H

[rakib06]

pip install streamlit pandas plotly tableauhyperapi

import streamlit as st
import pandas as pd
import plotly.express as px

from tableauhyperapi import HyperProcess, Connection

DATABASE = "test.hyper"

st.title("Hyper File Explorer")

query = st.text_area(
    "SQL Query",
    "SELECT * FROM Extract.Extract LIMIT 100"
)

if st.button("Run Query"):

    with HyperProcess() as hyper:
        with Connection(
            endpoint=hyper.endpoint,
            database=DATABASE
        ) as connection:

            rows = connection.execute_list_query(query)

            columns = [desc.name for desc in connection.catalog.get_table_definition(
                "Extract.Extract"
            ).columns]

    df = pd.DataFrame(rows, columns=columns)

    st.dataframe(df)

    if len(df.columns) >= 2:
        x_col = st.selectbox("X Axis", df.columns)
        y_col = st.selectbox("Y Axis", df.columns)

        fig = px.bar(df, x=x_col, y=y_col)

        st.plotly_chart(fig)

[rakib06]

from tableauhyperapi import HyperProcess, Connection, Telemetry

HYPER_PATH = r""

with HyperProcess(
    telemetry=Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU,
    hyper_path=HYPER_PATH
) as hyper:

    print("Hyper endpoint:", hyper.endpoint)

    with Connection(
        endpoint=hyper.endpoint,
        database="test.hyper"
    ) as connection:

        rows = connection.execute_list_query(
            "SELECT * FROM Extract.Extract LIMIT 10"
        )

        print(rows)

[rakib06]

import streamlit as st
import pandas as pd
import plotly.express as px

from tableauhyperapi import (
    HyperProcess,
    Connection,
    Telemetry,
    TableName
)

# =========================================================
# CONFIGURATION
# =========================================================

HYPER_PATH = r""

DATABASE = r""

# =========================================================
# PAGE SETTINGS
# =========================================================

st.set_page_config(
    page_title="Hyper File Explorer",
    layout="wide"
)

st.title("Tableau Hyper GUI Explorer")

st.markdown("Offline Tableau Alternative using Streamlit + Hyper API")

# =========================================================
# START HYPER PROCESS
# =========================================================

try:

    with HyperProcess(
        telemetry=Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU,
        hyper_path=HYPER_PATH
    ) as hyper:

        st.success(f"Hyper Server Started: {hyper.endpoint}")

        # =====================================================
        # CONNECT TO DATABASE
        # =====================================================

        with Connection(
            endpoint=hyper.endpoint,
            database=DATABASE
        ) as connection:

            # =================================================
            # GET TABLES
            # =================================================

            table_names = connection.catalog.get_table_names()

            st.sidebar.header("Available Tables")

            table_options = [str(t) for t in table_names]

            if not table_options:
                st.error("No tables found in Hyper file.")
                st.stop()

            selected_table = st.sidebar.selectbox(
                "Select Table",
                table_options
            )

            st.sidebar.write("Selected:", selected_table)

            # =================================================
            # DEFAULT QUERY
            # =================================================

            default_query = f"SELECT * FROM {selected_table} LIMIT 100"

            query = st.text_area(
                "SQL Query",
                default_query,
                height=150
            )

            # =================================================
            # RUN QUERY
            # =================================================

            if st.button("Run Query"):

                try:

                    result = connection.execute_list_query(query)

                    # =========================================
                    # GET COLUMN NAMES
                    # =========================================

                    table_def = connection.catalog.get_table_definition(
                        TableName(selected_table)
                    )

                    columns = [col.name for col in table_def.columns]

                    # =========================================
                    # DATAFRAME
                    # =========================================

                    df = pd.DataFrame(result, columns=columns[:len(result[0])] if result else columns)

                    st.subheader("Query Results")

                    st.dataframe(
                        df,
                        use_container_width=True
                    )

                    # =========================================
                    # CSV EXPORT
                    # =========================================

                    csv = df.to_csv(index=False).encode("utf-8")

                    st.download_button(
                        "Download CSV",
                        csv,
                        "hyper_export.csv",
                        "text/csv"
                    )

                    # =========================================
                    # GRAPH SECTION
                    # =========================================

                    if len(df.columns) >= 2:

                        st.subheader("Generate Graph")

                        chart_type = st.selectbox(
                            "Chart Type",
                            [
                                "Bar",
                                "Line",
                                "Scatter",
                                "Pie",
                                "Histogram"
                            ]
                        )

                        x_col = st.selectbox(
                            "X Axis",
                            df.columns
                        )

                        y_col = st.selectbox(
                            "Y Axis",
                            df.columns
                        )

                        fig = None

                        # =====================================
                        # BAR CHART
                        # =====================================

                        if chart_type == "Bar":
                            fig = px.bar(
                                df,
                                x=x_col,
                                y=y_col
                            )

                        # =====================================
                        # LINE CHART
                        # =====================================

                        elif chart_type == "Line":
                            fig = px.line(
                                df,
                                x=x_col,
                                y=y_col
                            )

                        # =====================================
                        # SCATTER
                        # =====================================

