
    charts.append(chart.render_embed())
    del chart  # Free memory

# Combine rendered charts
final_html = combine_charts(charts)

# Handle rendering errors gracefully
try:
    chart.render("output.html")
except Exception as e:
    print(f"Rendering error: {e}")
    # Fallback to embedded rendering
    html_content = chart.render_embed()
    with open("output.html", "w", encoding="utf-8") as f:
        f.write(f"<html><body>{html_content}</body></html>")

# Validate chart before rendering
def validate_chart(chart):
    """Check if chart has required data and options."""
    if not chart.options.get("series"):
        raise ValueError("Chart has no data series")
    return True

# Memory-safe batch rendering
def render_charts_safely(charts, output_dir):
    """Render multiple charts with memory management."""
    for i, chart in enumerate(charts):
        try:
            chart.render(f"{output_dir}/chart_{i}.html")
        except Exception as e:
            print(f"Failed to render chart {i}: {e}")
        finally:
            del chart  # Free memory