Platform · SeLoger

SeLoger Data Scraping

In France the energy rating is not an attribute. It decides whether a property can legally be let at all.

SeLoger data scraping collects French property listings, asking prices, rents and attributes. What makes France distinct is that the DPE energy rating carries legal consequences: the worst-rated homes cannot lawfully be let. So the rating is not a nice-to-have field — it determines whether a listing represents lettable stock, and it is the first thing a French rental dataset has to get right.

Most property datasets treat an energy rating as a descriptive attribute. In France it is closer to a licence, and a 2026 reform moved a very large number of homes across the line without anyone touching a wall.

Get a free sample See sample data

Free pilot on your own SeLoger list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

seloger.jsonl LIVE FEED

{"listing_id":"sl-44120","city":"Lyon", "listing_type":"let", "dpe_rating":"G","dpe_assessed_date":"2024-03-11", "dpe_gate_status":"barred_for_new_lease", "rent_amount":740,"rent_charges":85, "surface_value":48,"surface_basis":"unstated", "caution":"counting this as lettable stock counts what cannot lawfully be let"} {"listing_id":"sl-88120", "dpe_rating":"F","dpe_assessed_date":"2026-02-04", "prior_rating_same_property":"G", "note":"rating improved. NO work was done — the 2026 coefficient reform moved it"} {"methodology_break":"2026 DPE electricity coefficient revision", "affected_estimate":"~850,000 homes, per reporting", "caution":"a series spanning this shows a renovation wave that did not happen"}

3 of 1,204,880 listing rows · run 2026-08-25 · FranceDPE is a GATING field · 2026 methodology break flagged · schema v1.1

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to SeLoger or its owners. SeLoger and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

Our Data Powers

B2C Marketplace

amazon

D2C + Marketplace

NYKAA

D2C + Marketplace

Walmart

FMCG Marketplace

udaan

Food Delivery

Uber Eats

Quick Commerce

blinkit

Taxi Aggregator

Uber

E-Commerce

Tmall

SeLoger at a glance

How we handle SeLoger specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Portal: SeLoger — France
The distinctive field: DPE energy rating, A to G
Why it matters: The worst ratings cannot lawfully be let
Timetable: G since January 2025; F from 2028; E from 2034
The 2026 catch: A reform moved many homes across the threshold with no work done
So: A rating change in your series may not be a property change
Rent control: Applies in some cities. Recorded where the listing states it
Refresh: Daily. French listing turnover is moderate but rating data updates matter

Platform specifics

An energy rating that functions as a licence

These are the reasons a SeLoger dataset needs its own handling rather than a shared retail schema.

The letting ban makes DPE a gating field, not an attribute

Under the Climate and Resilience law, French homes are being progressively barred from the rental market by energy rating.

G-rated homes have been barred from new lettings since January 2025.
F-rated homes follow from January 2028.
E-rated homes from January 2034.

The bans apply to new leases, renewals and tacit continuations rather than terminating existing tenancies immediately.

For a dataset that means dpe_rating is a gating field. A rental stock count that includes G-rated listings is counting properties that cannot lawfully be let on a new lease, and the share is not trivial — reporting has put the G-rated stock in the hundreds of thousands.

We record dpe_rating, dpe_gate_status against the current timetable, and ges_rating where published. We do not assess whether a specific listing is lawful — exemptions exist for architectural and heritage constraints and for some co-ownership situations, and that is a legal determination rather than a data one.

A 2026 reform moved homes across the line without any work being done

This is the part that matters most for anyone holding a French time series, and it is the kind of thing a dataset should surface rather than let a client discover.

In 2026 the conversion coefficient used for electricity in the DPE calculation was revised downward. Reporting put the effect at roughly 850,000 electrically heated homes moving out of the worst-rated category — mechanically, as a result of the calculation change rather than any renovation.

What that does to a series

A mass improvement appears in the data at the point of the reform.
It looks like a renovation wave. It is a coefficient change.
Any analysis of energy-efficiency improvement spanning that date will be badly wrong unless the break is identified.

We record dpe_assessed_date where published, so a rating can be placed against the methodology in force when it was issued. And we flag the reform date in the deliverable rather than letting a client read a calculation change as market behaviour.

Reporting in 2026 also indicated a further bill that could soften the ban timetable. It had not been voted at the time of writing, and we do not build a page on legislation that has not passed.

Rent control, surface conventions, and asking prices

Rent control

Rent caps apply in some French cities. Where a listing displays a reference rent or a supplement, we capture those as their own fields rather than folding them into the rent.