                        elif chart_type == "Scatter":
                            fig = px.scatter(
                                df,
                                x=x_col,
                                y=y_col
                            )

                        # =====================================
                        # PIE CHART
                        # =====================================

                        elif chart_type == "Pie":
                            fig = px.pie(
                                df,
                                names=x_col,
                                values=y_col
                            )

                        # =====================================
                        # HISTOGRAM
                        # =====================================

                        elif chart_type == "Histogram":
                            fig = px.histogram(
                                df,
                                x=x_col
                            )

                        if fig:
                            st.plotly_chart(
                                fig,
                                use_container_width=True
                            )

                except Exception as query_error:
                    st.error(f"Query Error: {query_error}")

except Exception as e:
    st.error(f"Hyper Startup Error: {e}")

[rakib06]

import streamlit as st
import pandas as pd
import plotly.express as px
import os

from tableauhyperapi import (
    HyperProcess,
    Connection,
    Telemetry,
    CreateMode,
    TableDefinition,
    SqlType,
    Inserter,
    TableName
)

# =========================================================
# CONFIGURATION
# =========================================================

HYPER_PATH = r""

DEFAULT_DB = "demo.hyper"

# =========================================================
# STREAMLIT UI
# =========================================================

st.set_page_config(layout="wide")

st.title("Offline Tableau Hyper GUI")

st.sidebar.header("Hyper Database")

db_name = st.sidebar.text_input(
    "Hyper Database File",
    DEFAULT_DB
)

# =========================================================
# START HYPER PROCESS
# =========================================================

hyper = HyperProcess(
    telemetry=Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU,
    hyper_path=HYPER_PATH
)

# =========================================================
# CREATE DATABASE
# =========================================================

st.sidebar.subheader("Create New Hyper Database")

new_db = st.sidebar.text_input(
    "New Database Name",
    "new_database.hyper"
)

if st.sidebar.button("Create Hyper DB"):

    with Connection(
        endpoint=hyper.endpoint,
        database=new_db,
        create_mode=CreateMode.CREATE_AND_REPLACE
    ) as connection:

        connection.catalog.create_schema("Extract")

        example_table = TableDefinition(
            table_name=TableName("Extract", "Sales"),
            columns=[
                TableDefinition.Column("Region", SqlType.text()),
                TableDefinition.Column("Sales", SqlType.double()),
                TableDefinition.Column("Profit", SqlType.double())
            ]
        )

        connection.catalog.create_table(example_table)

        with Inserter(connection, example_table) as inserter:
            inserter.add_rows([
                ["East", 1000, 200],
                ["West", 1500, 300],
                ["North", 1200, 250],
                ["South", 1800, 500]
            ])
            inserter.execute()

    st.sidebar.success(f"Created {new_db}")

# =========================================================
# CONNECT TO DATABASE
# =========================================================

if os.path.exists(db_name):

    st.success(f"Connected to: {db_name}")

    with Connection(
        endpoint=hyper.endpoint,
        database=db_name
    ) as connection:

        # =================================================
        # SHOW TABLES
        # =================================================

        st.subheader("Tables")

        table_names = connection.catalog.get_table_names()

        table_list = []

        for table in table_names:
            table_list.append(str(table))

        st.write(table_list)

        # =================================================
        # SELECT TABLE
        # =================================================

        selected_table = st.selectbox(
            "Select Table",
            table_list
        )

        # =================================================
        # SQL QUERY
        # =================================================

        st.subheader("SQL Query")

        default_query = f'SELECT * FROM {selected_table} LIMIT 100'

        query = st.text_area(
            "Enter SQL",
            default_query,
            height=150
        )

        if st.button("Run Query"):

            rows = connection.execute_list_query(query)

            table_def = connection.catalog.get_table_definition(
                TableName.from_string(selected_table)
            )

            columns = [col.name for col in table_def.columns]

            df = pd.DataFrame(rows, columns=columns)

            st.subheader("Query Results")

            st.dataframe(df, use_container_width=True)

            # =============================================
            # DOWNLOAD CSV
            # =============================================

            csv = df.to_csv(index=False)

            st.download_button(
                label="Download CSV",
                data=csv,
                file_name="results.csv",
                mime="text/csv"
            )

            # =============================================
            # CHART BUILDER
            # =============================================

            st.subheader("Generate Graph")

            if len(df.columns) >= 2:

                chart_type = st.selectbox(
                    "Chart Type",
                    ["Bar", "Line", "Scatter", "Pie", "Histogram"]
                )

                x_col = st.selectbox(
                    "X Axis",
                    df.columns
                )

                y_col = st.selectbox(
                    "Y Axis",
                    df.columns
                )

                if chart_type == "Bar":
                    fig = px.bar(df, x=x_col, y=y_col)

                elif chart_type == "Line":
                    fig = px.line(df, x=x_col, y=y_col)

                elif chart_type == "Scatter":
                    fig = px.scatter(df, x=x_col, y=y_col)

                elif chart_type == "Pie":
                    fig = px.pie(df, names=x_col, values=y_col)

                elif chart_type == "Histogram":
                    fig = px.histogram(df, x=x_col)

                st.plotly_chart(
                    fig,
                    use_container_width=True
                )

