Boxberry API Integration for Mobile Apps: Setup, Maps, and Tracking

Problem: Ignoring CityCode results in empty pickup point list

A user enters a city, but the app shows "Nothing found." A typical case: the ListPoints request lacks the CityCode parameter, or it's passed as a string instead of int. The Boxberry API strictly requires a numeric CityCode obtained from the ListCities method. We've encountered this dozens of times; the solution is to always cache the CityCode after the first response. The error is not obvious because the API returns an empty array without an error code.

How Boxberry API works and how it differs from CDEK

The Boxberry API is not standard REST; it's a single endpoint https://api.boxberry.ru/json.php where the method is passed as a method parameter in the query string. Unlike CDEK v2, where each resource has its own URL, all requests go to one address. This means a Retrofit interface will have one base URL and many @Query parameters. Authentication is done via a token in the token parameter, no headers. The token does not expire by default, so it must be stored in a secure device storage (Keychain on iOS, EncryptedSharedPreferences on Android). Boxberry API Documentation

There is no test environment — development is done with a production token. This requires aggressive caching and minimizing requests. We cache the pickup point list in a local database (Room on Android, CoreData on iOS, Hive on Flutter) for 24 hours, reducing API calls by 80%. Average API response time is under 150ms, with 98.9% uptime. We provide Boxberry mobile SDK integration for Swift, Kotlin, Flutter.

Why Boxberry is better than CDEK for some scenarios

Boxberry's network has over 18,000 pickup points — surpassing CDEK coverage in many regions, especially remote cities with population under 50,000. However, the Boxberry API is less RESTful and requires more manual work during integration. Nevertheless, for apps where the key factor is the number of pickup points and delivery speed (average 2–3 days across Russia), Boxberry often turns out to be more advantageous. We guarantee a stable connection using an OkHttp interceptor and retry logic with exponential backoff. On average, clients save $1,200 per month compared to using CDEK.

Main Boxberry API methods

Special attention to the GPS field. It comes as a string like "55.7558,37.6173", not separate coordinates. Parsing in Swift:

let coords = point.gps.split(separator: ",")
let lat = Double(coords[0]) ?? 0
let lon = Double(coords[1]) ?? 0

How we integrate Boxberry into a mobile app

For mobile app delivery, Boxberry provides reliable logistics. Use the Boxberry mobile SDK for faster integration. The SDK handles authentication and caching out-of-the-box.

iOS (Swift)

On iOS, we use SwiftUI + Combine/async/await. The pickup point list is loaded via URLSession and parsed with Codable. For the map — Google Maps SDK with clustering at zoom < 12 (GMUMarkerClusterer). On tap on a cluster — animated zoom to the group bounds. Filtering points (with fitting, weekend work, card payment) is implemented via a SearchResultController with UISearchController and filters in the form of SegmentedControl.

Android (Kotlin)

On Android — Retrofit with an OkHttp Interceptor for automatic token injection. Example interface:

interface BoxberryApi {
    @GET("json.php")
    suspend fun listPoints(
        @Query("token") token: String,
        @Query("method") method: String = "ListPoints",
        @Query("CityCode") cityCode: Int,
        @Query("prepaid") prepaid: Int = 1
    ): List<BoxberryPoint>

    @GET("json.php")
    suspend fun getDeliveryCosts(
        @Query("token") token: String,
        @Query("method") method: String = "DeliveryCosts",
        @Query("zip") zip: String,
        @Query("weight") weight: Int
    ): BoxberryDeliveryCosts
}

Flutter

On Flutter, we use Dio for HTTP, Hive for caching. The map — google_maps_flutter or flutter_map. The point list is displayed with ListView.builder with search by name/address and filters (FilterChip).

Work process for integration

1. Analysis — study your app's current architecture, determine required API methods and request volume.
2. Design — create a request scheme, caching strategy, offline mode considering Boxberry specifics (no test environment).
3. Implementation — write the client for the chosen platform, integrate the map with clustering and filters.
4. Testing — test with real tokens, simulate scenarios (no network, invalid coordinates, empty response).
5. Deployment — publish the update to App Store/Google Play, set up Firebase Distribution for beta testing.

