.gitignore

@@ -2,4 +2,3 @@ checkpoints*
 plots*
 *.csv
 output/
-.requirements_installed

Makefile

@@ -2,7 +2,7 @@ all: install data train eval
 
 city_distances_full.csv: check generate_data.py
 	@echo "Generating distance data..."
-	@bash -c 'time python generate_data.py -w 8 -c US -s 10000'
+	@bash -c 'time python generate_data.py'
 
 data: city_distances_full.csv
 
@@ -18,7 +18,7 @@ lint:
 	@echo "Auto-linting files and performing final style checks..."
 	@isort --profile=black .
 	@black .
-	@flake8 --max-line-length=88 --ignore E203 .
+	@flake8 --max-line-length=88 .
 
 check: lint
 	@echo "Checking for unstaged or untracked changes..."
@@ -34,10 +34,7 @@ compress: plots/progress_136013_sm.png
 plots/progress_136013_sm.png: plots/progress_136013.png
 	@convert -resize 33% plots/progress_136013.png plots/progress_136013_sm.png
 
-install: .requirements_installed
+install:
-
-.requirements_installed: requirements.txt
 	pip install -r requirements.txt
-	@echo "installed requirements" > .requirements_installed
 
 .PHONY: data train eval lint check clean all

generate_data.py

@@ -1,4 +1,3 @@
-import argparse
 import concurrent.futures
 import csv
 import itertools
@@ -8,41 +7,15 @@ from functools import lru_cache
 import geonamescache
 import numpy as np
 from geopy.distance import geodesic
-from tqdm import tqdm
 
 MAX_DISTANCE = 20_037.5
 
-# Add argparse
-parser = argparse.ArgumentParser()
-parser.add_argument(
-    "-c", "--country", help="Specify the country code", type=str, default="US"
-)
-parser.add_argument(
-    "-w", "--workers", help="Specify the number of workers", type=int, default=1
-)
-parser.add_argument(
-    "-s",
-    "--chunk-size",
-    help="Specify chunk size for batching calculations",
-    type=int,
-    default=1000,
-)
-parser.add_argument(
-    "-o",
-    "--output-file",
-    help="Specify the name of the output file (file.csv)",
-    type=str,
-    default="city_distances_full.csv",
-)
-args = parser.parse_args()
-
-
 gc = geonamescache.GeonamesCache()
 cities = gc.get_cities()
 us_cities = {
     k: c
     for k, c in cities.items()
-    if (c.get("countrycode") == args.country)  # & (c.get("population", 0) > 5e4)
+    if (c.get("countrycode") == "US")  # & (c.get("population", 0) > 5e4)
 }
 
 
@@ -65,9 +38,11 @@ def get_coordinates(city_name, country_code="US"):
         or None if the city is not found.
     """
     search_results = gc.search_cities(city_name, case_sensitive=True)
-    search_results = [
+    search_results = {
-        d for d in search_results if (d.get("countrycode") == country_code)
+        k: c
-    ]
+        for k, c in search_results.items()
+        if (c.get("countrycode") == country_code)
+    }
 
     if not search_results:
         return None
@@ -116,39 +91,29 @@ def main():
     cities = list(us_cities.values())
     print(f"Num cities: {len(cities)}")
     city_combinations = list(itertools.combinations(cities, 2))
-    chunk_size = args.chunk_size
-    num_chunks = len(city_combinations) // chunk_size + 1
-    output_file = args.output_file
 
-    with open(output_file, "w", newline="") as csvfile:
+    with open("city_distances_full.csv", "w", newline="") as csvfile:
         fieldnames = ["city_from", "city_to", "distance"]
         writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
         writer.writeheader()
 
         try:
-            executor = concurrent.futures.ProcessPoolExecutor(max_workers=args.workers)
+            executor = concurrent.futures.ProcessPoolExecutor(max_workers=8)
-            for i in tqdm(
+            # results = executor.map(calculate_distance, city_combinations)
-                range(num_chunks),
+            futures = {
-                total=num_chunks,
+                executor.submit(calculate_distance, pair): pair
-                desc="Processing chunks",
+                for pair in city_combinations
-                ncols=100,
+            }
-                bar_format="{l_bar}{bar:30}{r_bar}",
+            for future in as_completed(futures):
-            ):
+                city_from, city_to, distance = future.result()
-                chunk = city_combinations[(i * chunk_size) : (i + 1) * chunk_size]
+                if distance is not None:
-                futures = {
+                    writer.writerow(
-                    executor.submit(calculate_distance, pair): pair for pair in chunk
+                        {
-                }
+                            "city_from": city_from,
-                for future in as_completed(futures):
+                            "city_to": city_to,
-                    city_from, city_to, distance = future.result()
+                            "distance": distance,
-                    if distance is not None:
+                        }
-                        writer.writerow(
+                    )
-                            {
-                                "city_from": city_from,
-                                "city_to": city_to,
-                                "distance": distance,
-                            }
-                        )
-                        csvfile.flush()  # write to disk immediately
         except KeyboardInterrupt:
             print("Interrupted. Terminating processes...")
             executor.shutdown(wait=False)