diff --git a/examples/component_demo.ipynb b/examples/component_demo.ipynb
new file mode 100644
index 0000000..9066c14
--- /dev/null
+++ b/examples/component_demo.ipynb
@@ -0,0 +1,180 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2142be9e-460c-45af-88aa-d356954b0caa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pygwalker as pyg\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7384b136-9098-482d-8914-1663547dc6ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"https://kanaries-app.s3.ap-northeast-1.amazonaws.com/public-datasets/bike_sharing_dc.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45cbe3c8-6606-498b-a741-455425798cc9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pyg.component(df).bar().encode(x=\"season\", y=\"sum(casual)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf5f40ff-a2ed-44c6-9f85-d633b75fa020",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component = pyg.component(df)\n",
+    "component_0 = component.encode(x=\"season\", y=\"sum(casual)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a98cf2a9-5286-4f4a-9279-d51a69d166bb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.bar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d81d0c87-4c6f-42f8-8d22-8b32fc61384f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.area()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b5f1b05a-4b43-4f73-9558-1ce2edae81a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.line()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d8f9721-688f-4ade-aaaa-577be9bda56a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.trail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "901ecec4-cddc-4b74-afac-c82a7c52e98e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component.scatter().encode(x=\"feeling_temp\", y=\"temperature\", color=\"humidity\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "98bb748f-0aaf-4b43-acbe-0524eafe10af",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component.circle().encode(x=\"feeling_temp\", y=\"temperature\", color=\"humidity\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "80c52a23-b3e3-4957-860f-21dd80b6ef47",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "(\n",
+    "component\n",
+    " .rect()\n",
+    " .encode(x='bin(\"feeling_temp\", 6)', y='bin(\"temperature\", 6)', color=\"MEAN(humidity)\")\n",
+    " .layout(height=400, width=460)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4cbf2edb-8bef-4190-986f-62b48517e7f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component.arc().encode(theta=\"SUM(registered)\", color=\"season\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f622848b-6122-4ee4-a7b1-d8521520b63f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.bar().explorer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aafdd3b4-6819-480f-9c34-70c8d1aa410e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.profiling()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bff819f3-209d-4a78-b723-103b70dfb2a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/pygwalker/__init__.py b/pygwalker/__init__.py
index 92ac2ef..e4254a9 100644
--- a/pygwalker/__init__.py
+++ b/pygwalker/__init__.py
@@ -10,12 +10,13 @@
 from pygwalker.services.global_var import GlobalVarManager
 from pygwalker.services.kaggle import show_tips_user_kaggle as __show_tips_user_kaggle
 
-__version__ = "0.4.9.1"
+__version__ = "0.4.9.2"
 __hash__ = __rand_str()
 
 from pygwalker.api.jupyter import walk, render, table
 from pygwalker.api.html import to_html
 from pygwalker.data_parsers.base import FieldSpec
+from pygwalker.api.component import component
 
 if GlobalVarManager.privacy == 'offline':
     logging.getLogger(__name__).info("Running in offline mode. There might be newer releases available. Please check at https://github.com/Kanaries/pygwalker or https://pypi.org/project/pygwalker.")
@@ -23,4 +24,4 @@
 if __check_kaggle():
     __show_tips_user_kaggle()
 
-__all__ = ["walk", "render", "table", "to_html", "FieldSpec", "GlobalVarManager"]
+__all__ = ["walk", "render", "table", "to_html", "FieldSpec", "GlobalVarManager", "component"]
diff --git a/pygwalker/api/component.py b/pygwalker/api/component.py
new file mode 100644
index 0000000..86f90ab
--- /dev/null
+++ b/pygwalker/api/component.py
@@ -0,0 +1,516 @@
+from typing import List, Optional, Dict, Any, Union
+from typing_extensions import Literal
+from copy import deepcopy
+
+from pydantic import BaseModel, Field
+import sqlglot
+import sqlglot.expressions as exp
+
+from .pygwalker import PygWalker
+from pygwalker._typing import DataFrame, IAppearance, IThemeKey, ISpecIOMode
+from pygwalker.data_parsers.base import FieldSpec
+from pygwalker.data_parsers.database_parser import Connector
+from pygwalker.utils.randoms import rand_str
+
+
+GRAPHIC_WALKER_AGG_FUNCS = {
+    "sum", "mean", "median", "count",
+    "min", "max", "variance", "stddev",
+}
+
+GRAPHIC_WALKER_FIELD_FUNCS = {
+    "bin", "bin_count"
+}
+
+
+def _convert_sql_to_field(sql: str, is_agg_sql: bool) -> Dict[str, Any]:
+    """Convert sql to field info."""