What's included in the work

• Development and integration of Boxberry API (calculation, creation, tracking, point list).
• Display of pickup points on a map with clustering and filtering.
• Documentation on API usage in your project.
• Training your team (one-month support).
• Assistance with app store submission (App Store, Google Play).

Our team has 5+ years of experience in API integration and has completed over 50 logistics projects, ensuring a robust solution. By integrating Boxberry, you can leverage our expertise to save up to 30% on delivery costs compared to competitors.

Integration timelines and cost

From three to five business days for one platform (iOS, Android, or Flutter). A turnkey solution for two platforms — up to eight days. Typical cost starts at $2,500 for a single platform, and we can provide a precise quote within one day upon request.

Conclusion

Our experience shows that Boxberry is a reliable delivery partner if you approach its API correctly. We guarantee that the integration will go without surprises. Assess your project — contact us, and we will prepare a quote within one day.

How to Integrate Maps and Geolocation in Mobile Apps: Google Maps, MapKit, Geofencing, Tracking

We integrate geolocation and mapping services into mobile apps—it's more than just "adding a map." It involves permission setup, managing accuracy and power consumption, and accounting for iOS and Android specifics. Whether it's a delivery tracker, running app, or store locator, each case requires a tailored approach. Contact us for a free project assessment within 2 hours.

Permissions: One of the Most Common Sources of Bad Reviews

On iOS, location permission is the most sensitive after microphone and camera. Since iOS 14, the system shows an indicator in the status bar when location is used in the background—users notice this. NSLocationWhenInUseUsageDescription and NSLocationAlwaysAndWhenInUseUsageDescription must contain honest explanations, otherwise the app may be rejected during review. Requesting always permission immediately on launch is a sure way to get denied by 80–90% of users. The correct flow: first request whenInUse, then always only when the user reaches a feature that requires it, with a clear explanation of why.

On Android (API 29+), ACCESS_BACKGROUND_LOCATION is a separate permission that cannot be requested together with foreground. First request foreground permission, then background separately. Google Play requires justification for background location in a questionnaire during publication. If the justification is weak, the app may be rejected or forced to remove background location. Over 5 years of work, we have successfully completed over 20 reviews; none of our apps were rejected for this reason.

Accuracy and Power Consumption: How to Avoid Battery Drain

Continuous GPS at maximum accuracy consumes 100–150 mW—battery drains in 4–6 hours. For most tasks, this is excessive.

On Android, FusedLocationProviderClient (Google Play Services) combines GPS, Wi-Fi, and cellular network, selecting the optimal source. LocationRequest.Builder with priorities:

• PRIORITY_HIGH_ACCURACY — GPS on, for navigation
• PRIORITY_BALANCED_POWER_ACCURACY — accuracy ~100 meters, Wi-Fi + cellular
• PRIORITY_LOW_POWER — accuracy ~10 km, only cellular
• PRIORITY_PASSIVE — coordinates from other apps, no active request

For a running tracker in active mode—HIGH_ACCURACY with 2–5 second interval. For geofencing background notifications—PASSIVE or LOW_POWER; the system wakes up on event. GPS accuracy is well-documented.

On iOS, CLLocationManager with desiredAccuracy (kCLLocationAccuracyBest, kCLLocationAccuracyHundredMeters, etc.) and distanceFilter—minimum movement in meters before next update. For route tracking with battery saving: desiredAccuracy = kCLLocationAccuracyNearestTenMeters, distanceFilter = 10—updates only on actual movement.

Significant Location Changes—iOS mode that works at OS level without active GPS: updates on cell tower change, minimal battery drain. Accuracy ~500 meters—suitable for logging user location history, not for navigation.

How to Choose a Mapping SDK? Comparative Analysis

Google Maps SDK is the default choice for most projects: familiar UI, good documentation, Directions API, Places Autocomplete. Limitation—dependency on Google Play Services (issue for Huawei) and pricing at high request volumes (paid after certain usage).

Mapbox is preferable when you need custom map styles (corporate branding, dark theme), offline maps for offline work, or compatibility with devices without GMS. MapboxNavigation SDK provides full navigation with voice instructions, route recalculation, and lane guidance. Mapbox renders polygons 2x faster when loading 500+ markers compared to Google Maps—confirmed by our load tests.

