Compare commits
4 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| a35bcd6647 | |||
| e750501b44 | |||
| 766a573989 | |||
| b0b816b0ee |
@@ -12,12 +12,31 @@ jobs:
|
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defaults:
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run:
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working-directory: api
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services:
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postgres:
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image: postgres:16-alpine
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env:
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POSTGRES_USER: opengoods
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POSTGRES_PASSWORD: opengoods
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POSTGRES_DB: opengoods
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ports:
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- "5432:5432"
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options: >-
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--health-cmd "pg_isready -U opengoods"
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--health-interval 5s --health-timeout 5s --health-retries 10
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env:
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OPENGOODS_DATABASE_URL: postgres://opengoods:opengoods@localhost:5432/opengoods?sslmode=disable
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-go@v5
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with:
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go-version: "1.23"
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cache-dependency-path: api/go.sum
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- name: Apply migrations
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working-directory: .
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run: |
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go install -tags 'postgres' github.com/golang-migrate/migrate/v4/cmd/migrate@v4.18.1
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migrate -path migrations -database "$OPENGOODS_DATABASE_URL" up
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- name: Verify gofmt
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run: test -z "$(gofmt -l .)"
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- run: go vet ./...
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@@ -43,3 +62,32 @@ jobs:
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run: ruff format --check .
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- name: Pytest
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run: pytest -q
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migrations:
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name: Migrations (postgres)
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runs-on: ubuntu-latest
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services:
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postgres:
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image: postgres:16-alpine
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env:
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POSTGRES_USER: opengoods
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POSTGRES_PASSWORD: opengoods
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POSTGRES_DB: opengoods
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ports:
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- "5432:5432"
|
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options: >-
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--health-cmd "pg_isready -U opengoods"
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--health-interval 5s --health-timeout 5s --health-retries 10
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env:
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DBURL: postgres://opengoods:opengoods@localhost:5432/opengoods?sslmode=disable
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-go@v5
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with:
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go-version: "1.23"
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- name: Install golang-migrate
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run: go install -tags 'postgres' github.com/golang-migrate/migrate/v4/cmd/migrate@v4.18.1
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- name: Migrate up
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run: migrate -path migrations -database "$DBURL" up
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- name: Migrate down (reversibility)
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run: migrate -path migrations -database "$DBURL" down -all
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+20
-1
@@ -2,20 +2,39 @@
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package main
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import (
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"context"
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"log"
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"net/http"
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"time"
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"github.com/jackc/pgx/v5/pgxpool"
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"github.com/baicai2026-baicai/goods/api/internal/config"
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"github.com/baicai2026-baicai/goods/api/internal/handler"
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"github.com/baicai2026-baicai/goods/api/internal/store"
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)
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func main() {
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cfg := config.Load()
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ctx := context.Background()
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pool, err := pgxpool.New(ctx, cfg.DatabaseURL)
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if err != nil {
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log.Fatalf("failed to create db pool: %v", err)
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}
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defer pool.Close()
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pingCtx, cancel := context.WithTimeout(ctx, 5*time.Second)
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defer cancel()
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if err := pool.Ping(pingCtx); err != nil {
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log.Printf("warning: database not reachable at startup: %v", err)
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}
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h := handler.New(store.New(pool))
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srv := &http.Server{
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Addr: cfg.Addr,
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Handler: handler.Router(),
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Handler: h.Router(),
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ReadHeaderTimeout: 10 * time.Second,
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}
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+13
-1
@@ -2,4 +2,16 @@ module github.com/baicai2026-baicai/goods/api
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go 1.23.4
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require github.com/go-chi/chi/v5 v5.1.0
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require (
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github.com/go-chi/chi/v5 v5.1.0
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github.com/jackc/pgx/v5 v5.7.2
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)
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require (
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github.com/jackc/pgpassfile v1.0.0 // indirect
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github.com/jackc/pgservicefile v0.0.0-20240606120523-5a60cdf6a761 // indirect
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github.com/jackc/puddle/v2 v2.2.2 // indirect