+    fid = "gw_" + rand_str(6)
+    field_item = {
+        "fid": fid,
+        "name": sql,
+        "analyticType": "dimension",
+        "semanticType": "nominal",
+        "computed": True,
+        "expression": {
+            "as": fid,
+            "op": "expr",
+            "params": [
+                {"type": "sql", "value": sql}
+            ]
+        }
+    }
+    if is_agg_sql:
+        field_item["aggName"] = "expr"
+    return field_item
+
+
+def _convert_gw_agg_function_to_field(func_name: str, field_name: str) -> Dict[str, Any]:
+    """Convert graphic walker agg function to field info."""
+    field_name = field_name.strip("\"'")
+    field_item = {
+        "fid": field_name,
+        "name": field_name,
+        "analyticType": "measure",
+        "semanticType": "quantitative",
+        "aggName": func_name,
+    }
+    return field_item
+
+
+def _convert_gw_bin_function_to_field(func_name: str, field_name: str, num: int) -> Dict[str, Any]:
+    """Convert graphic walker bin function to field info."""
+    fid = "gw_" + rand_str(6)
+    field_name = field_name.strip("\"'")
+    field_item = {
+        "fid": fid,
+        "name": f"{func_name}{num}({field_name})",
+        "analyticType": "dimension",
+        "semanticType": "ordinal",
+        "computed": True,
+        "expression": {
+            "op": func_name,
+            "as": fid,
+            "params": [
+                {"type": "field", "value": field_name},
+            ],
+            "num": num,
+        }
+    }
+    return field_item
+
+
+def _handle_anonymous(ast: exp.Anonymous, origin_str: str) -> Dict[str, Any]:
+    """Handle anonymous expression."""
+    func_name = str(ast.this).lower()
+    if func_name in GRAPHIC_WALKER_AGG_FUNCS:
+        return _convert_gw_agg_function_to_field(func_name, str(ast.expressions[0]))
+    if func_name in GRAPHIC_WALKER_FIELD_FUNCS:
+        return _convert_gw_bin_function_to_field(func_name, str(ast.expressions[0]), int(str(ast.expressions[1])))
+    return _convert_sql_to_field(origin_str, False)
+
+
+def _handle_agg_func(ast: exp.AggFunc, origin_str: str) -> Dict[str, Any]:
+    """Handle agg function expression."""
+    func_name = ast.sql_name().lower()
+    if func_name in GRAPHIC_WALKER_AGG_FUNCS:
+        return _convert_gw_agg_function_to_field(func_name, str(ast.this))
+    return _convert_sql_to_field(origin_str, True)
+
+
+class Expression(BaseModel):
+    op: str
+    as_: str = Field(alias="as")
+    params: List[Dict[str, Any]]
+
+
+class FieldInfo(BaseModel):
+    fid: str
+    name: str
+    semantic_type: str = Field(alias="semanticType")
+    analytic_type: str = Field(alias="analyticType")
+    computed: bool
+    agg_name: str = Field(alias="aggName")
+    expression: Expression
+
+
+# pylint: disable=protected-access
+class Component:
+    """
+    Component class for creating a chain of components.
+
+    Kargs:
+        - walker (PygWalker): PygWalker instance.
+        - render_type (str): render type.
+        - field_map (Dict[str, Any]): field map.
