streetworks

An open Python SDK for street works and roadworks data — the UK's registers, Europe's national roadworks feeds, and the US WZDx standard, behind one consistent, typed, well-tested client.

We do this not because it is easy, but because it is hard.

from streetworks.streetmanager import StreetManagerClient, Environment

with StreetManagerClient("api-user@example.com", password, environment=Environment.SANDBOX) as sm:
    sm.authenticate()                                  # verify credentials
    submitted = sm.reporting.permits(status="submitted")

Shared across all modules: automatic retries with exponential backoff and jitter, Retry-After-aware 429 handling, a single exception hierarchy, and both sync and async clients built on httpx.

What this is (and isn't)

It is a typed client library: it handles authentication, token lifecycles, retries, rate limiting, pagination, and request/response plumbing for each of these APIs, so you call Python methods instead of hand-rolling HTTP. Auth and connectivity are verified against the real systems (see Status below).

It isn't a replacement for the APIs' own documentation. You still bring your own credentials (issued by the service operators, not by this SDK) and you still need each API's domain concepts — what a permit payload contains, what makes a valid USRN filter, which DataVIA layer holds which data. The SDK gets you connected and typed; the linked docs tell you what to send.

Status

Early alpha. Authentication and read/consume access are verified against the real systems for all providers except one, noted below: Street Manager (SANDBOX), Geoplace DataVIA (live — including a real feature query), D-TRO (production token + events search), the Open Data SNS parsing/verification pipeline, SRWR Open Data (parsed against real published daily and monthly extracts), OS Open USRN (Downloads API + GeoPackage reader), UK Police (live safety_signal() and category queries against data.police.uk), WZDx (parsed against 12 live agency feeds spanning v3.1–v4.2), Digitraffic/ Finland, IRCA/Iceland, Bison Futé/France, DGT/Spain, Autobahn GmbH/Germany, and the German states Hamburg, Brandenburg and Saxony (all parsed against real live feeds).

Autobahn GmbH's licence is unconfirmed - checked four independent sources (see the Autobahn GmbH section below for what was checked) and none state reuse/redistribution terms. Shipped anyway, flagged deliberately rather than silently assumed open - confirm your own rights before redistributing this data.

The one unverified provider is Norway (streetworks.datex2.vegvesen): implemented to Statens vegvesen's published specs and covered by mocked tests, but never run against real Norwegian data — the authenticated pull is blocked pending credentials. It ships as a scaffold and is excluded from the verified-providers claim above; see the module docstring for precisely what's confirmed vs. still open. If you have Statens vegvesen API credentials, running the smoke test against it and reporting back would be a genuinely valuable contribution.

Not yet exercised against live systems — implemented to the published specs and covered by mocked tests: the write/publish paths (Street Manager work submission and assessment; D-TRO create/update and provisions). These are publisher-scoped and deliberately excluded from the read-only smoke test.

Known reconciliation items: D-TRO v4.0.0 schema models to follow when it lands (production cut-over expected mid-2026; v3.5.1 models ship now); the streetworks.exceptions API and client method surface may change before 1.0. See docs/INTEGRATION.md for how to verify against the real systems yourself. First-contact reports welcome.

Install

pip install streetworks            # core
pip install "streetworks[sns]"     # + SNS signature verification (cryptography)

Requires Python 3.10+.

Quickstart

The fastest way to see everything working: copy the credential template, fill in what you have, and run the one-file tour — it logs in to each configured provider and retrieves a little real data (read-only). Providers you leave blank are skipped, and SRWR / OS Open USRN need no credentials at all.

cp .env.example .env      # then edit .env
python examples/quickstart.py

For connectivity checks without data retrieval, use the smoke test instead: python scripts/smoke_test.py.

Prerequisites: credentials

Credentials are issued by the service operators. You only need the ones for the service(s) you'll use. Keep them in environment variables or a secret manager — never in code.

Credentials are per-environment — sandbox/integration credentials do not work against production, and vice versa.

Verify your setup

Before writing any code, confirm your credentials and connectivity with the included smoke test. It targets the test environments by default, is read-only, and skips any service you haven't configured:

SM_EMAIL='api-user@example.com' SM_PASSWORD='...' python scripts/smoke_test.py

================================================================
streetworks connectivity smoke test
TARGET  Street Manager: sandbox
All checks are READ-ONLY.
================================================================

  [PASS] Street Manager - authenticated (sandbox/v6), organisation 1355
  ...

A FAIL prints the exact exception, so a wrong credential or environment is obvious immediately. See docs/INTEGRATION.md for the full variable list and how to (deliberately) target production.

Street Manager

Authentication, token caching, and refresh (via the Party API, with automatic fall-back to re-authentication) are handled for you — following the DfT integration guidance: one token, reused, never re-authenticating per call.

from streetworks.streetmanager import StreetManagerClient, Environment, ApiVersion

with StreetManagerClient(
    "api-user@example.com",
    "password",                      # store securely, e.g. environment variable
    environment=Environment.SANDBOX, # or Environment.PRODUCTION
    version=ApiVersion.V6,           # or ApiVersion.V7 / ApiVersion.LATEST
) as sm:
    # Typed convenience methods for common workflows...
    work = sm.work.get_work("TSR1591199404915")
    submitted = sm.reporting.permits(status="submitted")

    # Or let the SDK walk every page for you:
    for permit in sm.reporting.iter_permits(status="submitted"):
        ...
    sm.work.assess_permit("TSR1591199404915", "TSR1591199404915-01",
                          {"assessment_status": "granted", ...})

    # ...and a generic escape hatch for every endpoint we haven't wrapped yet:
    s58 = sm.work.post("section-58s", json={...})
    updates = sm.event.works_updates()

Async is a mirror image:

from streetworks.streetmanager import AsyncStreetManagerClient

async with AsyncStreetManagerClient("api-user@example.com", "password") as sm:
    permits = await sm.reporting.permits(status="submitted")

Environments. Environment.SANDBOX and Environment.PRODUCTION are isolated systems with separate credentials. Develop and test against SANDBOX; only point at PRODUCTION once your workflows are proven. The smoke test and integration suite refuse to touch production without an explicit opt-in, so a stray setting can't send you at live data by accident.