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golang.org/x/crypto v0.31.0 // indirect
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golang.org/x/sync v0.10.0 // indirect
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golang.org/x/text v0.21.0 // indirect
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)
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+28
@@ -1,2 +1,30 @@
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github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
|
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github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
|
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github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
|
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github.com/go-chi/chi/v5 v5.1.0 h1:acVI1TYaD+hhedDJ3r54HyA6sExp3HfXq7QWEEY/xMw=
|
||||
github.com/go-chi/chi/v5 v5.1.0/go.mod h1:DslCQbL2OYiznFReuXYUmQ2hGd1aDpCnlMNITLSKoi8=
|
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github.com/jackc/pgpassfile v1.0.0 h1:/6Hmqy13Ss2zCq62VdNG8tM1wchn8zjSGOBJ6icpsIM=
|
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github.com/jackc/pgpassfile v1.0.0/go.mod h1:CEx0iS5ambNFdcRtxPj5JhEz+xB6uRky5eyVu/W2HEg=
|
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github.com/jackc/pgservicefile v0.0.0-20240606120523-5a60cdf6a761 h1:iCEnooe7UlwOQYpKFhBabPMi4aNAfoODPEFNiAnClxo=
|
||||
github.com/jackc/pgservicefile v0.0.0-20240606120523-5a60cdf6a761/go.mod h1:5TJZWKEWniPve33vlWYSoGYefn3gLQRzjfDlhSJ9ZKM=
|
||||
github.com/jackc/pgx/v5 v5.7.2 h1:mLoDLV6sonKlvjIEsV56SkWNCnuNv531l94GaIzO+XI=
|
||||
github.com/jackc/pgx/v5 v5.7.2/go.mod h1:ncY89UGWxg82EykZUwSpUKEfccBGGYq1xjrOpsbsfGQ=
|
||||
github.com/jackc/puddle/v2 v2.2.2 h1:PR8nw+E/1w0GLuRFSmiioY6UooMp6KJv0/61nB7icHo=
|
||||
github.com/jackc/puddle/v2 v2.2.2/go.mod h1:vriiEXHvEE654aYKXXjOvZM39qJ0q+azkZFrfEOc3H4=
|
||||
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
|
||||
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
|
||||
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
|
||||
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
|
||||
github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
|
||||
github.com/stretchr/testify v1.8.1 h1:w7B6lhMri9wdJUVmEZPGGhZzrYTPvgJArz7wNPgYKsk=
|
||||
github.com/stretchr/testify v1.8.1/go.mod h1:w2LPCIKwWwSfY2zedu0+kehJoqGctiVI29o6fzry7u4=
|
||||
golang.org/x/crypto v0.31.0 h1:ihbySMvVjLAeSH1IbfcRTkD/iNscyz8rGzjF/E5hV6U=
|
||||
golang.org/x/crypto v0.31.0/go.mod h1:kDsLvtWBEx7MV9tJOj9bnXsPbxwJQ6csT/x4KIN4Ssk=
|
||||
golang.org/x/sync v0.10.0 h1:3NQrjDixjgGwUOCaF8w2+VYHv0Ve/vGYSbdkTa98gmQ=
|
||||
golang.org/x/sync v0.10.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
|
||||
golang.org/x/text v0.21.0 h1:zyQAAkrwaneQ066sspRyJaG9VNi/YJ1NfzcGB3hZ/qo=
|
||||
golang.org/x/text v0.21.0/go.mod h1:4IBbMaMmOPCJ8SecivzSH54+73PCFmPWxNTLm+vZkEQ=
|
||||
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
|
||||
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
|
||||
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
|
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+154
-15
@@ -1,5 +1,4 @@
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// Package handler wires up the public, read-only OpenGoods HTTP API.
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//
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// The OpenGoods service is a public-good product information API: it only
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// collects and serves product facts. It exposes no purchase, checkout, or
|
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// commerce endpoints by design.
|
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@@ -7,48 +6,188 @@ package handler
|
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|
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import (
|
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"encoding/json"
|
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"errors"
|
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"net/http"
|
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"strconv"
|
||||
|
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"github.com/go-chi/chi/v5"
|
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"github.com/go-chi/chi/v5/middleware"
|
||||
|
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"github.com/baicai2026-baicai/goods/api/internal/store"
|
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)
|
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|
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// APIVersion is the current public API version prefix.
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const APIVersion = "v1"
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|
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const (
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defaultPageSize = 20
|
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maxPageSize = 100
|
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)
|
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|
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// Handler holds dependencies shared by the HTTP routes.
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type Handler struct {
|
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store *store.Store
|
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}
|
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|
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// New constructs a Handler backed by the given store.
|
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func New(s *store.Store) *Handler {
|
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return &Handler{store: s}
|
||||
}
|
||||
|
||||
// Router builds the top-level HTTP handler with middleware and routes mounted.
|
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func Router() http.Handler {
|
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func (h *Handler) Router() http.Handler {
|
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r := chi.NewRouter()
|
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r.Use(middleware.RequestID)
|
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r.Use(middleware.RealIP)
|
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r.Use(middleware.Recoverer)
|
||||
|
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r.Get("/healthz", Healthz)
|
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r.Get("/healthz", h.Healthz)
|
||||
|
||||
r.Route("/api/"+APIVersion, func(r chi.Router) {
|
||||
r.Route("/products", func(r chi.Router) {
|
||||
r.Get("/barcode/{gtin}", notImplemented)
|
||||
r.Get("/search", notImplemented)
|
||||
r.Get("/{id}", notImplemented)
|
||||
r.Get("/{id}/nutriments", notImplemented)
|
||||
r.Get("/{id}/msrp", notImplemented)
|
||||
r.Get("/barcode/{gtin}", h.ProductByBarcode)
|
||||
r.Get("/search", h.SearchProducts)
|
||||
r.Get("/{id}", h.ProductByID)
|
||||
r.Get("/{id}/nutriments", h.ProductNutriments)
|
||||
r.Get("/{id}/msrp", h.ProductMSRP)
|
||||
})
|
||||
r.Get("/brands", notImplemented)
|
||||
r.Get("/categories", notImplemented)
|
||||
r.Get("/sources/{id}", notImplemented)
|
||||
r.Get("/brands", h.ListBrands)
|
||||
r.Get("/categories", h.ListCategories)
|
||||
r.Get("/sources/{id}", h.SourceByID)
|
||||
})
|
||||
|
||||
return r
|
||||
}
|
||||
|
||||
// Healthz reports liveness of the service.
|
||||
func Healthz(w http.ResponseWriter, r *http.Request) {
|
||||
func (h *Handler) Healthz(w http.ResponseWriter, r *http.Request) {
|
||||
writeJSON(w, http.StatusOK, map[string]string{"status": "ok"})
|
||||
}
|
||||
|
||||
// notImplemented is a placeholder for endpoints scoped to later milestones.
|
||||
func notImplemented(w http.ResponseWriter, r *http.Request) {
|
||||
writeError(w, r, http.StatusNotImplemented, "not_implemented", "endpoint not implemented yet")
|
||||
// ProductByBarcode returns a product by its GTIN.
|
||||
func (h *Handler) ProductByBarcode(w http.ResponseWriter, r *http.Request) {
|
||||
p, err := h.store.ProductByGTIN(r.Context(), chi.URLParam(r, "gtin"))
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, p)
|
||||
}
|
||||
|
||||
// ProductByID returns a product by its UUID.