+        - single_chart_spec (Dict[str, Any]): single chart
+    """
+    def __init__(
+        self,
+        *,
+        walker: PygWalker,
+        render_type: str,
+        field_map: Dict[str, Any],
+        single_chart_spec: Dict[str, Any],
+    ):
+        self.walker = walker
+        self._render_type = render_type
+        self._field_map = field_map
+        self._single_chart_spec = single_chart_spec
+        self._runtime_time = None
+
+    def copy(self) -> "Component":
+        """return new copied component."""
+        return self.__class__(
+            walker=self.walker,
+            render_type=self._render_type,
+            field_map=deepcopy(self._field_map),
+            single_chart_spec=deepcopy(self._single_chart_spec)
+        )
+
+    def _update_single_chart_spec(self, key: str, value: Any) -> Dict[str, Any]:
+        """update single chart spec."""
+        cur_obj = self._single_chart_spec
+        keys = key.split("__")
+        for k in keys[:-1]:
+            cur_obj = cur_obj[k]
+        cur_obj[keys[-1]] = value
+
+    def _convert_string_to_field_info(self, s: str) -> Dict[str, Any]:
+        """
+        example: sum(field_name), field_name
+        """
+        ast = sqlglot.parse_one(s, dialect="duckdb")
+        if isinstance(ast, exp.Anonymous):
+            return _handle_anonymous(ast, s)
+        elif isinstance(ast, exp.AggFunc):
+            return _handle_agg_func(ast, s)
+        elif isinstance(ast, exp.Func):
+            return _convert_sql_to_field(s, False)
+        elif isinstance(ast, exp.Column):
+            return {
+                "fid": s,
+                "name": s,
+                "analyticType": "dimension",
+                "semanticType": "nominal",
+                "computed": False,
+                **self._field_map.get(s, {})
+            }
+        return {}
+
+    def _repr_html_(self) -> str:
+        return self.to_html()
+
+    def to_html(self) -> str:
+        if self._render_type == "pure_chart":
+            return self._get_single_chart_html()
+        if self._render_type == "explorer":
+            return self._get_explorer_html()
+        if self._render_type == "profiling":
+            return self._get_profiling_html()
+        return ""
+
+    def _get_single_chart_html(self) -> str:
+        return self.walker.get_single_chart_html_by_spec(spec=self._single_chart_spec)
+
+    def _get_explorer_html(self) -> str:
+        all_datas = None
+        if self.walker.kernel_computation:
+            all_datas = self.walker.data_parser.to_records()
+        pyg_props = self.walker._get_props(data_source=all_datas)
+        pyg_props["visSpec"] = [self._single_chart_spec]
+
+        return self.walker._get_render_iframe(pyg_props)
+
+    def _get_profiling_html(self) -> str:
+        all_datas = None
+        if self.walker.kernel_computation:
+            all_datas = self.walker.data_parser.to_records()
+        pyg_props = self.walker._get_props(data_source=all_datas)
+        pyg_props["gwMode"] = "table"
+        return self.walker._get_render_iframe(pyg_props)
+
+    def bar(self) -> "Component":
+        """Bar chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["bar"])
+        return copied_obj
+
+    def line(self) -> "Component":
+        """Line chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["line"])
+        return copied_obj
+
+    def area(self) -> "Component":
+        """Area chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["area"])
+        return copied_obj
+
+    def trail(self) -> "Component":
+        """Trail chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["trail"])
+        return copied_obj
+
+    def scatter(self) -> "Component":
+        """Scatter chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["point"])
+        return copied_obj
+
+    def circle(self) -> "Component":
+        """Circle chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["circle"])
+        return copied_obj
+
+    def tick(self) -> "Component":
+        """Tick chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["tick"])
+        return copied_obj
+
+    def rect(self) -> "Component":
+        """Rect chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["rect"])
+        return copied_obj
+
+    def arc(self) -> "Component":
+        """Arc chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["arc"])
+        return copied_obj
+
+    def text(self) -> "Component":
+        """Text chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["text"])
+        return copied_obj
+
+    def box(self) -> "Component":
+        """Box chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["boxplot"])
+        return copied_obj
+
+    def table(self) -> "Component":
+        """Table chart."""