Typed models

Pydantic v2 models generated from the official DfT swagger specifications live under streetworks.streetmanager.models.<version> and validate any client payload:

from streetworks.streetmanager.models.v6.work import WorkResponse

work = WorkResponse.model_validate(sm.work.get_work("TSR1591199404915"))

To regenerate after a DfT release, run the Regenerate Street Manager models workflow from the Actions tab (it opens a PR), or locally:

pip install -e ".[gen]"
python scripts/generate_models.py --version v6 --from-dir specs/streetmanager/v6

Street Manager Open Data (SNS push)

Open Data is a push model: Street Manager POSTs event notifications to an HTTPS endpoint you host. The receiver needs no credentials — messages are authenticated with AWS's public signing certificate (fetched over HTTPS), not a shared secret, so there's nothing to configure on the SDK side for parsing, verifying, or confirming. streetworks.opendata handles all of that, framework-agnostic:

from streetworks.opendata import handle

# inside your web handler, with the raw request body:
event = handle(request_body, expected_topic_arn="arn:aws:sns:eu-west-2:...:...")
if event is not None:               # None => subscription handshake, auto-confirmed
    print(event["event_type"], event["object_reference"])

See examples/opendata_fastapi.py for a complete FastAPI receiver.

Credentials nuance. Receiving Open Data needs no credentials. But note there are two distinct feeds: the fully public Open Data feed (this module), and a separate per-organisation API Notifications feed whose subscription is set up by calling an authenticated Street Manager endpoint (POST api-notifications/subscribe) — that setup step needs Street Manager credentials, though the messages, once flowing, are received the same credential-free way. This module handles the receiving side of both.

Geoplace DataVIA

Basic auth or OAuth2 client credentials (server-to-server), the full NSG layer catalogue (Layer.STREET_LINES, ESU_STREETS, ESU_ONE_WAY_EXEMPTIONS, and the Interest / Construction / Special Designation layers in all three geometry flavours), composable OGC filters, and transparent paging:

from streetworks.datavia import DataViaClient, Layer, filters

with DataViaClient(username="user", password="pass") as dv:      # or client_id=/client_secret=
    street = dv.street_by_usrn(4401245)
    nearby = dv.streets_near_point(-0.138405, 50.825181, 100)    # within 100m

    sed = dv.get_features(
        Layer.SPECIAL_DESIGNATION_LINES,
        filter_fragment=filters.and_(
            filters.intersects_polygon(ring),
            filters.property_equals("special_designation_code", 3),
        ),
    )

    for feature in dv.iter_features(Layer.ESU_STREETS, page_size=500):
        ...

POST GetFeature bodies match the shapes in the DataVIA documentation (WFS 1.1.0 + ogc:Filter); GET KVP with startIndex/count is also available via get_features_kvp(). Output formats: GeoJSON (default), OGRGML, SHAPEZIP, CSV, SPATIALITEZIP.

WMS (rendered map images)

The same endpoints also serve OGC WMS, so you can pull rendered map images of NSG layers or ask "what street is at this pixel?":

from pathlib import Path

png = dv.get_map([Layer.STREET_LINES], (424000, 533800, 426000, 535200))
Path("durham-streets.png").write_bytes(png)

info = dv.get_feature_info(Layer.STREET_LINES, (424000, 533800, 426000, 535200),
                           i=384, j=384)      # pixel coords in the image

Coordinates default to British National Grid (EPSG:27700), which sidesteps the WMS 1.3.0 lat/lon axis-order trap that bites with EPSG:4326.

DfT D-TRO

OAuth2 client credentials (30-minute tokens, cached and renewed automatically), x-app-id and per-request X-Correlation-ID headers handled for you:

from streetworks.dtro import DTROClient, Environment

with DTROClient(client_id, client_secret, app_id=app_id,
                environment=Environment.INTEGRATION) as dtro:
    events = dtro.search_events(since="2026-06-01T00:00:00", pageSize=50)
    record = dtro.get_dtro(events["events"][0]["id"])

    dtro.create_dtro(payload)                          # publisher scope
    dtro.create_dtro_from_file(big_json, gzip=True)    # large D-TROs
    signed = dtro.get_all_dtros_url()                  # full CSV extract

    dtro.schema_versions()                             # available schema versions
    dtro.search({...})                                 # search published D-TROs
    dtro.create_provisions([...], dtro_id="...")       # provisions (App-Id header handled)

Scottish Road Works Register (SRWR) Open Data

Scotland's national road works register publishes its full noticing data as daily Open Data extracts under the Open Government Licence v3 — no credentials required. streetworks.srwr downloads the archives and parses the multi-record-type CSV format (spec v2.02) into typed records, grouped into complete Activities:

from streetworks.srwr import SRWRClient, describe

with SRWRClient() as srwr:
    archive = srwr.download_daily("srwr-daily.zip")
    for activity in srwr.iter_activities(archive):
        phase = activity.phases[-1]
        print(activity.activity_id,
              describe("works_type", phase.works_type),
              describe("activity_status", phase.activity_status),
              phase.location)

Parsing streams (a 4-million-record monthly archive parses in well under a minute at ~30 MB memory). Monthly/yearly archives concatenate the daily extracts; latest_activities() applies the spec's most-recent-occurrence rule. Notices, phases, sites, inspections, FPNs, restrictions and reference data are all exposed; describe() translates the register's coded values.

The authenticated SRWR (Aurora) web-services API is available only to Scottish roads authorities and utilities and is not publicly documented, so it isn't covered. The Open Data feed carries the register's noticing data and needs no account.

