streetlevel

streetlevel is a Python library designed to download panoramas and metadata from various street-level imagery providers by interfacing with their internal APIs.

Key Coordinate Standards:

• The library uses latitude/longitude order.
• All coordinates are in the WGS84 coordinate system unless explicitly stated otherwise in provider-specific documentation.

The streetlevel.ja module uses specific data classes to represent panorama information:

• JaPanorama: The primary object representing a panorama, containing metadata like ID, coordinates, and heading.
• Address: Contains address-related information for the panorama location.
• CaptureDate: Contains the date information for when the panorama was captured.

You can install streetlevel via PyPI using pip.

macOS Users: You may need to install additional system dependencies using Homebrew to ensure all features work correctly:

brew install gettext
brew install inih

pip install streetlevel

To download the closest Google Street View panorama to a specific latitude and longitude using synchronous calls, use streetview.find_panorama followed by streetview.download_panorama.

This method uses requests internally.

from streetlevel import streetview

# Find the closest panorama to the coordinates
pano = streetview.find_panorama(46.883958, 12.169002)

# Download the panorama to a file named after its ID
streetview.download_panorama(pano, f"{pano.id}.jpg")

For asynchronous workflows, use the _async variants of the functions. These require an aiohttp.ClientSession to be passed as an argument.

This method uses aiohttp internally.

from streetlevel import streetview
from aiohttp import ClientSession

async with ClientSession() as session:
    # Find the closest panorama asynchronously
    pano = await streetview.find_panorama_async(46.883958, 12.169002, session)
    
    # Download the panorama asynchronously
    await streetview.download_panorama_async(pano, f"{pano.id}.jpg", session)

You can find available panoramas in a specific area using tile coordinates or latitude/longitude. The library provides both synchronous and asynchronous methods for these lookups. The returned CoverageTile object contains a list of LookaroundPanorama objects.

from streetlevel import lookaround

# By tile coordinates
tile = lookaround.get_coverage_tile(109775, 56716)

# By latitude and longitude
tile = lookaround.get_coverage_tile_by_latlon(23.53239040648735, 121.5068719584602)

first = tile.panos[0]
print(f"ID: {first.id}\tLatitude: {first.lat}\tLongitude: {first.lon}")

Use find_panoramas to search for available Kakao Road View panoramas near a specific latitude and longitude. For asynchronous workflows, use find_panoramas_async which requires an aiohttp.ClientSession.

from streetlevel import kakao

# Synchronous
panos = kakao.find_panoramas(37.4481486, 126.4509719)
print(panos[0].lat, panos[0].lon)
print(panos[0].id)
print(panos[0].date)

# Asynchronous
from aiohttp import ClientSession

async with ClientSession() as session:
    panos = await kakao.find_panoramas_async(37.4481486, 126.4509719, session)
    print(panos[0].lat, panos[0].lon)
    print(panos[0].id)
    print(panos[0].date)

Use find_panorama to locate a Yandex panorama near specific latitude and longitude coordinates. For asynchronous workflows, use find_panorama_async which requires an aiohttp.ClientSession.

from streetlevel import yandex

# Synchronous
pano = yandex.find_panorama(43.249064, 76.941999)
print(pano.lat, pano.lon)
print(pano.id)
print(pano.date)

# Asynchronous
from aiohttp import ClientSession
async with ClientSession() as session:
    pano = await yandex.find_panorama_async(43.249064, 76.941999, session)
    print(pano.lat, pano.lon)
    print(pano.id)
    print(pano.date)

If you already have a panorama ID, you can retrieve the panorama object directly using find_panorama_by_id (synchronous) or find_panorama_by_id_async (asynchronous). The asynchronous version requires an aiohttp.ClientSession.

from streetlevel import streetview
from aiohttp import ClientSession

# Synchronous
# Note: find_panorama_by_id is documented as async in the source, use await if applicable
pano = await streetview.find_panorama_by_id("Py5vaKsLWJG16XyZosdYBQ")

# Asynchronous
async with ClientSession() as session:
    pano = await streetview.find_panorama_by_id_async("Py5vaKsLWJG16XyZosdYBQ", session)
    print(pano.id)

Once you have a YandexPanorama object, you can download the image to a file. Use download_panorama for synchronous operations or download_panorama_async for asynchronous operations (which requires an aiohttp.ClientSession).

from streetlevel import yandex
from aiohttp import ClientSession

# Synchronous download
pano = yandex.find_panorama_by_id("1532719828_788624743_23_1678861237")
yandex.download_panorama(pano, f"{pano.id}.jpg")

# Asynchronous download
async with ClientSession() as session:
    pano = await yandex.find_panorama_by_id_async("1532719828_788624743_23_1678861237", session)
    await yandex.download_panorama_async(pano, f"{pano.id}.jpg", session)