morocco-communes

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SUMMARY

Morocco's 1,503 communes as open data: HCP codes, the 2024 and 2014 censuses, boundaries, an HTTP API and an MCP server.

README.md

Morocco communes

An open dataset and HTTP API for Morocco's administrative divisions: 12 régions, 75
provinces and préfectures, 8 préfectures d'arrondissements, 213 cercles, 1,503 communes
and 41 arrondissements, with
official HCP geographic codes, names in French and Arabic, 2024 and 2014 population, HCP's
census figures on age, education, languages, work and housing from both years, the 2024
count of economic establishments, and boundaries from OpenStreetMap.

HCP publishes the census as spreadsheets. This builds a dataset, an API and a site from them
and from OpenStreetMap, and shows the working.

The dataset

data/v1/ is committed and versioned, so you can use it without the API at all.
CHANGELOG.md says what each version added; the build refuses a version
with no entry in it.

Directory Holds Licence
attributes/ every unit, JSON and CSV HCP, on CC BY 4.0 terms
geometry/ one TopoJSON per région, and which communes border which ODbL, share-alike
indicators/ the census indicators for every unit, 2024 and 2014, JSON and CSV HCP, on CC BY 4.0 terms
economy/ the 2024 count of economic establishments for every unit, JSON and CSV HCP, on CC BY 4.0 terms
housing/ the 2024 urban housing stock, by dwelling, JSON and CSV HCP, on CC BY 4.0 terms
crosswalk/ the 2014 ↔ 2024 reconciliation HCP, on CC BY 4.0 terms
sources.json each source's digest, licence and vintage

The licences differ by directory and geometry/ carries its own LICENSE. Five fields on
each commune (centroid, bbox, osm, areaKm2 and density) come from OpenStreetMap
and are ODbL too; provenance.geometry marks them. Every level has a CSV that opens
cleanly in Excel, Arabic included.

Rebuild it with pnpm dataset:build. From the same cache the output is byte-identical.

pnpm build also writes the boundaries as GeoJSON from the TopoJSON above: each commune,
and each province and région outlined from its communes. They're served beside it rather
than committed.

The API

Three tiers, and which one served a response is in its X-Api-Tier header.

Pre-rendered. 11,629 files written at build time and served straight from
Cloudflare Pages, without running any code. Free and unmetered.

GET /api/regions.json                        GET /api/regions/01.json
GET /api/regions/01/provinces.json           GET /api/regions/01/communes/page/1.json
GET /api/provinces/01.511.json               GET /api/provinces/01.511/cercles.json
GET /api/cercles/01.511.05.json              GET /api/communes/01.511.01.0.json
GET /api/communes/page/1.json                GET /api/communes/type/urban/page/1.json
GET /api/communes/01.511.01.0/arrondissements.json
GET /api/communes/09.581.01.07/neighbours.json
GET /api/communes/01.511.01.0/indicators.json
GET /api/communes/09.581.01.07/economy.json
GET /api/arrondissements/01.511.01.05.json   GET /api/indicators.json
GET /api/economy.json                        GET /api/version.json
GET /data/v1/**

Alias. The query-string and extensionless shapes. A path-keyed asset store can't
match on a query string, so the Worker resolves these to the file that already holds the
answer and names it in Content-Location:

GET /api/communes?province=01.511&page=1     GET /api/communes?type=urban
GET /api/communes/tanger                     GET /api/communes/001511010
GET /api/communes/tanger/indicators          GET /api/communes/tiznit/economy

Computed. The answers no file holds:

GET /api/search?q=tanger&levels=commune&limit=10
GET /api/communes/near?lat=33.5731&lng=-7.5898&radius=15
GET /api/communes/at?lat=35.786&lng=-5.8125
GET /api/communes?province=01.511&type=urban
GET /api/communes?sort=-population&min_population=100000
GET /api/communes?region=01&sort=-labour.unemploymentRate
GET /api/communes?sort=-economy.establishments.jobs

A list sorts by any of the census indicators, by its path, and each commune it lists then
carries the figure it was sorted by. 2014. before the path sorts by the 2014 figure and
change. by how far a commune moved between the censuses. An establishment count goes
under economy..

Search takes French, Arabic, a slug or a code. It folds the alef variants, ta-marbuta and alef
maqsura the names actually carry, and the tatweel and vowel marks they never do but people
type anyway. It matches names spelt another way by their consonants, so titwan finds
Tétouan and jdida El Jadida. 01.511.01.0, 001511010, 1511010 and tanger all
address one commune, and 18 exonyms are listed by hand because no amount of character folding gets from Fez
to Fès or from Port Lyautey to Kénitra.