OS Open USRN

Every Unique Street Reference Number in Great Britain, with street geometry, as Ordnance Survey OpenData — no credentials required. USRNs are the common key across this SDK: Street Manager works, DataVIA streets, D-TRO regulated places and SRWR activities all reference them. streetworks.openusrn downloads the GeoPackage via the OS Downloads API and queries it with the standard library only (no GDAL or geospatial stack):

from streetworks.openusrn import OpenUSRNClient, UsrnDatabase, extract_gpkg

with OpenUSRNClient() as client:
    archive = client.download("osopenusrn.zip")   # ~300 MB, streamed

with UsrnDatabase(extract_gpkg(archive)) as db:
    street = db.get(33909869)
    print(street.geometry)        # WKT, British National Grid (EPSG:27700)

DATEX II (European roadworks)

DATEX II is the European standard for traffic and roadworks data exchange, used by the National Access Points across Europe. streetworks.datex2 is a streaming, namespace-tolerant parser for SituationPublication roadworks — DATEX II v3 and v2 — plus source adapters. The first is the Netherlands' credential-free NDW open data (XML):

from streetworks.datex2 import NDWClient, iter_roadworks

with NDWClient() as ndw:
    feed = ndw.download_planned_works("ndw-planned.xml.gz")

for situation in iter_roadworks(feed, provider="NDW"):
    works = situation.roadworks[0]
    print(works.source_name, works.road_maintenance_type,
          works.validity.overall_start, works.location.point)

The parser streams (the ~170 MB Dutch national feed parses in seconds at ~35 MB memory) and normalises locations across referencing methods. Coordinates are WGS84 latitude/longitude — not the British National Grid used by the UK providers here.

iter_situations/iter_roadworks (and their _full variants) take an optional provider label, as above, naming the source in the debug-level log a field-mapping fallback emits when it fires (see Spain below). IRCA, Bison Futé and DGT pass it automatically since they own their own fetch; it's stated explicitly here since you're calling the parser directly (Digitraffic and National Highways parse JSON separately, so it doesn't apply there).

National Highways (England's Strategic Road Network) publishes its DATEX II v3.4 extended profile as JSON, not XML, so it needs its own parsing path rather than the streaming XML parser above — streetworks.datex2.nationalhighways maps that JSON onto the same Situation/SituationRecord models. Needs a free subscription key from the developer portal; it pages through results automatically via the x-next cursor:

from streetworks.datex2 import ClosureType, NationalHighwaysClient

with NationalHighwaysClient(subscription_key) as nh:
    for situation in nh.iter_roadworks(ClosureType.PLANNED):
        works = situation.roadworks[0]
        print(works.cause_type, works.road_maintenance_type, works.location.point)

(Verified against the live API: it returns XML regardless of Accept headers unless you also send X-Response-MediaType: application/json — the client sends this for you.)

Finland's Digitraffic (Fintraffic's open data platform) publishes national roadworks credential-free as its own JSON schema — not a DATEX II serialisation, unlike National Highways — so streetworks.datex2.digitraffic has its own parsing path too, onto the same shared models:

from streetworks.datex2.digitraffic import DigitrafficClient, provinces

with DigitrafficClient() as digitraffic:
    payload = digitraffic.get_roadworks()
    situations = digitraffic.parse(payload)

situation_provinces = provinces(payload)  # {situation.id: "province name", ...}
for situation in situations:
    works = situation.roadworks[0]
    print(situation_provinces.get(situation.id), works.road_maintenance_type,
          works.location.point)

Verified against the live feed (2026-07): record_type is a documented compromise (Digitraffic has no maintenance/construction split, so it's hardcoded, not read off a field), validity.status stays unset always (no active/planned/suspended-equivalent exists in the feed, so date_confidence honestly comes out unknown), and the coordinate given per record is the situation's affected-area geometry, not that record's exact spot — road_number/Alert-C name are the precise per-record locators. See streetworks/datex2/digitraffic.py's module docstring for the full field-by-field mapping and why each choice was made.

Iceland's IRCA/Vegagerðin publishes national roadworks credential-free as genuine DATEX II v3 XML over a SOAP snapshotPull interface, reused through the same shared field-extraction logic as NDW — no bespoke parsing path needed. Its ~250 KB response is small enough to parse fully into memory (iter_situations_full), unlike NDW's ~170 MB feed, so .raw is populated here where NDW's streaming parser leaves it unset:

from streetworks.datex2.irca import IcelandClient

with IcelandClient() as irca:
    for situation in irca.iter_roadworks():
        works = situation.roadworks[0]
        print(works.record_type, works.validity.overall_start, works.location.point)

Verified against multiple independent live fetches (2026-07): reliably reachable with no credentials, no API key, no IP allow-listing; record_type is a genuine xsi:type discriminator (not a compromise); location is always PointLocation (checked across every situation on two separate fetches — no linear geometry, no Alert-C); administrative_area has no genuinely-stated source field anywhere in the feed (checked exhaustively), so it's left unset rather than inferred. Data is published under a licence permitting free reuse, redistribution, and commercial use, with mandatory attribution — see streetworks/datex2/irca.py's module docstring for the exact required wording and the full field-by-field mapping.

France's Bison Futé/the DIRs publish roadworks for the non-concessionary national road network (the state-run RRN) credential-free, as genuine DATEX II v2 XML — again reused through the same shared parser, no bespoke path needed:

from streetworks.datex2.bisonfute import BisonFuteClient, dir_regions

with BisonFuteClient() as bf:
    situations = list(bf.iter_roadworks())
regions = dir_regions(situations)  # {situation.id: "DIR region name", ...}
for situation in situations:
    works = situation.roadworks[0]
    print(regions.get(situation.id), works.road_maintenance_type, works.location.point)

Verified against the live feed (2026-07, 256 situations, 170 roadworks): every single roadworks record carries WGS84 coordinates and an Alert-C reference side by side — coordinates are taken, Alert-C is preserved (not decoded). France's real data is what surfaced two genuine gaps in the shared DATEX parser, now fixed: alert_c_location used to return a raw numeric location-table code instead of the human-readable name sitting right next to it, and TPEG linear locations (a segment's from/to endpoints) used to keep only whichever endpoint came first in document order, silently dropping the other — both fixed in streetworks/datex2/parser.py, and the 2-point line now survives all the way to Coordinate.points (see below). administrative_area (the DIR region, e.g. "DIR Sud-Ouest") is genuinely stated but on a different, coarser field than the shared model's source_name — dir_regions() reads it from each record's .raw XML directly. Published under the Licence Ouverte / Open Licence 2.0 (Etalab) — see streetworks/datex2/bisonfute.py's module docstring for the attribution wording and full field-by-field mapping.

