Kyle Barron kylebarron

## pydantic.py
from typing import Generic, TypeVar

import numpy as np
from pydantic.fields import ModelField

JSON_ENCODERS = {
    np.ndarray: lambda arr: arr.tolist()
}

DType = TypeVar('DType')

## image.png

      
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                kylebarron
                / image.png
            
            
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              May 23, 2025 17:57
            
              
                obstore zarr planetary computer example
              
          
## create_async_tiff_graph.py
import altair as alt
import pandas as pd

recv_bytes_per_second_mean = pd.DataFrame(
    {
        "Group": ["rasterio", "async-tiff"],
        "Throughput (bytes/s)": [972102.34, 24319246.71],
    },
)

## convert.py
import geopandas as gpd
import pandas as pd
import pyarrow as pa
import pyarrow.feather as feather
import pyarrow.parquet as pq
import pygeos
import pyogrio

# https://ookla-open-data.s3.us-west-2.amazonaws.com/parquet/performance/type=mobile/year=2019/quarter=1/2019-01-01_performance_mobile_tiles.parquet

## hcpcs_scrape.py
#! /usr/bin/env python3
"""
---------------------------------------------------------------------
Program: hcpcs_scrape.py
Author:  Kyle Barron <barronk@mit.edu>
Created: 2/5/2018
Updated: 2/5/2018
Purpose: Scrape HCPCS codes from the internet
"""

## ibis_lonboard.py
# Old
m = leafmap.Map()

m.add_vector(broad_station_gdf, get_fill_color="blue")
m.add_vector(sts_near_broad_gdf, get_color="red", opacity=0.5)
m.add_vector(streets_gdf, get_color="grey", zoom_to_layer=False, opacity=0.3)
m

# New: simple method, just want to see my data:

## requirements.txt
lonboard==0.1.0-beta.2
geopandas
shapely

## .gitattributes
# GitHub syntax highlighting
pixi.lock linguist-language=YAML

## poetry.lock
[[package]]
name = "affine"
version = "2.3.1"
description = "Matrices describing affine transformation of the plane."
category = "main"
optional = false
python-versions = "*"

[package.extras]
test = ["coveralls", "flake8", "pydocstyle", "pytest (>=4.6)", "pytest-cov"]

## README.md

      
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                kylebarron
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              Last active
              September 4, 2022 10:52
            
              
                Preprocessing for example of ADSB data in deck.gl
              
          
    todo
	from typing import Generic, TypeVar

	import numpy as np
	from pydantic.fields import ModelField

	JSON_ENCODERS = {
	np.ndarray: lambda arr: arr.tolist()
	}

	DType = TypeVar('DType')
	import altair as alt
	import pandas as pd

	recv_bytes_per_second_mean = pd.DataFrame(
	{
	"Group": ["rasterio", "async-tiff"],
	"Throughput (bytes/s)": [972102.34, 24319246.71],
	},
	)
	import geopandas as gpd
	import pandas as pd
	import pyarrow as pa
	import pyarrow.feather as feather
	import pyarrow.parquet as pq
	import pygeos
	import pyogrio

	# https://ookla-open-data.s3.us-west-2.amazonaws.com/parquet/performance/type=mobile/year=2019/quarter=1/2019-01-01_performance_mobile_tiles.parquet
	#! /usr/bin/env python3
	"""
	---------------------------------------------------------------------
	Program: hcpcs_scrape.py
	Author: Kyle Barron <barronk@mit.edu>
	Created: 2/5/2018
	Updated: 2/5/2018
	Purpose: Scrape HCPCS codes from the internet
	"""
	# Old
	m = leafmap.Map()

	m.add_vector(broad_station_gdf, get_fill_color="blue")
	m.add_vector(sts_near_broad_gdf, get_color="red", opacity=0.5)
	m.add_vector(streets_gdf, get_color="grey", zoom_to_layer=False, opacity=0.3)
	m

	# New: simple method, just want to see my data:
	# GitHub syntax highlighting
	pixi.lock linguist-language=YAML
	[[package]]
	name = "affine"
	version = "2.3.1"
	description = "Matrices describing affine transformation of the plane."
	category = "main"
	optional = false
	python-versions = "*"

	[package.extras]
	test = ["coveralls", "flake8", "pydocstyle", "pytest (>=4.6)", "pytest-cov"]