What's counted. The alias and computed routes and the MCP server count their own use
in Workers Analytics Engine: the route with its codes taken out, or an MCP message's tool
when it called one and its method otherwise, the name an MCP client gives itself, the
first word of the User-Agent, the country, the status and how long it took. Pre-rendered
files run no code, so they aren't counted. pnpm stats reads it back, with the npm, PyPI
and GitHub numbers.

A second store, in D1, counts 5 kinds of row: a search, a place opened, a tool an assistant
calls, the name an MCP client gives itself, and a file downloaded. An assistant connecting
through the MCP server is counted by the name it gives itself, and each tool it calls by
the tool's name and the place it asks about. A row is a day and a handful of categories,
and no row holds a key, a cookie or an address that ties it to another. pnpm demand
reads it back; the site's /docs/privacy/ page says exactly what's kept.

pnpm deploy:live switches it on. It applies the migration to the live database, builds
the site with the most looked-up page read from that database, deploys it, then deploys
the nightly rollup Worker. A plain pnpm build doesn't query the database and leaves that
page empty. A failed write is swallowed, so pnpm demand a day after the first deploy is
how to see rows are arriving.

Every response is enveloped with data, meta and links. Errors are RFC 9457 problem
documents, and a well-formed code that names nothing is a 404 while something unsearchable
is a 400. CORS is open.

Full reference: api/README.md.

For programs and agents

  • /api/openapi.json: an OpenAPI 3.1 description of every route, built from the
    same module the Worker reads its limits from, so the defaults and bounds it states are
    the ones enforced. Most agent frameworks turn it into tools directly.
  • /llms.txt: a short markdown map of the API and the dataset, in the llmstxt.org
    shape, for an LLM reading the site.
  • /mcp: an MCP server with 9 read-only tools (search, get_commune, get_unit,
    communes_near, commune_at, list_communes, get_indicators, get_economy,
    get_housing), so
    Claude, Claude Code and other MCP clients can query the data directly, census figures
    included. The site's /docs/mcp/ page has the setup for each client.

In a form, or offline

  • /components/commune-picker.js: a custom element that fills a région, a province
    and a commune <select> from the static files, so a form posts the commune's HCP code.
    It's served with open CORS, and /docs/components/ has a React version beside it.
  • morocco-communes: the dataset as an npm package, in packages/morocco-communes/.
    Codes, names, parents and population as ES modules with types, one per level, and
    without the OpenStreetMap fields, so it carries no ODbL terms. pnpm npm:build builds
    it from data/v1, and the package takes the dataset's version number.
  • morocco-communes on PyPI: the same dataset for analysts, in
    packages/morocco-communes-py/. The units, both censuses, the establishments and the
    crosswalk, each table a pandas DataFrame, or a list of dicts with as_frame=False,
    which needs nothing but the standard library. pnpm py:build builds its data from
    data/v1, gzipped, and it takes the dataset's version too.

The docs site

site/ is an Astro site in English and French, with a light and dark theme and a control
to pick either or follow the system. It builds to static HTML: the home page, 7 docs pages
(the API reference, the MCP setup, the components, the npm package, the Python package,
the census figures and a glossary), and a page for every région, province and commune,
3,216 pages in all.

The home page opens on a map of every commune, shaded by density, change since 2014, or
urban and rural. Hovering one shows its figures and clicking opens its page. A commune's
page has its figures and rank, a map of its province, the communes it borders, where its
change sits among all of them, and its census figures: an age pyramid of men and women,
headline rates beside the women's and the country's, and the languages its people use.
A list of every commune filters as you type, in French or Arabic.

Its JavaScript is the map's hover and switch, the list's filter, the playground (a Solid
island that queries whatever API it's deployed beside and shows the X-Api-Tier of each
response), the picker on the components page, and the copy buttons.

Everything on it that describes the data or the API is generated at build time, by the
scripts under site/scripts/:

  • map.ts draws the home map from the TopoJSON the API serves. Each shared border is one
    arc, simplified once for both of its communes, so the fills meet without slivers. Its
    colours were checked for contrast and colour-blind separation in both themes.

  • hierarchy.ts builds the code ladder, a real chain from région down to arrondissement.

  • charts.ts computes population change per région, the distribution of commune sizes,
    how little land half the population lives on, how many communes lost people, and the growth
    spread of the 207 crosswalked communes against the 1,286 whose code never changed. That
    last one is the reconciliation checking itself: the two distributions sit almost on top
    of each other.

  • downloads.ts lists the files under data/v1 with their real sizes, and fails the
    build on a file that isn't there.

  • reference.ts builds the API reference from buildOpenApi, with each example a real
    response from the emitted files or the Worker's own functions, and lists the MCP tools
    by connecting a client to the server. The French page reads a translation of each line
    of the spec, and the build fails when one is missing or left over.

The région, province and commune pages are built from site/src/lib/places.ts, which
reads data/v1 once per build: ranks, the communes each one borders, matched on shared
boundary points, and small maps drawn the same way as the home map.