Spain's DGT (Dirección General de Tráfico) publishes national traffic incidents, including roadworks, credential-free as genuine DATEX II v3 (Level C, with Spanish national extensions alongside the standard elements) — reused through the same shared parser, no bespoke path needed:

from streetworks.datex2.dgt import DGTClient, provinces

with DGTClient() as dgt:
    situations = list(dgt.iter_roadworks())
spanish_provinces = provinces(situations)  # {situation.id: "province name", ...}
for situation in situations:
    works = situation.roadworks[0]
    print(spanish_provinces.get(situation.id), works.road_maintenance_type, works.location.point)

Verified against the live feed (2026-07, 656 situations, 391 roadworks records, 100% coordinate coverage): Spain's real data is what surfaced the first genuine discriminator gap, not just a field-mapping one — DGT has zero MaintenanceWorks/ConstructionWorks records anywhere in the feed. It publishes roadworks as a generic record type (RoadOrCarriagewayOrLaneManagement, mostly, but also SpeedManagement and AbnormalTraffic) discriminated only by cause/causeType=roadMaintenance + roadMaintenanceType=roadworks — SituationRecord.is_roadworks now checks that pair additively when the xsi:type isn't one of the two dedicated types, confirmed not to change any other adapter's real fixture. The road identifier is stated as roadName (e.g. "N-400"), not roadNumber like NDW/France — added as a fallback, tried only when roadNumber is absent. administrative_area comes from a new provinces() helper (the real per-record province, e.g. "Toledo" — genuinely stated on 391/391 real records, nested in a Spanish location extension, not on the shared model, same shape of solution as France's dir_regions()). Coverage is national except Catalonia and the Basque Country, which run their own regional traffic authorities and publish separately — documented honestly, like France's non-concessionary-network scope. Published under Creative Commons Attribution (CC BY) — see streetworks/datex2/dgt.py's module docstring for the attribution wording and full field-by-field mapping.

Autobahn GmbH (Germany, national motorways)

Germany's national motorway (Autobahn) network roadworks, via Autobahn GmbH's own open JSON REST API — credential-free, but not DATEX II and not OGC/WFS, so streetworks.autobahn has its own small parser rather than routing through streetworks.datex2 (the same shape of choice as WZDx for the US). Covers the national motorway network only; German state roads are a separate WFS-based source, out of scope here.

⚠️ Licence unconfirmed. Checked govdata.de's CKAN catalogue entry for this API (organisation: Mobilithek — license_title/license_url both blank), the MDM portal link that entry points to (unreachable), the community bundesAPI/autobahn-api documentation (no licence stated), and the official autobahn.de app page (no terms of use found). None confirm reuse/redistribution rights. Shipped deliberately with this caveat rather than silently assumed open — confirm your own rights before redistributing this data.

from streetworks.autobahn import AutobahnClient
from streetworks.common import from_autobahn

with AutobahnClient() as autobahn:
    roads = autobahn.list_roads()               # 113 real road ids, e.g. "A1"
    items = list(autobahn.iter_all_roadworks(roads))   # one request per road

works = from_autobahn(items)                     # grouped into works + phases
for w in works:
    print(w.reference, len(w.sites), w.administrative_area)

Verified against a live fetch of all 113 roads (2026-07, zero failures): 2,873 roadworks records, grouping into 997 works. territory="Germany", administrative_area="Autobahn GmbH" — the national motorway operator IS the data-owning authority, same rule as National Highways for England.

Two real road-list traps, confirmed live, not just documented: "A64a"/"A99a" use lowercase route suffixes — don't upper-case road ids. More surprising: "A60 " (trailing space) isn't a formatting quirk on the one real A60 — the list carries two separate entries, a plain "A60" and this space-suffixed one, and they behave differently: GET .../A60/... returns 20 real roadworks, GET .../A60%20/... (the listed id, correctly percent-encoded, not stripped) returns zero. Stripping the space would silently refetch the other entry's 20 records under the wrong road id — so despite looking like noise, road ids must be used exactly as listed, never stripped or reformatted.

Geometry is a real line, not a point — every one of 2,873 real records carries LineString geometry (2–767 vertices), kept whole on Coordinate.points, same as the France/WZDx line-geometry handling. Native axis order is genuinely reversed within one record: the coordinate field is (lat, long), geometry.coordinates is GeoJSON (lon, lat) — both native in Roadworks, flipped explicitly in from_autobahn, same as WZDx.

A genuine two-level spine, confirmed not assumed: records sharing an identifier prefix (before its first --) are phases of one works — in the full fetch, 599 multi-record groups, and every one agrees on its overall end date (599/599, zero disagreements). Grouping is cross-road: 50 of 997 real prefixes span more than one road, because a works at a junction gets listed under every connecting road's own response (e.g. one A1/A61 junction project has 3 records under A1 and 2 under A61) — confirmed safe to merge (no identifier is ever duplicated across roads).

Dates are a deliberate, documented exception to "never infer, only take what's stated", in the same honest register as Digitraffic's validity.status caveat: there is no end-date field anywhere in this API, and no start-date field at all for SHORT_TERM_ROADWORKS records (0/1,184 real ones carry it, vs. 1,689/1,689 long-term ROADWORKS records that do). Dates for everything else come from parsing description[] — machine-generated, consistently-formatted text, not human prose, so this is extraction, not inference, but it's still an exception, and Roadworks.is_start_verified exists so callers can tell a verified date from an estimated one rather than trusting every date equally. Five real text shapes are handled (long-term Beginn/Ende, the overall-measure end, and three short-term shapes — single-day, overnight/multi-day, and a recurring-weekly pattern collapsed to its outer bounding window, the same trade-off DATEX's Validity makes for multi-period validity) — coverage is 100% for ROADWORKS and 99.7% (1,181/1,184) for SHORT_TERM_ROADWORKS; the remaining 3 records use free-form "valid except these days" text that isn't safely extractable without guessing, and are left with dates unset, raw text preserved. Timezone is Europe/Berlin via zoneinfo, not a fixed offset — DST is genuinely observed in the data (+01:00/+02:00 both seen live), and "24:00" (also seen live) means end-of-day, handled by rolling to 00:00 the next day rather than rejected. See streetworks/autobahn/parser.py's module docstring for the exact shapes and full field-by-field mapping.

The per-item details/roadworks/{id} endpoint was checked and confirmed to add nothing over the list response (sampled 6 varied real records, every extra field was null) — skipped, avoiding ~2,900 extra requests.

