Create CSV scale list from ArcGIS Pro

__init__.py

# Scale levels from https://developers.arcgis.com/documentation/demos/zoom-calculator/zoomCalculator.html

from collections import OrderedDict
from typing import Literal, TypedDict, NamedTuple


class ScaleItemDict(TypedDict):
    scale: float
    suggestion: str


zoom_scale_lookups = dict[int, ScaleItemDict](
    {
        -1: {
            "scale": 591657527.591555,  # zoom of 0 for Image Tile Layers
            "suggestion": "World",
        },
        0: {
            "scale": 295828763.795777,  # zoom of 0 for Vector Tile Layers
            "suggestion": "World",
        },
        1: {
            "scale": 147914381.897889,
            "suggestion": "World",
        },
        2: {
            "scale": 73957190.948944,
            "suggestion": "Continent",
        },
        3: {
            "scale": 36978595.474472,
            "suggestion": "Continent",
        },
        4: {
            "scale": 18489297.737236,
            "suggestion": "Countries",
        },
        5: {
            "scale": 9244648.868618,
            "suggestion": "Country",
        },
        6: {
            "scale": 4622324.434309,
            "suggestion": "States / Provinces",
        },
        7: {
            "scale": 2311162.217155,
            "suggestion": "Counties",
        },
        8: {
            "scale": 1155581.108577,
            "suggestion": "Counties",
        },
        9: {
            "scale": 577790.554289,
            "suggestion": "County",
        },
        10: {
            "scale": 288895.277144,
            "suggestion": "Metropolitan Area",
        },
        11: {
            "scale": 144447.638572,
            "suggestion": "Cities",
        },
        12: {
            "scale": 72223.819286,
            "suggestion": "City",
        },
        13: {
            "scale": 36111.909643,
            "suggestion": "Town",
        },
        14: {
            "scale": 18055.954822,
            "suggestion": "Neighborhood",
        },
        15: {
            "scale": 9027.977411,
            "suggestion": "Streets",
        },
        16: {
            "scale": 4513.988705,
            "suggestion": "City block",
        },
        17: {
            "scale": 2256.994353,
            "suggestion": "Buildings",
        },
        18: {
            "scale": 1128.497176,
            "suggestion": "Building",
        },
        19: {
            "scale": 564.248588,
            "suggestion": "Houses",
        },
        20: {
            "scale": 282.124294,
            "suggestion": "Houses",
        },
        21: {
            "scale": 141.062147,
            "suggestion": "Houses",
        },
        22: {
            "scale": 70.5310735,  # zoom of 23 for image tile layers
            "suggestion": "House property",
        },
        23: {
            "scale": 35.2655368,  # zoom of 23 for vector tile layers
            "suggestion": "House",
        },
    }
)

# Reverse the order of the scales
zoom_scale_lookups = OrderedDict(sorted(zoom_scale_lookups.items(), reverse=True))


class ScaleSuggestionTuple(NamedTuple):
    scale: float
    suggestion: str


def get_scale_info(layer_type: Literal["Image", "Vector"] | None = None):
    for zoom_level, scale_item in zoom_scale_lookups.items():
        current_scale = scale_item["scale"]
        current_suggestion = scale_item["suggestion"]
        current_image_zoom_level = zoom_level
        current_vector_zoom_level = current_image_zoom_level - 1

        # skip if negative zoom level integer
        if (layer_type == "Vector" and current_vector_zoom_level < 0) or (
            layer_type == "Image" and current_image_zoom_level < 0
        ):
            continue

        if layer_type == "Vector":
            current_suggestion = f"{current_vector_zoom_level} - {current_suggestion}"
        elif layer_type == "Image":
            current_suggestion = f"{current_image_zoom_level} - {current_suggestion}"
        else:
            current_suggestion = f"{current_suggestion} (Image: {current_image_zoom_level} / Vector: {current_vector_zoom_level})"

        yield ScaleSuggestionTuple(current_scale, current_suggestion)

__main__.py

import argparse
import csv
from sys import stdout

from . import get_scale_info


def main():
    arg_parser = argparse.ArgumentParser(
        description="Creates a CSV list of scales for use with ArcGIS Pro"
    )
    arg_parser.add_argument(
        "layer_type", choices=("Image", "Vector"), default=None, nargs="?"
    )
    args = arg_parser.parse_args()

    w = csv.writer(stdout, "excel", lineterminator="\n")

    for t in get_scale_info(args.layer_type):
        w.writerow(t)


if __name__ == "__main__":
    main()