|
||||
func (h *Handler) ProductByID(w http.ResponseWriter, r *http.Request) {
|
||||
p, err := h.store.ProductByID(r.Context(), chi.URLParam(r, "id"))
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, p)
|
||||
}
|
||||
|
||||
// SearchProducts runs a fuzzy name search with optional category filter + paging.
|
||||
func (h *Handler) SearchProducts(w http.ResponseWriter, r *http.Request) {
|
||||
q := r.URL.Query().Get("q")
|
||||
category := r.URL.Query().Get("category")
|
||||
page, size := pageParams(r)
|
||||
|
||||
items, total, err := h.store.SearchProducts(r.Context(), q, category, size, (page-1)*size)
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, map[string]any{
|
||||
"items": items,
|
||||
"page": page,
|
||||
"size": size,
|
||||
"total": total,
|
||||
})
|
||||
}
|
||||
|
||||
// ProductNutriments returns just the nutrition facts of a product.
|
||||
func (h *Handler) ProductNutriments(w http.ResponseWriter, r *http.Request) {
|
||||
n, err := h.store.Nutriments(r.Context(), chi.URLParam(r, "id"))
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, n)
|
||||
}
|
||||
|
||||
// ProductMSRP returns official suggested retail price snapshots (no purchase link).
|
||||
func (h *Handler) ProductMSRP(w http.ResponseWriter, r *http.Request) {
|
||||
items, err := h.store.ListMSRP(r.Context(), chi.URLParam(r, "id"))
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, map[string]any{
|
||||
"items": items,
|
||||
"disclaimer": "厂商建议零售价历史快照,仅供参考,不构成购买建议,本服务不提供任何购买入口。",
|
||||
})
|
||||
}
|
||||
|
||||
// ListBrands returns a paginated list of brands.
|
||||
func (h *Handler) ListBrands(w http.ResponseWriter, r *http.Request) {
|
||||
page, size := pageParams(r)
|
||||
items, total, err := h.store.ListBrands(r.Context(), size, (page-1)*size)
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, map[string]any{
|
||||
"items": items, "page": page, "size": size, "total": total,
|
||||
})
|
||||
}
|
||||
|
||||
// ListCategories returns the full category tree.
|
||||
func (h *Handler) ListCategories(w http.ResponseWriter, r *http.Request) {
|
||||
items, err := h.store.ListCategories(r.Context())
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, map[string]any{"items": items})
|
||||
}
|
||||
|
||||
// SourceByID returns a single data source.
|
||||
func (h *Handler) SourceByID(w http.ResponseWriter, r *http.Request) {
|
||||
src, err := h.store.SourceByID(r.Context(), chi.URLParam(r, "id"))
|
||||
if h.handleErr(w, r, err) {
|
||||
return
|
||||
}
|
||||
writeJSON(w, http.StatusOK, src)
|
||||
}
|
||||
|
||||
// handleErr writes an appropriate error response; returns true if it handled one.
|
||||
func (h *Handler) handleErr(w http.ResponseWriter, r *http.Request, err error) bool {
|
||||
if err == nil {
|
||||
return false
|
||||
}
|
||||
if errors.Is(err, store.ErrNotFound) {
|
||||
writeError(w, r, http.StatusNotFound, "not_found", "resource not found")
|
||||
return true
|
||||
}
|
||||
writeError(w, r, http.StatusInternalServerError, "internal_error", "internal server error")
|
||||
return true
|
||||
}
|
||||
|
||||
func pageParams(r *http.Request) (page, size int) {
|
||||
page = atoiDefault(r.URL.Query().Get("page"), 1)
|
||||
if page < 1 {
|
||||
page = 1
|
||||
}
|
||||
size = atoiDefault(r.URL.Query().Get("size"), defaultPageSize)
|
||||
if size < 1 {
|
||||
size = defaultPageSize
|
||||
}
|
||||
if size > maxPageSize {
|
||||
size = maxPageSize
|
||||
}
|
||||
return page, size
|
||||
}
|
||||
|
||||
func atoiDefault(s string, fallback int) int {
|
||||
if s == "" {
|
||||
return fallback
|
||||
}
|
||||
v, err := strconv.Atoi(s)
|
||||
if err != nil {
|
||||
return fallback
|
||||
}
|
||||
return v
|
||||
}
|
||||
|
||||
func writeJSON(w http.ResponseWriter, status int, body any) {
|
||||
|
||||
@@ -0,0 +1,134 @@
|
||||
package handler
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"net/http"
|
||||
"net/http/httptest"
|
||||
"os"
|
||||
"testing"
|
||||
"time"
|
||||
|
||||
"github.com/jackc/pgx/v5/pgxpool"
|
||||
|
||||
"github.com/baicai2026-baicai/goods/api/internal/store"
|
||||
)
|
||||
|
||||
// newTestHandler connects to the test database, skipping if unavailable or
|
||||
// unmigrated. It inserts a known product (cleaned up via t.Cleanup) so the
|
||||
// endpoint assertions are deterministic.