German state roadworks (OGC WFS)

Germany's individual states (Bundesländer) each publish their own regional-road roadworks as open geodata — separate from, and complementary to, Autobahn GmbH's national-motorway API above. streetworks.ogc is a generic OGC-features GeoJSON client (OGCFeaturesClient), plus a declarative per-state field-map registry (streetworks.ogc.germany) that one shared converter reads — adding a state is writing a new field-map entry, not a new converter. (streetworks.ogc is new infrastructure in 0.7.0 and its interface is provisional — it was deliberately built generic so the future gazetteer work can reuse it, and that work may reshape it in 0.8.0.)

from streetworks.common import from_ogc_features
from streetworks.ogc.germany import BRANDENBURG, GermanRoadworksClient

with GermanRoadworksClient() as germany:
    features = germany.fetch("Brandenburg")

works = from_ogc_features(features, BRANDENBURG)
for w in works:
    print(w.administrative_area, w.sites[0].works_type, w.sites[0].location_description)

Three states are live, all verified against real data (2026-07): Hamburg (130 features, Point geometry, dates DD.MM.YYYY, via WFS), Brandenburg (487 features, LineString, dates ISO, via WFS), and Saxony (1,531 real closures + 813 diversions, LineString, dates DD.MM.YYYY with an occasional real hour suffix, via a direct GeoJSON download — Saxony has no queryable service at all). Hamburg and Brandenburg publish under Datenlizenz Deutschland — Namensnennung — Version 2.0 (dl-de/by-2-0); Saxony under Creative Commons Attribution 4.0 International. All three confirmed directly from each service's own GetCapabilities/catalogue metadata, with exact attribution wording baked into each state's field-map entry.

GeoJSON-primary, no GML — but not every state is EPSG:4326. OGCFeaturesClient always requests application/geo+json over WFS, never trusting a server's default output format (commonly GML). A GML-only state is out of scope, not a GML-parsing project — confirmed live for both Mecklenburg-Vorpommern (its WFS explicitly rejects application/geo+json with an InvalidParameterValue exception) and Saxony-Anhalt (rejects application/json too, with an msPostGISLayer exception) — both parked. Saxony-Anhalt has a second, independent reason: its GetCapabilities states outright "This service is for non-commercial use only" — an explicit restriction, not merely an unconfirmed licence, and one that conflicts with this SDK's own MIT licence. (The state's own web page separately calls the service "free of charge," which reads as open but answers a different question — cost, not commercial-use rights. Worth knowing before anyone reopens this one.) NRW and Bavaria are parked too, for a different reason each: NRW's open geodata is road network data (a gazetteer concern), not roadworks — its actual roadworks route is the gated Mobilithek/DATEX path already out of scope elsewhere; Bavaria's BAYSIS portal has no Baustellen (roadworks) layer at all.

CRS is stated per state, never assumed — and Saxony breaks the "always WGS84" pattern deliberately. Every request states its CRS explicitly (SRSNAME=EPSG:4326 for the WFS states) rather than trusting a server default (commonly a UTM zone). Saxony's data, checked exhaustively (its WMS, its direct download, even its "planned works" dataset's own ISO metadata), genuinely has no WGS84 source anywhere — only EPSG:25833 (UTM33N). Rather than park a source this rich (district and municipal roadworks, not just state roads — deeper coverage than Hamburg or Brandenburg) over an axis-order technicality, Saxony ships with its real CRS carried through and labelled explicitly on Coordinate.crs — the same policy this SDK already uses for its British National Grid providers (OS Open USRN, DataVIA, Street Manager): a non-4326 CRS is never silently reprojected, just stated. GeoJSON coordinates in Saxony's feed are (easting, northing), taken as-is, no axis flip — exactly how from_streetmanager already handles BNG.

Axis order was checked, not assumed — WFS 2.0/EPSG:4326 can come back lat/lon (the reverse of GeoJSON's mandated lon/lat), the same trap the DataVIA WMS work already documented. Every real coordinate from Hamburg and Brandenburg falls inside Germany's true lon/lat bounds (~5.6–15.3, ~47.0–55.3); Saxony has its own equivalent UTM bounds check. All three confirmed in a mandatory test per state, not just eyeballed once.

Hamburg's access mode was genuinely ambiguous — resolved, not assumed. The state's open-data catalogue also lists a "direct GeoJSON download"; confirmed live, it's a ZIP archive wrapping this same WFS's output (the archive contains de_hh_up_baustelle_EPSG_4326.json) — not a separate source. The direct WFS GetFeature call is the canonical path: one HTTP request, GeoJSON immediately, no archive to unpack. Saxony's own "direct GeoJSON download" is genuinely the only path — confirmed via the GDI-DE catalogue's own metadata search (5 real records for Saxony's SPERRINFOSYS) that the "GDI-Baustellen-WFS" once referenced in passing doesn't exist as a live, queryable endpoint.

One Works per feature, one WorksSite, deliberately not grouped — no state's data states a genuine works/phase grouping key. Brandenburg's ID property has real prefix/suffix structure (e.g. "267201193_1", "_2", "_3") and 140 of 164 distinct prefixes are multi-record, but agreement within a group is only ~81–88% on dates/type/road — far short of Autobahn's independently-corroborated 100%. Saxony shows the same shape of pattern through a different field: 1,531 real features, only 1,133 distinct ID values — a spot-check confirms a duplicated ID is one closure split across several line segments, but the full pattern wasn't checked as thoroughly as Brandenburg's. Both ship 1:1 like every other provider without a genuine grouping signal, per this SDK's record-identity rule: raise an observed pattern, never act on it without real evidence. territory="Germany", administrative_area ("Hamburg"/"Brandenburg"/ "Sachsen") is endpoint provenance, not a record field — there is no bundesland property on any state's features; the state is known because each field map is bound to one state's own endpoint, the same mechanism National Highways' administrative_area="National Highways" uses, not Spain's provinces() reading a real per-record field.

Field names are UTF-8 throughout, umlauts and ß included — one real Brandenburg field name is Straßenummner (double "n", a typo in the source schema itself, confirmed live — not Straßennummer). Hamburg has no road number/name field of any kind (checked all 130 real features) and no single clean status field either — six independent boolean flags (iststoerung, istfreigegeben, istoepnveingeschraenkt, ...) instead, all preserved on .raw, none forced into the common model. See streetworks/ogc/germany.py's module docstring for the full field-by-field mapping and every state's exact attribution text.

