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JohnMountJohnMount
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update example
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‎examples/weather/run_weather_reports_3.py

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# python run_weather_reports_2.py
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from wvpy.jtools import JTask, run_pool
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if __name__ == '__main__':
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state_codes = [
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"CA",
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"TX",
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"KS",
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]
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tasks = [
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JTask(
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sheet_name="weather_example_3.py",
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sheet_vars={"state_code": state_code},
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output_suffix=f"_{state_code}",
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)
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for state_code in state_codes
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]
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run_pool(tasks, use_Jupyter=False)

‎examples/weather/weather_example_0.ipynb

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@@ -34,6 +34,19 @@
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"from plotnine import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# configure\n",
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"html_render = True\n",
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"\n",
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"def present(txt: str):\n",
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" display(Markdown(txt))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
@@ -67,9 +80,9 @@
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"outputs": [],
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"source": [
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"# format some result info\n",
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"display(Markdown(f\"\"\"\n",
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"present(f\"\"\"\n",
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"[weather.gov](https://www.weather.gov/documentation/services-web-api) alerts for {state_code} retrieved at {time_stamp_str}.\n",
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"\"\"\"))"
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"\"\"\")"
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]
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},
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{
@@ -94,7 +107,7 @@
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"else:\n",
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" display_df = pd.DataFrame({col: [None] for col in display_cols})\n",
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"\n",
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"display_df"
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"present(display_df.to_markdown())"
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]
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},
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{
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"outputs": [],
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"source": [
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"# plot\n",
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"if sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0:\n",
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"if html_render and (sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0):\n",
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" with warnings.catch_warnings():\n",
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" warnings.simplefilter(\"ignore\")\n",
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" print(\n",
@@ -113,7 +126,7 @@
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" mapping=aes(x=\"properties.severity\"),\n",
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" )\n",
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" + geom_histogram()\n",
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" + ggtitle(f\"Weather severity distributiojn for {state_code}, retrieved at {time_stamp_str}\")\n",
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" + ggtitle(f\"Weather severity distribution for {state_code}, retrieved at {time_stamp_str}\")\n",
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" )"
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]
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},

‎examples/weather/weather_example_1.ipynb

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@@ -81,6 +81,19 @@
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"from plotnine import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# configure\n",
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"html_render = True\n",
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"\n",
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"def present(txt: str):\n",
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" display(Markdown(txt))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"outputs": [],
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"source": [
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"# format some result info\n",
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"display(Markdown(f\"\"\"\n",
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"present(f\"\"\"\n",
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"[weather.gov](https://www.weather.gov/documentation/services-web-api) alerts for {state_code} retrieved at {time_stamp_str}.\n",
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"\"\"\"))"
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"\"\"\")"
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]
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},
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{
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"else:\n",
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" display_df = pd.DataFrame({col: [None] for col in display_cols})\n",
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"\n",
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"display_df"
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"present(display_df.to_markdown())"
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]
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},
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{
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"outputs": [],
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"source": [
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"# plot\n",
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"if sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0:\n",
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"if html_render and (sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0):\n",
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" with warnings.catch_warnings():\n",
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" warnings.simplefilter(\"ignore\")\n",
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" print(\n",
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" mapping=aes(x=\"properties.severity\"),\n",
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" )\n",
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" + geom_histogram()\n",
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" + ggtitle(f\"Weather severity distributiojn for {state_code}, retrieved at {time_stamp_str}\")\n",
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" + ggtitle(f\"Weather severity distribution for {state_code}, retrieved at {time_stamp_str}\")\n",
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" )"
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]
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},