+        copied_obj = self.copy()
+        copied_obj._update_single_chart_spec("config__geoms", ["table"])
+        return copied_obj
+
+    # pylint: disable=unused-argument
+    def encode(
+        self,
+        x: Union[str, List[str]] = "",
+        y: Union[str, List[str]] = "",
+        color: str = "",
+        opacity: str = "",
+        size: str = "",
+        shape: str = "",
+        radius: str = "",
+        theta: str = "",
+        longitude: str = "",
+        latitude: str = "",
+        geoid: str = "",
+        details: str = "",
+        text: str = "",
+    ) -> "Component":
+        """
+        Encode fields.
+        example: .encode(x="field_0", y="field_1", color="field_2")
+        .encode(x="field_0", y="SUM(field_1)")
+        """
+        all_params = {
+            key: [value] if isinstance(value, str) else value
+            for key, value in locals().items()
+            if key != "self"
+        }
+        copied_obj = self.copy()
+        params_key_map = {
+            "x": "columns",
+            "y": "rows",
+            "geoid": "geoId",
+        }
+
+        for key, field_str_list in all_params.items():
+            field_list = []
+            for field_str in field_str_list:
+                if not field_str:
+                    continue
+                field_info = copied_obj._convert_string_to_field_info(field_str)
+                if field_info.get("aggName"):
+                    copied_obj._update_single_chart_spec("config__defaultAggregated", True)
+                field_list.append(field_info)
+                if field_info["fid"] not in copied_obj._field_map:
+                    copied_obj._field_map[field_info["fid"]] = field_info
+                    if field_info["analyticType"] == "dimension":
+                        copied_obj._single_chart_spec["encodings"]["dimensions"].append(field_info)
+                    else:
+                        copied_obj._single_chart_spec["encodings"]["measures"].append(field_info)
+            copied_obj._single_chart_spec["encodings"][params_key_map.get(key, key)] = field_list
+
+        return copied_obj
+
+    # pylint: enable=unused-argument
+    def layout(
+        self,
+        *,
+        mode: Optional[Literal["auto", "fixed", "container"]] = None,
+        width: Optional[int] = None,
+        height: Optional[int] = None,
+        **kwargs
+    ) -> "Component":
+        """
+        Set layout config.
+        example: .layout(resolve__color=False)
+        {
+            "colorPalette": "paired",
+            "format": {},
+            "geoKey": "name",
+            "interactiveScale": False,
+            "resolve": {
+                "color": False,
+                "opacity": False,
+                "shape": False,
+                "size": False,
+                "x": False,
+                "y": False,
+            },
+            "scale": {
+                "opacity": {},
+                "size": {},
+            },
+            "scaleIncludeUnmatchedChoropleth": False,
+            "showActions": False,
+            "showTableSummary": False,
+            "size": {
+                "mode": "fixed",
+                "width": 360,
+                "height": 360,
+            },
+            "stack": "stack",
+            "useSvg": False,
+            "zeroScale": True,
+        }
+        """
+        copied_obj = self.copy()
+        layout_info = {
+            "size__mode": mode,
+            "size__width": width,
+            "size__height": height,
+            **kwargs
+        }
+        for key, value in layout_info.items():
+            if value is None:
+                continue
+            copied_obj._update_single_chart_spec("layout__" + key, value)
+
+        return copied_obj
+
+    def profiling(self) -> "Component":
+        """Profiling mode."""
+        copied_obj = self.copy()
+        copied_obj._render_type = "profiling"
+        return copied_obj
+
+    def explorer(self) -> "Component":
+        """Explorer mode."""