WZDx (US Work Zone Data Exchange)

WZDx is the US standard for work zone data — GeoJSON-based, distinct from DATEX II, so streetworks.wzdx is its own parser rather than a datex2 adapter. It's a schema published independently by ~40+ agencies (state DOTs, MPOs, tolling authorities...), not one central API, so WZDxClient.fetch() takes any feed URL directly — credential-free:

from streetworks.wzdx import WZDxClient

with WZDxClient() as wzdx:
    feed = wzdx.fetch("https://wzdx.wsdot.wa.gov/api/v4/WorkZoneFeed")
    print(feed.version, feed.publisher, len(feed.road_events))
    for event in feed.road_events:
        if event.is_work_zone:
            print(event.road_names, event.vehicle_impact, event.geometry.point)

Use streetworks.wzdx.list_feeds() to discover feed URLs from the USDOT feed registry rather than hardcoding one.

Verified against 12 live agency feeds spanning WZDx v3.1–v4.2 (not one sample — cross-agency variation a single feed hides is exactly what broke assumptions during development): core_details nesting is a v4-only convention (v3.1 feeds are flat on properties); the feed-info key isn't cleanly version-gated (feed_info vs the older road_event_feed_info - one v4.2 feed emits both); geometry varies (LineString/MultiPoint, sometimes both within one feed, always (longitude, latitude) GeoJSON order — the reverse of DATEX's (latitude, longitude)); and date-firmness has two independent encodings in the wild (boolean is_start_date_verified/is_end_date_verified flags, and accuracy enums start_date_accuracy/end_date_accuracy) that don't always agree with each other and don't always exist together. Real placeholder/garbage dates are confirmed at scale, not assumed — one live feed's "current" records spanned years 2019–2040. Every field is read defensively; nothing raises on a malformed record.

Northern Ireland & Wales (traveller-information RSS)

The remaining UK nations are covered by open RSS feeds — credential-free, but shallower data: these are traveller-information services (current and forthcoming closures as human-readable text), not works registers. Typed fields are best-effort extractions and the raw text is always preserved.

Northern Ireland — TrafficWatchNI (streetworks.trafficwatchni): DfI's Traffic Information & Control Centre feeds for roadworks, incidents and events; trunk roads and motorways NI-wide plus all roads in Greater Belfast, refreshed every 5 minutes. Attribution required: credit DfI TICC and preserve item URLs.

Wales — Traffic Wales (streetworks.trafficwales): Welsh Government feeds for roadworks, incidents/events and headlines on the motorway and trunk road network, in English and Welsh, refreshed every 5 minutes. Attribution required: credit Traffic Wales. (Traffic Wales also offers richer DATEX II feeds — access on application via traffic.wales/developers; once granted, streetworks.datex2 can parse them.)

from streetworks.trafficwatchni import TrafficWatchNIClient
from streetworks.trafficwales import TrafficWalesClient, Feed

with TrafficWatchNIClient() as twni:
    for item in twni.fetch():
        print(item.closure_type, item.road, item.town, "-", item.promoter)

with TrafficWalesClient() as tw:
    for item in tw.fetch(Feed.ROADWORKS):
        print(item.roads, item.title)

UK Police (crime data — a worker-safety signal)

There's no API for reporting abuse or aggression towards road workers directly — it doesn't exist. What does exist is the UK Police API (data.police.uk), which publishes street-level crime for England, Wales, and Northern Ireland — no credentials required. streetworks.police wraps it as a contextual safety signal for planning lone working or an unfamiliar site, not as a street-works dataset in its own right.

from streetworks.police import PoliceClient

with PoliceClient() as police:
    signal = police.safety_signal(51.500617, -0.124629)  # lat, lng of the worksite
    print(signal)
    # {'date': None, 'total_crimes': 3420, 'safety_relevant_count': 1623,
    #  'by_category': {'anti-social-behaviour': 1152, 'violent-crime': 344,
    #                  'public-order': 98, 'robbery': 21, 'possession-of-weapons': 8}}

safety_signal() fetches crime in roughly a one-mile radius of a point and counts only the categories in SAFETY_RELEVANT_CATEGORIES — violence and sexual offences, public order, anti-social behaviour, robbery, and possession of weapons. Property crime (vehicle crime, burglary, shoplifting, bicycle theft, criminal damage) is fetched but excluded from the count, because it says little about the risk of confrontation to a person on site. The raw per-point and per-polygon methods (street_level_crimes, street_level_crimes_in_area, crimes_at_location, crimes_no_location, forces, locate_neighbourhood, ...) are also available unfiltered.

Read this as contextual awareness, not prediction — three things that would otherwise mislead:

1. Historical, not live. The API publishes street-level crime roughly a month or two in arrears, aggregated per calendar month — recent past, not what's happening at the site today.
2. Area-level, not site-level. Police deliberately anonymise each crime's location to a snapped map point (often the middle of the street, sometimes 100m+ off the true spot) to protect victim privacy. This is a signal about the surrounding area, never the exact worksite.
3. Category matters more than the total. "High crime" as a lump figure is close to meaningless for personal safety — an area heavy in vehicle crime or shoplifting says little about risk to a road crew. That's why safety_signal() filters to the categories that actually bear on it rather than reporting the raw total.

Common models

Every provider above has its own native, full-fidelity shape — that's deliberate, and it never goes away. streetworks.common adds canonical types alongside those native interfaces, for code that wants to handle works data from several providers the same way without caring which one it came from:

from streetworks.common import from_srwr
from streetworks.srwr import SRWRClient, iter_activities

with SRWRClient() as srwr:
    archive = srwr.download_daily("srwr-daily.zip")
    for activity in iter_activities(archive):
        works = from_srwr(activity)
        for site in works.sites:
            print(site.reference, site.works_type, site.date_confidence, site.raw)

A DATEX source needs two more keyword arguments, since a Situation can't state them itself — see below:

from streetworks.common import from_datex2
from streetworks.datex2.dgt import DGTClient, provinces

with DGTClient() as dgt:
    situations = list(dgt.iter_roadworks())
spanish_provinces = provinces(situations)  # {situation.id: "province name", ...}
for situation in situations:
    works = from_datex2(
        situation, territory="Spain",
        administrative_area=spanish_provinces.get(situation.id),
    )

from_datex2 (and from_wzdx) take territory/administrative_area as keywords rather than deriving them, because neither can be read off a DATEX Situation (or a WZDx RoadEvent) alone — the provider sections above show what each source natively states — a province, a DIR region, or nothing at all — that you'd pass in.