‎examples/weather/weather_example_2.ipynb

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"from plotnine import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# configure\n",
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"html_render = True\n",
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"\n",
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"def present(txt: str):\n",
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" display(Markdown(txt))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"outputs": [],
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"source": [
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"# format some result info\n",
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"display(Markdown(f\"\"\"\n",
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"present(f\"\"\"\n",
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"[weather.gov](https://www.weather.gov/documentation/services-web-api) alerts for {state_code} retrieved at {time_stamp_str}.\n",
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"\"\"\"))"
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"\"\"\")"
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]
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},
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{
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"else:\n",
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" display_df = pd.DataFrame({col: [None] for col in display_cols})\n",
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"\n",
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"display_df"
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"present(display_df.to_markdown())"
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]
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},
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{
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"outputs": [],
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"source": [
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"# plot\n",
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"if sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0:\n",
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"if html_render and (sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0):\n",
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" with warnings.catch_warnings():\n",
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" warnings.simplefilter(\"ignore\")\n",
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" print(\n",
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" mapping=aes(x=\"properties.severity\"),\n",
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" )\n",
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" + geom_histogram()\n",
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" + ggtitle(f\"Weather severity distributiojn for {state_code}, retrieved at {time_stamp_str}\")\n",
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" + ggtitle(f\"Weather severity distribution for {state_code}, retrieved at {time_stamp_str}\")\n",
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" )"
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]
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},

‎examples/weather/weather_example_3.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Basic weather API example using [weather.gov](https://www.weather.gov/documentation/services-web-api)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from wvpy.jtools import declare_task_variables"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# set some variables to default values we are willing to override\n",
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"# we do this with the with context manager so that our Jupyter or IDE thinks these variables are defined in our environment\n",
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"# this defines both the set of names we allow overriding of and default values so we can debug in and IDE\n",
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"with declare_task_variables(globals()):\n",
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" # set what state we are querying for\n",
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" state_code = 'CA'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# import our packages\n",
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"import warnings\n",
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"import datetime\n",
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"import requests\n",
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"import pandas as pd\n",
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"from IPython.display import display, Markdown\n",
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"from plotnine import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# configure\n",
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"html_render = False\n",
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"\n",
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"def present(txt: str):\n",
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" print(txt)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# do the query\n",
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"response = requests.get(f\"https://api.weather.gov/alerts/active?area={state_code}\")\n",
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"# get JSON response\n",
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"json_data = response.json()\n",
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"# convert to data frame\n",
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"df = pd.json_normalize(json_data[\"features\"])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# get local query time\n",
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"now = datetime.datetime.now()\n",
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"tz = now.astimezone().tzinfo\n",
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"time_stamp_str = now.strftime('%Y-%m-%d %H:%M:%S ') + str(tz)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# format some result info\n",
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"present(f\"\"\"\n",
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"[weather.gov](https://www.weather.gov/documentation/services-web-api) alerts for {state_code} retrieved at {time_stamp_str}.\n",
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"\"\"\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# show an excerpt of the returned data frame\n",
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"display_cols = [\n",
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" \"properties.parameters.NWSheadline\",\n",
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" 'properties.areaDesc',\n",
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" 'properties.effective',\n",
112+
" 'properties.severity',\n",
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" 'properties.certainty',\n",
114+
" 'properties.event',\n",
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"]\n",
116+
"if df.shape[0] > 0:\n",
117+
" display_df = df.loc[\n",
118+
" pd.isnull(df[\"properties.parameters.NWSheadline\"]) == False,\n",
119+
" display_cols].reset_index(drop=True, inplace=False)\n",
120+
"else:\n",
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" display_df = pd.DataFrame({col: [None] for col in display_cols})\n",
122+
"\n",
123+
"present(display_df.to_markdown())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# plot\n",
133+
"if html_render and (sum(pd.isnull(display_df[\"properties.severity\"]) == False) > 0):\n",
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" with warnings.catch_warnings():\n",
135+
" warnings.simplefilter(\"ignore\")\n",
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" print(\n",
137+
" ggplot(\n",
138+
" data=display_df,\n",
139+
" mapping=aes(x=\"properties.severity\"),\n",
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" )\n",
141+
" + geom_histogram()\n",
142+
" + ggtitle(f\"Weather severity distribution for {state_code}, retrieved at {time_stamp_str}\")\n",
143+
" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# mark provenance\n",
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"display_df['QUERY_STATE_CODE'] = state_code\n",
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"display_df['QUERY_TIME_STAMP'] = time_stamp_str"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# save to CSV file (could also write to database)\n",
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"display_df.to_csv(\n",
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" f\"{state_code}_weather.csv\",\n",
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" index=False,\n",
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")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "wvpy_dev_env",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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