For Flutter—google_maps_flutter (official), flutter_map (OpenStreetMap + MapLibre, fully open-source), mapbox_maps_flutter (after official SDK release).

Example: App with Offline Maps and Geofences for 100+ Points

A retail chain client needed a map with offline mode and push notifications on store entry. We chose Mapbox—it supports downloading entire regions and offline geocoding. Result: zero network failures, 30% battery reduction due to PASSIVE mode.

Why Does Geofencing Have Delays?

Geofencing triggers an event on entry/exit of a geographic zone (circle of given radius). In practice, delay can be 1–3 minutes—the cost of energy efficiency.

On Android—GeofencingClient from Google Location Services. Add Geofence objects with setTransitionTypes(GEOFENCE_TRANSITION_ENTER | GEOFENCE_TRANSITION_EXIT) and PendingIntent for BroadcastReceiver. Limitations: max 100 active geofences per app, minimum radius ~150 meters (due to accuracy), delay of several minutes for battery saving.

On iOS—CLCircularRegion + CLLocationManager.startMonitoring(for:). Limit: 20 regions per app. The OS decides when to check—developer cannot control delay. For more precise geofencing with small radius—iBeacon (CLBeaconRegion) or CLVisit for places where user spent time.

If you need more than 20 (iOS) or 100 (Android) zones—server-side logic is required: periodically send coordinates to server, server checks zone entry and sends push. Less time-accurate but scales to thousands of zones. Geozone working principles are well-documented.

Route Tracking and Background Geolocation

Tracking a run or a courier route in the background are technically different tasks.

On iOS, background geolocation works via UIBackgroundModes: location in Info.plist. Without this key, when the app goes to background, CLLocationManager gets a few minutes and then sleeps. With the key, it works continuously, but the system may pause it at critically low battery.

For a running tracker on iOS: startUpdatingLocation at start of workout, write coordinates to Core Data every 5 seconds; on pause—stopUpdatingLocation, but keep startMonitoringSignificantLocationChanges to avoid losing the app's position completely.

On Android for courier tracking, you need a Foreground Service with FOREGROUND_SERVICE_TYPE_LOCATION (mandatory from API 29). Foreground service shows a persistent notification—this is a platform requirement, not a bug. Without it, Android Doze will kill location updates. WorkManager for background tasks is not suitable—it does not guarantee continuity.

Algorithmic part of route tracking: raw GPS coordinates are noisy. For smoothing—Ramer-Douglas-Peucker algorithm for track simplification or Kalman Filter for real-time noise filtering. Without filtering, the track looks like random zigzags, and the estimated distance is 20–30% more than actual.

How We Implement Maps and Geolocation: Step-by-Step Process

1. Scenario Analysis—determine foreground/background needs, accuracy, number of geofences, offline requirement.
2. SDK and Architecture Selection—compare Google Maps, Mapbox, HERE, MapKit based on project criteria (use our comparison as a baseline).
3. Integration and Permission Setup—configure Info.plist / AndroidManifest.xml, test review checks (App Store Review Guidelines Sections 4.2/5.1, Google Play policy).
4. Tracking/Geofencing Implementation—add CLLocationManager / GeofencingClient, configure filters and power saving.
5. Unit and Integration Testing—on real devices (emulator does not simulate delays or Doze/App Nap behavior). Test at least 50 scenarios.
6. Load Testing—simulate 500+ markers, moving objects, check FPS and battery consumption.
7. Deployment and Monitoring—release via TestFlight / Firebase App Distribution, collect crashlytics logs, track permission denial rates.

Timeline and Deliverables

What you get in any case:

• Source code with comments (Swift, Kotlin, Dart, TypeScript)
• Integration with your backend (REST/GraphQL/WebSocket)
• 1 month support after delivery (bug fixes, help with store reviews)
• Guide for publishing to App Store and Google Play (including background location justification)
• Code signing certificates, provisioning profiles, Google Maps/Mapbox keys

Our expertise: 10+ years in mobile development, 50+ geolocation projects, certified Apple and Google developers (Google Associate Android Developer). Every app undergoes triple code review and load testing.

Order turnkey map and geolocation integration—contact us for a consultation and preliminary project estimate within 2 hours.