+        copied_obj = self.copy()
+        copied_obj._render_type = "explorer"
+        return copied_obj
+# pylint: enable=protected-access
+
+
+def component(
+    dataset: Union[DataFrame, Connector, str],
+    *,
+    field_specs: Optional[List[FieldSpec]] = None,
+    spec: str = "",
+    spec_io_mode: ISpecIOMode = "rw",
+    theme_key: IThemeKey = "vega",
+    appearance: IAppearance = "media",
+    show_cloud_tool: Optional[bool] = False,
+    kernel_computation: Optional[bool] = None,
+    kanaries_api_key: str = "",
+    **kwargs
+) -> Component:
+    """
+    Component class for creating a chain of components.
+
+    Args:
+        - dataset (pl.DataFrame | pd.DataFrame | Connector, optional): dataframe.
+
+    Kargs:
+        - field_specs (List[FieldSpec], optional): Specifications of some fields. They'll been automatically inferred from `df` if some fields are not specified.
+        - spec (str): chart config data. config id, json, remote file url
+        - spec_io_mode (ISpecIOMode): spec io mode, Default to "r", "r" for read, "rw" for read and write.
+        - theme_key ('vega' | 'g2' | 'streamlit'): theme type.
+        - appearance (Literal['media' | 'light' | 'dark']): 'media': auto detect OS theme.
+        - kernel_computation(bool): Whether to use kernel compute for datas, Default to None.
+        - kanaries_api_key (str): kanaries api key, Default to "".
+    """
+    walker = PygWalker(
+        gid=None,
+        dataset=dataset,
+        field_specs=field_specs,
+        spec=spec,
+        source_invoke_code="",
+        theme_key=theme_key,
+        appearance=appearance,
+        show_cloud_tool=show_cloud_tool,
+        use_preview=True,
+        kernel_computation=isinstance(dataset, (Connector, str)) or kernel_computation,
+        use_save_tool="w" in spec_io_mode,
+        gw_mode="explore",
+        is_export_dataframe="w" in spec_io_mode,
+        kanaries_api_key=kanaries_api_key,
+        default_tab="data",
+        cloud_computation=False,
+        **kwargs
+    )
+    render_type = "pure_chart"
+    field_map = {
+        field["fid"]: field
+        for field in walker.data_parser.raw_fields
+    }
+    single_chart_spec = {
+        "name": "Chart 1",
+        "visId": "",
+        "config": {
+            "coordSystem": "generic",
+            "defaultAggregated": False,
+            "geoms": ["auto"],
+            "limit": -1,
+            "timezoneDisplayOffset": 0,
+        },
+        "encodings": {
+            "dimensions": [field for field in walker.data_parser.raw_fields if field["analyticType"] == "dimension"],
+            "measures": [field for field in walker.data_parser.raw_fields if field["analyticType"] == "measure"],
+            "rows": [],
+            "columns": [],
+            "color": [],
+            "opacity": [],
+            "size": [],
+            "shape": [],
+            "radius": [],
+            "theta": [],
+            "longitude": [],
+            "latitude": [],
+            "geoId": [],
+            "details": [],
+            "filters": [],
+            "text": [],
+        },
+        "layout": {
+            "format": {},
+            "geoKey": "name",
+            "interactiveScale": False,
+            "resolve": {
+                "color": False,
+                "opacity": False,
+                "shape": False,
+                "size": False,
+                "x": False,
+                "y": False,
+            },
+            "showActions": False,
+            "showTableSummary": False,
+            "size": {
+                "mode": "fixed",
+                "width": 360,
+                "height": 360,
+            },
+            "stack": "stack",
+            "zeroScale": True,
+        }
+    }
+    return Component(
+        walker=walker,
+        render_type=render_type,
+        field_map=field_map,
+        single_chart_spec=single_chart_spec,
+    )
diff --git a/pygwalker/api/pygwalker.py b/pygwalker/api/pygwalker.py
index 7053bc2..9bcd4fa 100644
--- a/pygwalker/api/pygwalker.py
+++ b/pygwalker/api/pygwalker.py
@@ -319,6 +319,26 @@ def display_chart(self, chart_name: str, *, title: Optional[str] = None, desc: s
         )
         display_html(html)
 
+    def get_single_chart_html_by_spec(
+        self,
+        *,
+        spec: Dict[str, Any],
+        title: str = "",
+        desc: str = "",
+    ) -> str:
+        # pylint: disable=import-outside-toplevel
+        from pygwalker.utils.dsl_transform import dsl_to_workflow