Two levels, deliberately not three: Works is the umbrella (reference, location, promoter — no committed dates of its own); WorksSite is the dated, actionable unit under it (Street Manager's -01/-02 permits, SRWR's phases joined to their Undertaker-Phase, DATEX roadworks records all map here). WorksPlanning is a separate type for planning artifacts — PAAs and Street Manager Forward Plans — with indicative rather than committed dates: a record that is born as a planning artifact maps here; a record that only transitions through a planning-ish status (SRWR's "Advance Planning", DATEX's validityStatus = planned) stays a WorksSite with that status exposed, so the same source record never migrates between canonical types as its lifecycle progresses.

Every canonical object carries a source_grade (register / operator / traveller_info) and WorksSite carries a computed date_confidence (verified / estimated / unknown), so consumers can filter by trustworthiness without provider-specific knowledge — and every one keeps .raw pointing back at its exact source record(s), so converting never loses anything.

Coordinate.value is always one representative point, so every point-only consumer keeps working unchanged; Coordinate.points holds every vertex when the source geometry is a real line (a WZDx/Street Manager LineString, a DATEX LinearLocation/TPEG segment) — points[0] == value always. This used to just collapse to value across every converter that had line geometry available; now it survives.

Works also carries location provenance, not location geography: territory (country-level — UK nations count as countries: "Scotland", "England", ..., plus "USA", "Netherlands") and administrative_area (the sub-national body that owns the data one level down — a UK highway authority, a US state DOT, a Dutch province, or a national operator's own name where the operator IS the authority). administrative_area is populated only where a provider genuinely states it, never inferred from a coordinate, and is consistent within one territory but not size-comparable across them — filter by territory before aggregating. WorksSite.territory/.administrative_area delegate to the parent Works, so a site in hand doesn't need the umbrella held separately. Some converters (from_datex2, from_wzdx) can't derive these from the source record alone — see their docstrings for why — and take them as keyword arguments instead of guessing.

Converters currently cover SRWR, Street Manager, DATEX II (NDW, National Highways, Digitraffic/Finland, IRCA/Iceland, Bison Futé/France, and DGT/Spain via the one shared converter), Autobahn GmbH/Germany, German state roadworks (Hamburg, Brandenburg, Saxony, via the one shared from_ogc_features converter), WZDx, TrafficWatchNI and Traffic Wales. UK Police stays outside the works hierarchy entirely — it's a context provider (area-level crime as a safety signal), not a works provider, and forcing it into a WorksSite would misrepresent what it actually is.

Design principles

1. Never block the user. Typed methods for confirmed, common endpoints; generic get/post/put/delete on every API group for everything else.
2. Be a good API citizen. Token reuse, refresh-then-reauth, exponential backoff, honoured Retry-After — per the DfT integration guidance.
3. Test without credentials, verify with them. The whole unit suite runs against mocked transports (respx) so CI needs no secrets; a separate smoke test and skip-guarded integration suite verify against the real systems when you supply credentials.
4. Room to grow. Each provider is a self-contained module over a shared transport/exception core — adding a new API is additive.