        # =================================================
        # CSV IMPORT
        # =================================================

        st.subheader("Import CSV Into Hyper")

        uploaded_file = st.file_uploader(
            "Upload CSV",
            type=["csv"]
        )

        table_name_input = st.text_input(
            "Target Table Name",
            "ImportedData"
        )

        if uploaded_file is not None:

            csv_df = pd.read_csv(uploaded_file)

            st.write(csv_df.head())

            if st.button("Import CSV to Hyper"):

                columns = []

                for col in csv_df.columns:

                    if pd.api.types.is_numeric_dtype(csv_df[col]):
                        sql_type = SqlType.double()
                    else:
                        sql_type = SqlType.text()

                    columns.append(
                        TableDefinition.Column(col, sql_type)
                    )

                table_def = TableDefinition(
                    table_name=TableName(
                        "Extract",
                        table_name_input
                    ),
                    columns=columns
                )

                try:
                    connection.catalog.create_table(table_def)
                except:
                    pass

                with Inserter(connection, table_def) as inserter:

                    inserter.add_rows(
                        csv_df.values.tolist()
                    )

                    inserter.execute()

                st.success("CSV Imported Successfully")

else:

    st.warning("Database file not found")

# =========================================================
# CLEANUP
# =========================================================

hyper.close()

[rakib06]

# =================================================
# SHOW TABLES
# =================================================

st.subheader("Tables")

from tableauhyperapi import SchemaName

schema = SchemaName("Extract")

table_names = connection.catalog.get_table_names(schema)

table_list = []

for table in table_names:
    table_list.append(str(table))

if len(table_list) == 0:
    st.warning("No tables found in Extract schema")

else:

    st.write(table_list)

    # =============================================
    # SELECT TABLE
    # =============================================

    selected_table = st.selectbox(
        "Select Table",
        table_list
    )

[rakib06]

if st.button("Run Query"):

    rows = connection.execute_list_query(query)

    # ---------------------------------------------
    # Parse table name
    # ---------------------------------------------

    clean_name = selected_table.replace('"', '')

    parts = clean_name.split('.')

    schema_name = parts[0]
    table_name = parts[1]

    # ---------------------------------------------
    # Get schema definition
    # ---------------------------------------------

    table_def = connection.catalog.get_table_definition(
        TableName(schema_name, table_name)
    )

    columns = [col.name for col in table_def.columns]

    # ---------------------------------------------
    # Build dataframe
    # ---------------------------------------------

    df = pd.DataFrame(rows, columns=columns)

    st.subheader("Query Results")

    st.dataframe(df, use_container_width=True)

[rakib06]

# =================================================
# RUN QUERY
# =================================================

if st.button("Run Query"):

    rows = connection.execute_list_query(query)

    # ---------------------------------------------
    # Parse table name
    # ---------------------------------------------

    clean_name = selected_table.replace('"', '')

    parts = clean_name.split('.')

    schema_name = parts[0]
    table_name = parts[1]

    # ---------------------------------------------
    # Get table definition
    # ---------------------------------------------

    table_def = connection.catalog.get_table_definition(
        TableName(schema_name, table_name)
    )

    columns = [col.name for col in table_def.columns]

    # ---------------------------------------------
    # Create dataframe
    # ---------------------------------------------

    df = pd.DataFrame(rows, columns=columns)

    # ---------------------------------------------
    # SAVE DATAFRAME
    # ---------------------------------------------

    st.session_state["df"] = df

# =================================================
# DISPLAY DATAFRAME
# =================================================

if "df" in st.session_state:

    df = st.session_state["df"]

    st.subheader("Query Results")

    st.dataframe(df, use_container_width=True)

    # =============================================
    # DOWNLOAD CSV
    # =============================================

    csv = df.to_csv(index=False)

    st.download_button(
        label="Download CSV",
        data=csv,
        file_name="results.csv",
        mime="text/csv"
    )

    # =============================================
    # CHART BUILDER
    # =============================================

    st.subheader("Generate Graph")

    if len(df.columns) >= 2:

        chart_type = st.selectbox(
            "Chart Type",
            ["Bar", "Line", "Scatter", "Pie", "Histogram"]
        )

        x_col = st.selectbox(
            "X Axis",
            df.columns
        )

        y_col = st.selectbox(
            "Y Axis",
            df.columns
        )

        # -----------------------------------------
        # CREATE CHART
        # -----------------------------------------

        if chart_type == "Bar":
            fig = px.bar(df, x=x_col, y=y_col)

        elif chart_type == "Line":
            fig = px.line(df, x=x_col, y=y_col)

        elif chart_type == "Scatter":
            fig = px.scatter(df, x=x_col, y=y_col)

        elif chart_type == "Pie":
            fig = px.pie(df, names=x_col, values=y_col)

        elif chart_type == "Histogram":
            fig = px.histogram(df, x=x_col)

        # -----------------------------------------
        # SHOW CHART
        # -----------------------------------------

        st.plotly_chart(
            fig,
            use_container_width=True
        )