We do not assess whether a listed rent complies with a cap. That depends on the property's exact characteristics and the applicable zone reference, and it is a determination for the client or their counsel.

Surface

French listings use several surface conventions, and the one that applies to a sale differs from the one that applies to a let. We record surface_value with surface_basis where the listing names it, and flag it unstated where it does not — rather than assuming one and producing a per-square-metre figure that is quietly wrong.

Asking, not transaction

price_type is a constant asking. French transaction data exists separately through the public land-transaction dataset, which is a different source with different coverage and lag.

Scope

What we collect on SeLoger, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

dpe_rating and ges_rating where published
dpe_gate_status against the current letting timetable
dpe_assessed_date, so a rating sits against the methodology in force
The 2026 methodology break flagged in the deliverable
Rent-control reference and supplement as separate fields where displayed
surface_value with surface_basis, or flagged unstated
price_type constant asking, on every record
Agency name as a commercial entity
Listing lifecycle, with disappearance reason unknown by default

❌ What we do not, and why

A judgement that a specific listing is lawfully lettable
An assessment of whether a rent complies with a cap
A per-square-metre figure from an unstated surface basis
A rating change treated as a property change across the 2026 reform
Individual agent names, numbers or photographs

Core SeLoger fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
listing_id / agency_name / city / department	The listing, agency and geography
dpe_rating / ges_rating / dpe_assessed_date	The ratings and when assessed
dpe_gate_status	Against the current timetable. Not a legal judgement
price / currency / price_type	Asking, with the type constant
rent_amount / rent_charges	Rent and charges as separate fields
rent_reference / rent_supplement	Where a controlled-rent city displays them
surface_value / surface_basis	With the basis named or flagged unstated
rooms / floor / build_year	As published
listing_type	Sale or let. The DPE consequences differ
first_seen / last_seen / disappearance_reason	Lifecycle, reason unknown by default
observed_at	Timestamp

Use cases

What teams do with SeLoger data

Lettable stock counts

DPE rating with gate status, so a rental supply figure excludes stock that cannot lawfully be let on a new lease rather than counting properties that are legally off the market.

Energy-efficiency trend analysis that survives the reform

Assessment dates recorded and the 2026 methodology break flagged, so a mass rating improvement is read as a coefficient change rather than a renovation wave.

Rent-controlled market monitoring

Reference rents and supplements captured as separate fields where displayed, without us assessing compliance — which is the client's or their counsel's determination.

Per-square-metre analysis with a stated basis

Surface basis named or flagged unstated, so sale and let conventions are not compared as though they were the same measure.

The 24-hour sample — run on your sources, not ours

Send us a SeLoger item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

SeLoger is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. SeLoger data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what real estate data covers, and a SeLoger-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

SeLoger data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because it carries legal consequences rather than being descriptive. G-rated homes have been barred from new lettings since January 2025, F follows in 2028 and E in 2034.

A rental stock count including G-rated listings is counting properties that cannot lawfully be let on a new lease, and the affected stock runs into the hundreds of thousands.

The conversion coefficient used for electricity in the DPE calculation was revised downward, and reporting put the effect at roughly 850,000 electrically heated homes moving out of the worst-rated category — mechanically, with no renovation involved.

In a time series that appears as a mass improvement at the reform date. It looks like a renovation wave and is a calculation change. We flag the break rather than letting it read as market behaviour.

No. We record the rating and its status against the published timetable. Exemptions exist for architectural and heritage constraints and for some co-ownership situations.

Whether a specific property qualifies is a legal determination, not a data one.

No. We capture the reference rent and any supplement as separate fields where the listing displays them.

Whether a listed rent complies depends on the property's exact characteristics and the applicable zone reference — that is for you or your counsel.

Because French listings use several surface conventions and the one applying to a sale differs from the one applying to a let. Assuming one produces a per-square-metre figure that is quietly wrong.

We record it where the listing names it and flag it unstated where it does not.

We quote individually on listing volume, departments in scope and refresh. DPE fields add no cost — they are on the listing.

One scoping call, a free pilot within 24 hours including DPE fill rate, then a fixed monthly quote. Request a quote.

See real SeLoger data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

▶

1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

▶

2 min

★★★★★

"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."

Iulen Ibanez

CEO / Datacy.es

▶

1:30

★★★★★

"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."

Febbin Chacko

-Fin, Small Business Owner