|
||||
func newTestHandler(t *testing.T) (*Handler, string) {
|
||||
t.Helper()
|
||||
dsn := os.Getenv("OPENGOODS_DATABASE_URL")
|
||||
if dsn == "" {
|
||||
dsn = "postgres://opengoods:opengoods@localhost:5432/opengoods?sslmode=disable"
|
||||
}
|
||||
ctx, cancel := context.WithTimeout(context.Background(), 3*time.Second)
|
||||
defer cancel()
|
||||
|
||||
pool, err := pgxpool.New(ctx, dsn)
|
||||
if err != nil {
|
||||
t.Skipf("no database: %v", err)
|
||||
}
|
||||
if err := pool.Ping(ctx); err != nil {
|
||||
pool.Close()
|
||||
t.Skipf("database not reachable: %v", err)
|
||||
}
|
||||
|
||||
var hasProduct bool
|
||||
if err := pool.QueryRow(ctx, "SELECT to_regclass('public.product') IS NOT NULL").Scan(&hasProduct); err != nil || !hasProduct {
|
||||
pool.Close()
|
||||
t.Skip("migrations not applied")
|
||||
}
|
||||
|
||||
gtin := "4006381333931"
|
||||
_, err = pool.Exec(context.Background(), `
|
||||
INSERT INTO product (gtin, name, category_id, net_content_value, net_content_unit)
|
||||
VALUES ($1, 'Test Cola', (SELECT id FROM category WHERE path='food.beverages.carbonated'), 330, 'ml')
|
||||
ON CONFLICT (gtin) WHERE gtin IS NOT NULL DO UPDATE SET name = EXCLUDED.name`, gtin)
|
||||
if err != nil {
|
||||
pool.Close()
|
||||
t.Fatalf("seed insert failed: %v", err)
|
||||
}
|
||||
var pid string
|
||||
_ = pool.QueryRow(context.Background(), "SELECT id FROM product WHERE gtin=$1", gtin).Scan(&pid)
|
||||
_, _ = pool.Exec(context.Background(), `
|
||||
INSERT INTO food_detail (product_id, nutrition_basis, nutriments)
|
||||
VALUES ($1, 'per_100ml', '{"energy_kcal": 42}'::jsonb)
|
||||
ON CONFLICT (product_id) DO UPDATE SET nutriments = EXCLUDED.nutriments`, pid)
|
||||
|
||||
t.Cleanup(func() {
|
||||
_, _ = pool.Exec(context.Background(), "DELETE FROM product WHERE gtin=$1", gtin)
|
||||
pool.Close()
|
||||
})
|
||||
return New(store.New(pool)), gtin
|
||||
}
|
||||
|
||||
func doGET(t *testing.T, h *Handler, path string) *httptest.ResponseRecorder {
|
||||
t.Helper()
|
||||
req := httptest.NewRequest(http.MethodGet, path, nil)
|
||||
rec := httptest.NewRecorder()
|
||||
h.Router().ServeHTTP(rec, req)
|
||||
return rec
|
||||
}
|
||||
|
||||
func TestProductByBarcode(t *testing.T) {
|
||||
h, gtin := newTestHandler(t)
|
||||
rec := doGET(t, h, "/api/"+APIVersion+"/products/barcode/"+gtin)
|
||||
if rec.Code != http.StatusOK {
|
||||
t.Fatalf("status = %d, body = %s", rec.Code, rec.Body.String())
|
||||
}
|
||||
var p store.Product
|
||||
if err := json.NewDecoder(rec.Body).Decode(&p); err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
if p.Name != "Test Cola" || p.GTIN == nil || *p.GTIN != gtin {
|
||||
t.Fatalf("unexpected product: %+v", p)
|
||||
}
|
||||
if p.CategoryPath == nil || *p.CategoryPath != "food.beverages.carbonated" {
|
||||
t.Fatalf("category not joined: %+v", p.CategoryPath)
|
||||
}
|
||||
}
|
||||
|
||||
func TestProductByBarcodeNotFound(t *testing.T) {
|
||||
h, _ := newTestHandler(t)
|
||||
rec := doGET(t, h, "/api/"+APIVersion+"/products/barcode/0000000000000")
|
||||
if rec.Code != http.StatusNotFound {
|
||||
t.Fatalf("expected 404, got %d", rec.Code)
|
||||
}
|
||||
}
|
||||
|
||||
func TestSearchProducts(t *testing.T) {
|
||||
h, _ := newTestHandler(t)
|
||||
rec := doGET(t, h, "/api/"+APIVersion+"/products/search?q=Cola&category=food.beverages")
|
||||
if rec.Code != http.StatusOK {
|
||||
t.Fatalf("status = %d", rec.Code)
|
||||
}
|
||||
var body struct {
|
||||
Items []store.ProductSummary `json:"items"`
|
||||
Total int `json:"total"`
|
||||
}
|
||||
if err := json.NewDecoder(rec.Body).Decode(&body); err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
if body.Total < 1 {
|
||||
t.Fatalf("expected at least 1 result, got %d", body.Total)
|
||||
}
|
||||
}
|
||||
|
||||
func TestListCategories(t *testing.T) {
|
||||
h, _ := newTestHandler(t)
|
||||
rec := doGET(t, h, "/api/"+APIVersion+"/categories")
|
||||
if rec.Code != http.StatusOK {
|
||||
t.Fatalf("status = %d", rec.Code)
|
||||
}
|
||||
var body struct {
|
||||
Items []store.Category `json:"items"`
|
||||
}
|
||||
if err := json.NewDecoder(rec.Body).Decode(&body); err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
if len(body.Items) < 20 {
|
||||
t.Fatalf("expected seeded categories, got %d", len(body.Items))
|
||||
}
|
||||
}
|
||||
@@ -11,7 +11,7 @@ func TestHealthz(t *testing.T) {
|
||||
req := httptest.NewRequest(http.MethodGet, "/healthz", nil)
|
||||
rec := httptest.NewRecorder()
|
||||
|
||||
Router().ServeHTTP(rec, req)
|
||||
New(nil).Router().ServeHTTP(rec, req)
|
||||
|
||||
if rec.Code != http.StatusOK {
|
||||
t.Fatalf("expected status %d, got %d", http.StatusOK, rec.Code)
|
||||
@@ -26,13 +26,23 @@ func TestHealthz(t *testing.T) {
|
||||
}
|
||||
}
|
||||
|
||||
func TestProductEndpointNotImplemented(t *testing.T) {
|
||||
req := httptest.NewRequest(http.MethodGet, "/api/"+APIVersion+"/products/barcode/3017624010701", nil)
|
||||
rec := httptest.NewRecorder()
|
||||
|
||||
Router().ServeHTTP(rec, req)
|
||||
|
||||
if rec.Code != http.StatusNotImplemented {
|
||||
t.Fatalf("expected status %d, got %d", http.StatusNotImplemented, rec.Code)
|
||||
func TestPageParams(t *testing.T) {
|
||||
cases := []struct {
|
||||
query string
|
||||
wantPage, wantSz int
|
||||
}{
|
||||
{"", 1, defaultPageSize},
|
||||
{"page=3&size=10", 3, 10},
|
||||
{"page=0&size=-5", 1, defaultPageSize},
|
||||
{"size=1000", 1, maxPageSize},
|
||||
{"page=abc", 1, defaultPageSize},
|
||||
}
|
||||
for _, c := range cases {
|
||||
req := httptest.NewRequest(http.MethodGet, "/?"+c.query, nil)
|
||||
page, size := pageParams(req)
|
||||
if page != c.wantPage || size != c.wantSz {
|
||||
t.Errorf("query %q: got page=%d size=%d, want page=%d size=%d",
|
||||
c.query, page, size, c.wantPage, c.wantSz)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -0,0 +1,278 @@
|
||||
// Package store is the read-only data access layer for the OpenGoods API.