The charts are inline SVG and CSS, so they need no JavaScript and no charting library.

Arabic names are in the data and Arabic queries work; the interface is English and French.

It's static because nothing in it needs a server, so the hand-written Worker stays
the only Worker and the pages cost nothing to serve.

Running it

pnpm install
pnpm dataset:build     # rebuilds data/v1 from the cached sources
pnpm build             # the docs site, then the API tree, into dist/
pnpm api:dev           # wrangler pages dev on :8788, serving the site and the API together
pnpm api:smoke         # probes a running deployment
pnpm check             # typecheck both trees, then the tests
pnpm eval              # asks a model 49 questions through the MCP server; see evals/

A deploy build takes the origin it will be served from, which the canonical URLs, the
link preview image, the sitemap and the MCP page's configuration snippets are all built
from:

SITE_URL=https://your-deployment pnpm build

Without it the site still builds and the build says so, and those four things are left
out.

The order inside pnpm build matters: Astro clears its output directory, so the site
builds first and the API tree is emitted into the same dist/ afterwards.

pnpm site:dev runs Astro alone with hot reload, but the playground has no API to call
that way; use pnpm api:dev to see both.

Node 22 or newer. Deploying needs a Cloudflare account; see api/README.md.

How the data was assembled

HCP publishes the census as Excel, where the code column is stored numerically and has
lost its leading zeros, so codes arrive 7, 8 or 9 digits wide. The
hierarchy is recovered from document row order rather than from code arithmetic, which is
then used only to check parentage. Urban and rural come from the same row order: a commune
listed before a Cercle heading is a municipality.

Boundaries come from OpenStreetMap admin_level=8 relations, joined to HCP on the
ref:MA:HCP tag that all 1,503 carry. Overpass returns each boundary as unordered way
fragments, so the rings are stitched end to end before anything is emitted. 1,502 of the
1,503 come through: Sidi Mohamed Benmansour's relation has no closeable outer ring, so it
ships with its geometry fields null rather than a repaired guess. The 41 arrondissements
come from admin_level=10 relations the same way, all of them, and each has to sit
inside its commune and the set has to cover the city.

HCP's indicators workbook lists the same units under the same codes, so it joins by code:
every one of the 1,852 units and the 164 urban centres. Commuting comes in a workbook of
its own for each census, with the same units in the same order, and is joined row by row
before anything is placed. Each column is named after the
heading HCP gives it, and the build refuses the workbook if a heading has moved. It then
checks that each unit's population and household count equal the population file's and
that the figures add up. indicators/README.md has the details.

The census counted the urban housing stock too, in a workbook of its own: how many
dwellings each town has, how many stand empty, what kind they are, how old, what they are
made of and what they are connected to. It counts dwellings rather than households, so it
sits in housing/ rather than among the census indicators, and 784 units have one.

The census also counted workplaces. HCP's field teams mapped every economic establishment
and published the count by commune, and it lands on 1,847 units: 22 figures each, from the
establishments mapped down to the businesses by sector, by the people they employ and by
the decade they were founded. Inside a unit the parts have to make the total, and across
the country every figure has to add up the tree. The 6 cities the workbook counts by
arrondissement carry the exact sum of their own, marked basis, the same route their 2014
population takes. economy/README.md has the details.

The 2014 census published the same kind of figures, in 4 workbooks of its own, and they
land on the units of today: 1,965 of the 1,979 rows, by code, through the crosswalk, or by
name inside a commune. Three of those workbooks share a layout, so one reader takes each
of them against its own field list. 73 fields ask what 2024 asks and can be subtracted
from it; the rest changed base or categories, or are 2014's alone: what people did for a
living, the sector they worked in, and the diplomas they held. Each says how. indicators/2014/README.md has the
details, and indicators/2014/unplaced.json names the 14 rows with nowhere to land.

The boundaries also say which communes border which. Two share a border when their
boundaries share a segment, and in OpenStreetMap that segment is the same nodes in both
relations, so the match is exact rather than within a tolerance: 4,134 pairs, each with
the length they share. Following those borders from any one commune reaches all 1,502 that
have a boundary, which is the check that the country comes out as one graph rather than
several.

207 communes were renumbered by the 2015 reform and have no 2014 figure under their
current code. crosswalk/ reconciles them in two deterministic passes and records the
evidence for every pairing, so each row can be checked rather than taken on trust.

Credits and prior work

Citing it, and correcting it

CITATION.cff holds the citation, which GitHub shows as "Cite this repository". A wrong
name, figure or boundary can be reported with the data issue form, which asks for the
source that settles it. Every push runs the tests, builds everything and probes it
under wrangler dev.

Licence

Code is MIT. The data licences are per directory, as above.

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