+        workflow = dsl_to_workflow(spec)
+        data = self.data_parser.get_datas_by_payload(workflow)
+        return render_gw_chart_preview_html(
+            single_vis_spec=spec,
+            data=data,
+            theme_key=self.theme_key,
+            title=title,
+            desc=desc,
+            appearance=self.appearance
+        )
+
     def _get_chart_by_name(self, chart_name: str) -> ChartData:
         if chart_name not in self._chart_map:
             raise ValueError(f"chart_name: {chart_name} not found, please confirm whether to save")
diff --git a/pyproject.toml b/pyproject.toml
index e66f2f8..0c7a8de 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "pygwalker"
 dynamic = ["version"]
-requires-python = ">=3.6"
+requires-python = ">=3.7"
 description = "pygwalker: turn your data into an interactive UI for data exploration and visualization"
 authors = [ { name = "kanaries", email = "support@kanaries.net" } ]
 license-files = { paths = ["LICENSE"] }
@@ -19,7 +19,7 @@ dependencies = [
     "ipywidgets",
     "pydantic",
     "psutil",
-    "duckdb>=0.10.1,<=1.0.0",
+    "duckdb>=0.10.1,<2.0.0",
     "pyarrow",
     "sqlglot>=23.15.8",
     "requests",
@@ -34,7 +34,8 @@ dependencies = [
     "cachetools",
     "packaging",
     "numpy<2.0.0",
-    "ipylab<=1.0.0"
+    "ipylab<=1.0.0",
+    "quickjs",
 ]
 [project.urls]
 homepage = "https://kanaries.net/pygwalker"
diff --git a/tests/test_component_api.ipynb b/tests/test_component_api.ipynb
new file mode 100644
index 0000000..9066c14
--- /dev/null
+++ b/tests/test_component_api.ipynb
@@ -0,0 +1,180 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2142be9e-460c-45af-88aa-d356954b0caa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pygwalker as pyg\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7384b136-9098-482d-8914-1663547dc6ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"https://kanaries-app.s3.ap-northeast-1.amazonaws.com/public-datasets/bike_sharing_dc.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45cbe3c8-6606-498b-a741-455425798cc9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pyg.component(df).bar().encode(x=\"season\", y=\"sum(casual)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf5f40ff-a2ed-44c6-9f85-d633b75fa020",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component = pyg.component(df)\n",
+    "component_0 = component.encode(x=\"season\", y=\"sum(casual)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a98cf2a9-5286-4f4a-9279-d51a69d166bb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.bar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d81d0c87-4c6f-42f8-8d22-8b32fc61384f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.area()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b5f1b05a-4b43-4f73-9558-1ce2edae81a3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.line()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d8f9721-688f-4ade-aaaa-577be9bda56a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.trail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "901ecec4-cddc-4b74-afac-c82a7c52e98e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component.scatter().encode(x=\"feeling_temp\", y=\"temperature\", color=\"humidity\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "98bb748f-0aaf-4b43-acbe-0524eafe10af",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component.circle().encode(x=\"feeling_temp\", y=\"temperature\", color=\"humidity\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "80c52a23-b3e3-4957-860f-21dd80b6ef47",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "(\n",
+    "component\n",
+    " .rect()\n",
+    " .encode(x='bin(\"feeling_temp\", 6)', y='bin(\"temperature\", 6)', color=\"MEAN(humidity)\")\n",
+    " .layout(height=400, width=460)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4cbf2edb-8bef-4190-986f-62b48517e7f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component.arc().encode(theta=\"SUM(registered)\", color=\"season\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f622848b-6122-4ee4-a7b1-d8521520b63f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.bar().explorer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aafdd3b4-6819-480f-9c34-70c8d1aa410e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_0.profiling()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bff819f3-209d-4a78-b723-103b70dfb2a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}