|
||||
// It only issues SELECT queries; all writes happen in the Python ingestion path.
|
||||
package store
|
||||
|
||||
import (
|
||||
"context"
|
||||
"errors"
|
||||
"strconv"
|
||||
|
||||
"github.com/jackc/pgx/v5"
|
||||
"github.com/jackc/pgx/v5/pgxpool"
|
||||
)
|
||||
|
||||
// ErrNotFound is returned when a requested row does not exist.
|
||||
var ErrNotFound = errors.New("not found")
|
||||
|
||||
// Store wraps a PostgreSQL connection pool.
|
||||
type Store struct {
|
||||
pool *pgxpool.Pool
|
||||
}
|
||||
|
||||
// New constructs a Store from an existing pgx pool.
|
||||
func New(pool *pgxpool.Pool) *Store {
|
||||
return &Store{pool: pool}
|
||||
}
|
||||
|
||||
// Ping verifies database connectivity.
|
||||
func (s *Store) Ping(ctx context.Context) error {
|
||||
return s.pool.Ping(ctx)
|
||||
}
|
||||
|
||||
// Product is the full public view of a product.
|
||||
type Product struct {
|
||||
ID string `json:"id"`
|
||||
GTIN *string `json:"gtin"`
|
||||
Name string `json:"name"`
|
||||
Brand *string `json:"brand"`
|
||||
CategoryPath *string `json:"category_path"`
|
||||
GPCBrickCode *string `json:"gpc_brick_code"`
|
||||
NetContentValue *float64 `json:"net_content_value"`
|
||||
NetContentUnit *string `json:"net_content_unit"`
|
||||
CountryOfOrigin *string `json:"country_of_origin"`
|
||||
QualityScore float64 `json:"quality_score"`
|
||||
Nutriments map[string]any `json:"nutriments,omitempty"`
|
||||
NutritionBasis *string `json:"nutrition_basis,omitempty"`
|
||||
NutriScore *string `json:"nutri_score,omitempty"`
|
||||
Ingredients *string `json:"ingredients_text,omitempty"`
|
||||
Allergens []string `json:"allergens,omitempty"`
|
||||
Additives []string `json:"additives,omitempty"`
|
||||
}
|
||||
|
||||
// ProductSummary is a lightweight row used in search/listing responses.
|
||||
type ProductSummary struct {
|
||||
ID string `json:"id"`
|
||||
GTIN *string `json:"gtin"`
|
||||
Name string `json:"name"`
|
||||
Brand *string `json:"brand"`
|
||||
CategoryPath *string `json:"category_path"`
|
||||
}
|
||||
|
||||
const productSelect = `
|
||||
SELECT p.id, p.gtin, p.name, b.name, c.path::text, p.gpc_brick_code,
|
||||
p.net_content_value, p.net_content_unit, p.country_of_origin, p.quality_score,
|
||||
f.nutriments, f.nutrition_basis, f.nutri_score, f.ingredients_text,
|
||||
f.allergens, f.additives
|
||||
FROM product p
|
||||
LEFT JOIN brand b ON b.id = p.brand_id
|
||||
LEFT JOIN category c ON c.id = p.category_id
|
||||
LEFT JOIN food_detail f ON f.product_id = p.id
|
||||
`
|
||||
|
||||
func scanProduct(row pgx.Row) (*Product, error) {
|
||||
var p Product
|
||||
err := row.Scan(
|
||||
&p.ID, &p.GTIN, &p.Name, &p.Brand, &p.CategoryPath, &p.GPCBrickCode,
|
||||
&p.NetContentValue, &p.NetContentUnit, &p.CountryOfOrigin, &p.QualityScore,
|
||||
&p.Nutriments, &p.NutritionBasis, &p.NutriScore, &p.Ingredients,
|
||||
&p.Allergens, &p.Additives,
|
||||
)
|
||||
if errors.Is(err, pgx.ErrNoRows) {
|
||||
return nil, ErrNotFound
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return &p, nil
|
||||
}
|
||||
|
||||
// ProductByGTIN looks up an active product by its barcode.
|
||||
func (s *Store) ProductByGTIN(ctx context.Context, gtin string) (*Product, error) {
|
||||
row := s.pool.QueryRow(ctx, productSelect+" WHERE p.gtin = $1 AND p.status = 'active'", gtin)
|
||||
return scanProduct(row)
|
||||
}
|
||||
|
||||
// ProductByID looks up a product by its UUID.
