streamlit

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# Copyright (c) Streamlit Inc. (2018-2022) Snowflake Inc. (2022-2024)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#     http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Any, cast
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import numpy as np
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import pandas as pd
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import streamlit as st
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from tests.streamlit import pyspark_mocks
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from tests.streamlit.snowpark_mocks import DataFrame as MockedSnowparkDataFrame
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from tests.streamlit.snowpark_mocks import Table as MockedSnowparkTable
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"""
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### Empty map
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"""
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st.map()
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"""
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### st.map with pyspark.sql.DataFrame
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"""
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st.map(pyspark_mocks.DataFrame(is_map=True))
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"""
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### st.map with unevaluated Snowpark Table
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"""
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st.map(MockedSnowparkTable(is_map=True, num_of_rows=50000))
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"""
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### st.map with unevaluated Snowpark DataFrame
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"""
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st.map(MockedSnowparkDataFrame(is_map=True, num_of_rows=50000))
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"""
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### Simple map
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"""
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# Cast is needed due to mypy not understanding the outcome of dividing
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# an array by a list of numbers.
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np.random.seed(0)
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coords: "np.typing.NDArray[np.float_]" = cast(
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    Any,
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    np.random.randn(1000, 2) / [50, 50],
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) + [37.76, -122.4]
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df = pd.DataFrame(coords, columns=["lat", "lon"])
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st.map(df)
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"""
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### Simple map with zoom
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"""
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st.map(df, zoom=8)
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"""
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### Map with color and size layers
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"""
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df = pd.DataFrame(
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    {
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        "xlat": [38.8762997, 38.8742997, 38.9025842],
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        "xlon": [-77.0037, -77.0057, -77.0556545],
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        "color": ["#f00", "#f0f", "#00f"],
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        "size": [1000, 500, 300],
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    }
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)
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st.map(
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    df,
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    latitude="xlat",
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    longitude="xlon",
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    color="color",
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    size="size",
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)
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