Intro_to_Fused: removing_cache_max_age_in_chart (#1966)

Intro_to_Fused: removing_cache_max_age_in_chart

Made in [Fused Workbench](https://www.fused.io/workbench)

Co-authored-by: max@fused.io <max@fused.io>

Author: fused-io-unstable[bot]

public/Intro_to_Fused/collection.json

@@ -63,7 +63,7 @@
             "nodeTemplateAlignment": "left",
             "nodeTemplateScaleFactor": 2
           },
-          "code": "A UDF can call another\n\nTo chart soem data for example",
+          "code": "A UDF can call another\n\nTo chart some data for example",
           "headers": []
         }
       }

public/Intro_to_Fused/note_920a6a1e_bcdb_4610_88c4_5d05c25dae56_57/meta.json

@@ -1,3 +1,3 @@
 A UDF can call another
 
-To chart soem data for example
+To chart some data for example

public/Intro_to_Fused/note_920a6a1e_bcdb_4610_88c4_5d05c25dae56_57/note_920a6a1e_bcdb_4610_88c4_5d05c25dae56_57.py

@@ -57,7 +57,7 @@
             },
             "fused:udfType": "auto"
           },
-          "code": "@fused.udf(cache_max_age=0)\ndef udf():\n    import altair as alt\n    import pandas as pd\n\n    # This loads the previous UDF and calls it\n    parent_udf = fused.load('sf_airbnb_listings')\n    df = parent_udf(cache_max_age=0)\n    print(df.T)\n\n    plot_df = df.dropna(subset=['price_in_dollar', 'number_of_reviews'])\n    plot_df = plot_df[plot_df['price_in_dollar'] <= 1000]\n    plot_df = plot_df[plot_df['number_of_reviews'] > 0]\n\n    plot_df = plot_df.sample(n=min(4999, len(plot_df)), random_state=42)\n\n    chart = alt.Chart(plot_df).mark_circle(size=200, opacity=0.9).encode(\n        x=alt.X('number_of_reviews:Q', title='Number of Reviews'),\n        y=alt.Y('price_in_dollar:Q', title='Price ($)'),\n        color=alt.Color('room_type:N', title='Room Type'),\n        tooltip=['name:N', 'neighbourhood_cleansed:N', 'room_type:N', 'price_in_dollar:Q', 'number_of_reviews:Q']\n    ).properties(\n        title='SF Airbnb: Price vs Number of Reviews',\n        width='container',\n        height=700,\n        background='white'\n    ).configure_title(\n        fontSize=28,\n        fontWeight='bold'\n    ).configure_axis(\n        titleFontSize=18,\n        labelFontSize=14\n    ).configure_legend(\n        titleFontSize=16,\n        labelFontSize=14\n    ).to_html(embed_options={\"renderer\": \"svg\"})\n\n    return chart",
+          "code": "@fused.udf\ndef udf():\n    import altair as alt\n    import pandas as pd\n\n    # This loads the previous UDF and calls it\n    parent_udf = fused.load('sf_airbnb_listings')\n    df = parent_udf()\n    print(df.T)\n\n    plot_df = df.dropna(subset=['price_in_dollar', 'number_of_reviews'])\n    plot_df = plot_df[plot_df['price_in_dollar'] <= 1000]\n    plot_df = plot_df[plot_df['number_of_reviews'] > 0]\n\n    plot_df = plot_df.sample(n=min(4999, len(plot_df)), random_state=42)\n\n    chart = alt.Chart(plot_df).mark_circle(size=200, opacity=0.9).encode(\n        x=alt.X('number_of_reviews:Q', title='Number of Reviews'),\n        y=alt.Y('price_in_dollar:Q', title='Price ($)'),\n        color=alt.Color('room_type:N', title='Room Type'),\n        tooltip=['name:N', 'neighbourhood_cleansed:N', 'room_type:N', 'price_in_dollar:Q', 'number_of_reviews:Q']\n    ).properties(\n        title='SF Airbnb: Price vs Number of Reviews',\n        width='container',\n        height=700,\n        background='white'\n    ).configure_title(\n        fontSize=28,\n        fontWeight='bold'\n    ).configure_axis(\n        titleFontSize=18,\n        labelFontSize=14\n    ).configure_legend(\n        titleFontSize=16,\n        labelFontSize=14\n    ).to_html(embed_options={\"renderer\": \"svg\"})\n\n    return chart",
           "headers": []
         }
       }

public/Intro_to_Fused/sf_airbnb_price_chart/meta.json

@@ -1,11 +1,11 @@
-@fused.udf(cache_max_age=0)
+@fused.udf
 def udf():
     import altair as alt
     import pandas as pd
 
     # This loads the previous UDF and calls it
     parent_udf = fused.load('sf_airbnb_listings')
-    df = parent_udf(cache_max_age=0)
+    df = parent_udf()
     print(df.T)
 
     plot_df = df.dropna(subset=['price_in_dollar', 'number_of_reviews'])