Roadmap

• Pydantic model generation pipeline for the Street Manager swagger specs
• Auto-pagination helpers for the Reporting API (iter_permits() etc.)
• DataVIA WMS support (get_map, get_feature_info, wms_capabilities)
• D-TRO publish models generated from the DfT JSON schemas, version-namespaced (v3.5.1 to match production, v4.0.0 to follow) — see docs/DTRO_SCHEMAS.md
• Scottish Road Works Register - Open Data provider (streetworks.srwr). The authenticated SRWR/Aurora web-services API is restricted to Scottish authorities and utilities; contributions from SRWR users welcome.
• Common models (streetworks.common): canonical cross-provider types (Works, WorksSite, WorksPlanning, Coordinate, Notice) with explicit per-provider converters (from_srwr, from_streetmanager, from_datex2, from_wzdx, from_trafficwatchni, from_trafficwales), so the same code handles works data from any provider — native full-fidelity interfaces retained, .raw always keeps the source record(s); Works also carries territory/administrative_area location provenance so a mixed cross-provider list can be filtered by where the data comes from
• OS Open USRN: credential-free GB-wide USRN lookup with geometry (streetworks.openusrn)
• Northern Ireland roadworks (TrafficWatchNI RSS) and Wales motorway/trunk roadworks (Traffic Wales RSS) — all four UK nations now have coverage
• UK Police crime data (streetworks.police) as a worker-safety signal — no API exists for roadworker abuse directly, so this is the closest honest proxy; safety_signal() filters to the categories that bear on personal safety — verified against the real API
• Traffic Wales DATEX II feeds (richer than the RSS; access on application)
• Scottish street gazetteer (OSG portal open data); Northern Ireland gazetteer (Wales street gazetteer is already covered by the Geoplace NSG via DataVIA)
• DATEX II parser (v3 + v2 SituationPublication roadworks) with the NDW (Netherlands, XML) open-data adapter — verified against the real national feed
• National Highways (England SRN) DATEX II v3.4 JSON adapter (streetworks.datex2.nationalhighways), cursor pagination via x-next — verified against the real API
• Finland (Digitraffic) DATEX adapter (streetworks.datex2.digitraffic) — its own JSON schema, not a DATEX-II serialisation, mapped onto the same shared models; verified against the real feed, no credentials
• Iceland (IRCA/Vegagerðin) DATEX adapter (streetworks.datex2.irca) — genuine DATEX II v3 XML over a SOAP snapshotPull interface, reused through the existing shared parser unchanged; verified against multiple independent live fetches, no credentials
• France (Bison Futé/the DIRs) DATEX adapter (streetworks.datex2.bisonfute) — genuine DATEX II v2 XML for the non-concessionary national network, reused through the existing shared parser; verified against the real feed (256 situations, 170 roadworks, 100% coordinate coverage), no credentials. Surfaced and fixed two real gaps in the shared parser itself (alert_c_location name preference, TPEG linear from/to geometry) - not France-specific bugs, just never exercised before
• Spain (DGT) DATEX adapter (streetworks.datex2.dgt) — genuine DATEX II v3 (Level C, Spanish-extended profile), reused through the existing shared parser; verified against the real feed (656 situations, 391 roadworks, 100% coordinate coverage), no credentials. Coverage excl. Catalonia & the Basque Country. Surfaced and fixed a genuine discriminator gap, not just a field-mapping one — DGT has zero MaintenanceWorks/ConstructionWorks records at all, so SituationRecord.is_roadworks gained an additive cause-based check (roadMaintenance/roadworks), plus a roadName fallback for the road identifier (Spain never states roadNumber)
• Germany (Autobahn GmbH) national motorway adapter (streetworks.autobahn) — its own JSON REST API, not DATEX; verified against a live fetch of all 113 roads (2,873 roadworks, zero failures), no credentials. A genuine two-level spine (works/phases) confirmed live, cross-road grouping (a junction project can be split across two roads' API responses), and a documented free-text date-parsing exception (99.7% coverage on the class with no date field at all). Licence unconfirmed despite checking four independent sources — shipped anyway, flagged prominently, not silently assumed open
• German state (Bundesland) roadworks (streetworks.ogc) — a reusable generic OGC WFS/Features/direct-download GeoJSON client plus a declarative per-state field-map registry, one shared converter reading it (adding a state is a field map, not a new converter). Hamburg, Brandenburg and Saxony shipped, verified against real data (130 + 487 + 1,531 features, 100% coordinate coverage, 0 out-of-bounds on the mandatory axis-order check each). Saxony has no queryable service at all — WMS + a direct GeoJSON ZIP download only — and no WGS84 source anywhere, so it ships in its real CRS (EPSG:25833/UTM33N), carried through and labelled explicitly, never reprojected, the same policy this SDK already applies to its BNG providers. Mecklenburg-Vorpommern and Saxony-Anhalt checked and parked (both GML-only; Saxony-Anhalt's licence also explicitly non-commercial); NRW and Bavaria parked too (network-only geodata / no Baustellen layer, not GML/CRS issues). Both Brandenburg's and Saxony's ID fields showed a real but imperfect grouping signal — raised, not acted on; ships 1:1 like every other provider without corroborated grouping evidence. Client built gazetteer-ready (generic GeoJSON fetch, CRS-aware) but no gazetteer features added yet — separate design session pending
• Norway (Statens vegvesen) DATEX adapter (streetworks.datex2.vegvesen) — Phase 1 scaffold built, pending live verification. Blocked on credentials for the actual authenticated pull; not usable against real Norwegian data yet — see the module docstring for what's confirmed vs. still open
• Further DATEX II adapters: Mobilithek (DE), transport.data.gouv.fr (FR) — per-NAP verification needed
• WZDx (US Work Zone Data Exchange) parser (streetworks.wzdx, v3.1–v4.2), a generic feed client, and a USDOT registry helper — verified against 12 live agency feeds, not one sample
• Ordnance Survey NGD / Linked Identifiers?

European & Crown Dependency roadworks — separate strand

Candidate feeds, researched but not yet verified. As always, each needs a real sample feed and a licence/access check before building — the first task per source is "can we get the feed and what do the terms permit," not coding.

Grouped by the client shape they need:

• DATEX II adapters (thin fetchers over the existing streetworks.datex2 models, Finland/National-Highways-style where the source isn't DATEX-shaped itself). Norway, Iceland, France, and Spain are covered above (Iceland, France, and Spain shipped, Norway Phase 1). Further candidates: Denmark (Vejdirektoratet), Sweden (Trafikverket — verify its SOAP/XML model is DATEX-compatible). Access models vary from fully open to registration/agreement-gated — confirm per country. Note Alert-C location-code decoding (numeric codes → geometry, not yet supported) is likely needed for some of these, unlike Finland's coordinate-carrying JSON.
• ArcGIS REST (a new client shape — Esri /query?f=json). Jersey publishes roadworks as an ArcGIS MapServer layer; likely a quick, self-contained win and the SDK's first Channel Islands coverage.
• Dedicated pieces (each its own project, not a quick adapter): Germany's Mobilithek broker (subscription access, mixed schemas — D-TRO-scale effort; distinct from Autobahn GmbH's own public motorway-roadworks API, already covered above); Guernsey (appears to be an HTML site — confirm whether any structured feed exists before committing, and check licensing for scraping).
• Verify-the-source-first: prefer official government feeds over third-party API-marketplace wrappers; a couple of the researched links need their real upstream endpoint confirmed.

International gazetteers — separate strand

The European equivalents of OS Open USRN (address/street reference layers, not roadworks — keep distinct from the feeds above): France BAN, Spain Catastro, Norway Kartverket, Netherlands PDOK, Germany Geoportal, Portugal SNIG, plus the UK GeoPlace gazetteer SOAP API. These eventually connect to the common models work; formats differ widely, so each needs its own mapping design. Germany's own state gazetteers are commonly published the same way as the regional roadworks above (WFS/OGC API Features) — streetworks.ogc's OGCFeaturesClient was deliberately kept generic (GeoJSON in, features out, CRS-aware, nothing roadworks-specific) so this future work can reuse it rather than needing its own fetch layer; no gazetteer-specific code exists yet, that's still its own design session.

Contributions welcome — see CONTRIBUTING.md.

Development

pip install -e ".[dev]"
pytest                    # mocked unit tests - no credentials needed
ruff check .

The unit tests mock the network so they run offline and without credentials. To verify the SDK against the real test/sandbox systems with your own credentials, use the smoke test or the integration suite — see docs/INTEGRATION.md:

python scripts/smoke_test.py     # one read-only call per configured service
pytest -m integration -v         # same checks, in the test suite

Licence

MIT. Not affiliated with or endorsed by the Department for Transport or Geoplace. Street Manager documentation is © Crown copyright, available under the Open Government Licence v3.0.