|
||||
func (s *Store) ProductByID(ctx context.Context, id string) (*Product, error) {
|
||||
row := s.pool.QueryRow(ctx, productSelect+" WHERE p.id = $1", id)
|
||||
return scanProduct(row)
|
||||
}
|
||||
|
||||
// SearchProducts performs a fuzzy name search with optional category subtree filter.
|
||||
func (s *Store) SearchProducts(ctx context.Context, q, category string, limit, offset int) ([]ProductSummary, int, error) {
|
||||
args := []any{}
|
||||
where := "WHERE p.status = 'active'"
|
||||
if q != "" {
|
||||
args = append(args, q)
|
||||
where += " AND p.name ILIKE '%' || $1 || '%'"
|
||||
}
|
||||
if category != "" {
|
||||
args = append(args, category)
|
||||
where += " AND c.path <@ $" + strconv.Itoa(len(args)) + "::ltree"
|
||||
}
|
||||
|
||||
countSQL := "SELECT count(*) FROM product p LEFT JOIN category c ON c.id = p.category_id " + where
|
||||
var total int
|
||||
if err := s.pool.QueryRow(ctx, countSQL, args...).Scan(&total); err != nil {
|
||||
return nil, 0, err
|
||||
}
|
||||
|
||||
args = append(args, limit, offset)
|
||||
listSQL := `
|
||||
SELECT p.id, p.gtin, p.name, b.name, c.path::text
|
||||
FROM product p
|
||||
LEFT JOIN brand b ON b.id = p.brand_id
|
||||
LEFT JOIN category c ON c.id = p.category_id ` + where +
|
||||
" ORDER BY p.name LIMIT $" + strconv.Itoa(len(args)-1) + " OFFSET $" + strconv.Itoa(len(args))
|
||||
|
||||
rows, err := s.pool.Query(ctx, listSQL, args...)
|
||||
if err != nil {
|
||||
return nil, 0, err
|
||||
}
|
||||
defer rows.Close()
|
||||
|
||||
out := []ProductSummary{}
|
||||
for rows.Next() {
|
||||
var ps ProductSummary
|
||||
if err := rows.Scan(&ps.ID, &ps.GTIN, &ps.Name, &ps.Brand, &ps.CategoryPath); err != nil {
|
||||
return nil, 0, err
|
||||
}
|
||||
out = append(out, ps)
|
||||
}
|
||||
return out, total, rows.Err()
|
||||
}
|
||||
|
||||
// Nutriments returns just the nutrition payload for a product.
|
||||
type Nutriments struct {
|
||||
ProductID string `json:"product_id"`
|
||||
Basis *string `json:"basis"`
|
||||
NutriScore *string `json:"nutri_score"`
|
||||
Values map[string]any `json:"values"`
|
||||
}
|
||||
|
||||
// Nutriments fetches the nutrition facts of a product.
|
||||
func (s *Store) Nutriments(ctx context.Context, id string) (*Nutriments, error) {
|
||||
var n Nutriments
|
||||
n.ProductID = id
|
||||
err := s.pool.QueryRow(ctx,
|
||||
"SELECT nutriments, nutrition_basis, nutri_score FROM food_detail WHERE product_id = $1", id,
|
||||
).Scan(&n.Values, &n.Basis, &n.NutriScore)
|
||||
if errors.Is(err, pgx.ErrNoRows) {
|
||||
return nil, ErrNotFound
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return &n, nil
|
||||
}
|
||||
|
||||
// MSRP is an official suggested retail price snapshot (never a purchase link).
|
||||
type MSRP struct {
|
||||
Amount float64 `json:"amount"`
|
||||
Currency string `json:"currency"`
|
||||
Region string `json:"region"`
|
||||
EffectiveDate *string `json:"effective_date"`
|
||||
SourceURL *string `json:"source_url"`
|
||||
Note *string `json:"note"`
|
||||
}
|
||||
|
||||
// ListMSRP returns all MSRP snapshots for a product.
|
||||
func (s *Store) ListMSRP(ctx context.Context, id string) ([]MSRP, error) {
|
||||
rows, err := s.pool.Query(ctx,
|
||||
`SELECT amount, currency, region, effective_date::text, source_url, note
|
||||
FROM product_msrp WHERE product_id = $1 ORDER BY effective_date DESC NULLS LAST`, id)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
defer rows.Close()
|
||||
out := []MSRP{}
|
||||
for rows.Next() {
|
||||
var m MSRP
|
||||
if err := rows.Scan(&m.Amount, &m.Currency, &m.Region, &m.EffectiveDate, &m.SourceURL, &m.Note); err != nil {
|
||||
return nil, err
|
||||
}
|
||||
out = append(out, m)
|
||||
}
|
||||
return out, rows.Err()
|
||||
}
|
||||
|
||||
// Brand is a public brand entry.
|
||||
type Brand struct {
|
||||
ID string `json:"id"`
|
||||
Name string `json:"name"`
|
||||
}
|
||||
|
||||
// ListBrands returns brands ordered by name.
|
||||
func (s *Store) ListBrands(ctx context.Context, limit, offset int) ([]Brand, int, error) {
|
||||
var total int
|
||||
if err := s.pool.QueryRow(ctx, "SELECT count(*) FROM brand").Scan(&total); err != nil {
|
||||
return nil, 0, err
|
||||
}
|
||||
rows, err := s.pool.Query(ctx, "SELECT id, name FROM brand ORDER BY name LIMIT $1 OFFSET $2", limit, offset)
|
||||
if err != nil {
|
||||
return nil, 0, err
|
||||
}
|
||||
defer rows.Close()
|
||||
out := []Brand{}
|
||||
for rows.Next() {
|
||||
var b Brand
|
||||
if err := rows.Scan(&b.ID, &b.Name); err != nil {
|
||||
return nil, 0, err
|
||||
}
|
||||
out = append(out, b)
|
||||
}
|
||||
return out, total, rows.Err()
|
||||
}
|
||||
|
||||
// Category is a node in the self-built category tree.
