yharby

Keybase proof

I hereby claim:

• I am youssef-harby on github.
• I am yharby (https://keybase.io/yharby) on keybase.
• I have a public key ASBmkyd87Ju7hwN_Uej1lBn8r2SbYZsl12bXghbTDcxPNwo

To claim this, I am signing this object:

yharby

import csv
import re


def extract_lat_long(csv_file, url_column):
    pattern = r".+!3d(-?\d+\.\d+)!4d(-?\d+\.\d+).+"
    data = []

    # Read the CSV file and extract latitude and longitude values
    with open(csv_file, 'r') as f:

yharby

import duckdb

con = duckdb.connect('./duckdb.duckdb')
data = """
SET memory_limit = '32GB';
SET threads TO 16;
SET enable_progress_bar = true;
SET enable_progress_bar_print = true;
INSTALL httpfs;
INSTALL spatial;

yharby

# dataset ref : https://www.kaggle.com/datasets/max-mind/world-cities-database/code
# pip install duckdb

import duckdb

con = duckdb.connect()

data = """
-- Environment setup
SET enable_progress_bar = true;

yharby

import httpx
import datetime
import hashlib
import hmac

# AWS credentials
access_key = "secret"
secret_key = "secret"
region = "eu-central-1"  # e.g. 'us-west-1'
bucket = "bucket-name"

yharby

import pyarrow as pa
import pyarrow.parquet as pq
from pathlib import Path
import json
import pandas as pd


def process_parquet_file(parquet_path):
    # Read the Parquet file into a PyArrow Table
    table = pq.read_table(parquet_path)

yharby

Overture Maps Data Downloader with Optional GeoJSON Clipping

This Python script downloads geospatial data from Overture Maps, based on user-defined themes and data types (e.g., buildings, transportation). The script can download specific data within a given bounding box (bbox) and export it in GeoParquet or GeoPackage format.

Features:

Allows downloading multiple themes/types (e.g., buildings, transportation) using the overturemaps Python library.
Bounding box (bbox) filtering to limit data to a specific geographic extent.
Optionally clips geometries to the exact boundaries of a GeoJSON file, if provided.

Supports output in GeoParquet or GeoPackage formats.

yharby

__doc__ = """
# Overview

This example shows how to open High Resolution Rapid Refresh (HRRR) meteorology
"surfaces." These surfaces are slices in vertical space to create single level
maps of variables like temperature, wind speed components, pressure, etc. Each
surface is opened using the Zarr archive described in Amazon's opendata registry
described at https://registry.opendata.aws/noaa-hrrr-pds/.

# Examples