|
||||
type Category struct {
|
||||
ID string `json:"id"`
|
||||
NameZH string `json:"name_zh"`
|
||||
NameEN *string `json:"name_en"`
|
||||
Path string `json:"path"`
|
||||
GPCBrickCode *string `json:"gpc_brick_code"`
|
||||
Level int `json:"level"`
|
||||
}
|
||||
|
||||
// ListCategories returns the full category tree ordered by path.
|
||||
func (s *Store) ListCategories(ctx context.Context) ([]Category, error) {
|
||||
rows, err := s.pool.Query(ctx,
|
||||
"SELECT id, name_zh, name_en, path::text, gpc_brick_code, level FROM category ORDER BY path")
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
defer rows.Close()
|
||||
out := []Category{}
|
||||
for rows.Next() {
|
||||
var c Category
|
||||
if err := rows.Scan(&c.ID, &c.NameZH, &c.NameEN, &c.Path, &c.GPCBrickCode, &c.Level); err != nil {
|
||||
return nil, err
|
||||
}
|
||||
out = append(out, c)
|
||||
}
|
||||
return out, rows.Err()
|
||||
}
|
||||
|
||||
// Source describes a data source with its license and trust weight.
|
||||
type Source struct {
|
||||
ID string `json:"id"`
|
||||
Name string `json:"name"`
|
||||
Homepage *string `json:"homepage"`
|
||||
License *string `json:"license"`
|
||||
TrustWeight float64 `json:"trust_weight"`
|
||||
}
|
||||
|
||||
// SourceByID fetches a single data source.
|
||||
func (s *Store) SourceByID(ctx context.Context, id string) (*Source, error) {
|
||||
var src Source
|
||||
err := s.pool.QueryRow(ctx,
|
||||
"SELECT id, name, homepage, license, trust_weight FROM source WHERE id = $1", id,
|
||||
).Scan(&src.ID, &src.Name, &src.Homepage, &src.License, &src.TrustWeight)
|
||||
if errors.Is(err, pgx.ErrNoRows) {
|
||||
return nil, ErrNotFound
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return &src, nil
|
||||
}
|
||||
@@ -0,0 +1,38 @@
|
||||
# ETL: Open Food Facts 导入 (M2)
|
||||
|
||||
把 Open Food Facts (OFF, ODbL 许可) 的食品数据采集、转换并入库。只有 Python 采集侧写库,每条记录都以 `openfoodfacts` 为来源记录**字段级溯源**。
|
||||
|
||||
## 流程
|
||||
```
|
||||
OFF API / dump(jsonl[.gz])
|
||||
→ adapters/openfoodfacts.py # 读取(限速 + User-Agent) / 解析 dump
|
||||
→ etl/transform.py # 字段映射 + 单位归一 + 营养 per_100g + 分类映射(关键词)
|
||||
→ etl/load.py # psycopg upsert(product/food_detail/product_image) + product_source 溯源
|
||||
```
|
||||
|
||||
## 运行
|
||||
先确保本地依赖与迁移就绪:`docker compose up -d postgres` + `migrate ... up`。
|
||||
|
||||
```bash
|
||||
# 用 OFF API 拉指定条码(客户端限速, 默认 4s/次)
|
||||
python -m opengoods.jobs.seed_off --barcodes 3017624010701 5449000000996
|
||||
|
||||
# 用下载好的 OFF dump 批量导入(可 .gz), 限制条数
|
||||
python -m opengoods.jobs.seed_off --dump products.jsonl.gz --limit 1000
|
||||
```
|
||||
DSN 默认读 `OPENGOODS_DATABASE_URL`。
|
||||
|
||||
## 字段映射要点
|
||||
| OFF | OpenGoods | 处理 |
|
||||
|-----|-----------|------|
|
||||
| `code` | `product.gtin` | GTIN-8/12/13/14 校验位验证, 不合法则不作为 gtin |
|
||||
| `product_name_zh/_/_en` | `product.name` | 优先中文 |
|
||||
| `brands` | `brand` | 取第一个, normalized_name 去重 |
|
||||
| `quantity` | `net_content_*` | 解析 "500 g"/"1,5 L" → 经 `units.py` 归一(原始+归一双存) |
|
||||
| `nutriments.*_100g` | `food_detail.nutriments` | per_100g; 能量 kJ/kcal 双存, 缺一自动换算 |
|
||||
| `allergens_tags`/`additives_tags` | `allergens`/`additives` | 去 `en:` 前缀 |
|
||||
| `nutriscore_grade` | `nutri_score` | 大写单字母 |
|
||||
| `categories*`/name | `category_id` | 关键词映射到自建品类树(起步版, 后续换 OFF 分类→GPC 映射表) |
|
||||
| `image_front_url` | `product_image` | 标 CC-BY-SA 许可 |
|
||||
|
||||
> 全量 dump 约数 GB;CI 与单测用 fixture 离线验证 transform,DB 集成测试在无库时自动跳过。
|
||||
@@ -0,0 +1,76 @@
|
||||
# 采集管理 (M4)
|
||||
|
||||
M4 在 M2(Open Food Facts 首次导入)基础上,补齐"持续运营"所需的采集能力:
|
||||
增量更新、第二数据源补全(GS1)、去重合并与字段级冲突解决、数据质量评分,
|
||||
以及把这些串起来的定时调度。全部为 Python 侧(`ingestion/`),只写库、可单测。
|
||||
|
||||
## 组成
|
||||
|
||||
| 能力 | 模块 | 说明 |
|
||||
|------|------|------|
|
||||
| 增量采集 | `adapters/openfoodfacts.py: fetch_modified_since()` | 按 `last_modified_t` 拉取自上次水位后变更的商品 |
|
||||
| 采集水位 | `etl/state.py` + `ingest_state` 表 | 每个源持久化 `last_modified_t`,只前进不回退 |
|
||||
| GS1 补全 | `adapters/gs1.py` + `etl/supplement.py` | 用权威条码源补**缺失**字段(品牌/厂商/GPC/产地/净含量),不覆盖已有值 |
|
||||
| 去重合并 | `etl/dedup.py` | 非 GTIN 重复(同名+品牌+净含量)合并到质量最高的主记录 |
|
||||
| 冲突解决 | `etl/merge.py` | 多源同字段按"源权重 > 新鲜度"择优,保留字段级溯源 |
|
||||
| 质量评分 | `etl/quality.py` | 0~1 分,落到 `product.quality_score` |
|
||||
| 定时调度 | `jobs/schedule.py` | 固定周期跑"增量 + 去重"一轮,零额外依赖 |
|
||||
|
||||
## 质量评分
|
||||
|
||||
锁定公式(各分量均归一到 0~1):
|
||||
|
||||
```
|
||||
quality = 0.4 * 完整度 + 0.3 * 源权重 + 0.2 * 多源一致 + 0.1 * 新鲜度
|
||||
```
|
||||
|
||||
- **完整度**:`name/gtin/brand/category/net_content/country/nutriments/ingredients/image` 9 项的命中比例。
|
||||
- **源权重**:贡献该商品的源中最高 `source.trust_weight`(OFF=0.7,GS1=0.9)。
|
||||
- **多源一致**:源数量代理——单源 0.5、两源 0.8、三源及以上 1.0(单源无法互证)。
|
||||
- **新鲜度**:最近一次 `product_source.fetched_at` 的时间衰减(≤30d=1.0 … >730d=0.2)。
|
||||
|
||||
`load_record()` 与 `merge_products()` 写入后都会调 `update_quality()` 重算。
|
||||
|
||||
## 增量水位
|
||||
|
||||
`ingest_state`(迁移 `0004`)每源一行,记录 `last_modified_t`、`last_run_at`、`stats`。
|
||||
`set_watermark()` 用 `GREATEST(...)` 保证水位只前进,避免乱序/中断的运行回退进度。
|
||||
|
||||
## 运行
|
||||
|
||||
前置:`docker compose up -d postgres` 且迁移已 `up`(含 `0004`)。DSN 默认读 `OPENGOODS_DATABASE_URL`。
|
||||
|
||||
```bash
|
||||
# 增量更新 OFF(从持久化水位开始;--since 可覆盖)
|
||||
python -m opengoods.jobs.update_off --max-pages 5
|
||||
python -m opengoods.jobs.update_off --since 1700000000
|
||||
|
||||
# 去重合并(--dry-run 只报告不写库)
|
||||
python -m opengoods.jobs.dedup --dry-run
|
||||
python -m opengoods.jobs.dedup --actor nightly
|
||||
|
||||
# 定时调度:单轮 / 周期循环(增量 + 去重)
|
||||
python -m opengoods.jobs.schedule --once
|
||||
python -m opengoods.jobs.schedule --interval 3600
|
||||
```
|
||||
|
||||
## GS1 补全
|
||||
|
||||
GS1 为付费、分区域的授权数据,适配器支持两种模式:
|
||||
|
||||
- **离线**(默认):从本地 JSON 映射 `{gtin: {...}}` 查(`GS1Adapter.from_file(path)`),
|
||||
供测试与内网环境使用。
|
||||
- **在线**:传 `base_url` + `client`(+ `api_key`),`GET {base_url}/{gtin}`,按
|
||||
Verified-by-GS1 风格字段解析。
|
||||
|
||||
补全只填**空缺**字段并在 `product_source` 记字段级溯源,源标记为 `gs1`。
|
||||
|
||||
## 测试
|
||||
|
||||
```bash
|
||||
cd ingestion && pip install -e ".[dev]"
|
||||
ruff check . && ruff format --check . && pytest -q
|
||||
```
|
||||
|
||||
纯函数测试(质量/冲突/增量分页)始终运行;依赖库的测试(水位/质量落库/去重/GS1 补全)
|
||||
在无数据库或未应用 M4 迁移时自动跳过。
|
||||
@@ -0,0 +1,124 @@
|
||||
"""GS1 barcode supplement adapter.
|
||||
|
||||
GS1 (e.g. *Verified by GS1* / GS1 China) is the authoritative registry that maps
|
||||
a GTIN to its brand owner, product description and GPC category. We use it to
|
||||
*supplement* — fill gaps in — records gathered from crowd sources like Open Food
|
||||
Facts, never to overwrite existing values.
|
||||
|
||||
Real GS1 access is credentialed and region-specific, so this adapter supports
|
||||
two modes:
|
||||
|
||||
* **offline** (default): look barcodes up in a local JSON mapping file. This is
|
||||
what tests and air-gapped runs use.
|
||||
* **online**: GET ``{base_url}/{gtin}`` with an API key header, then normalize
|
||||
the response. Enabled by passing ``base_url`` + ``client``.
|
||||
|
||||
Either way :meth:`fetch_barcode` returns a normalized *supplement* dict (or
|
||||
``None``); :mod:`opengoods.etl.supplement` applies it to the database.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from collections.abc import Iterator
|
||||
from pathlib import Path
|
||||
|
||||
import httpx
|
||||
|
||||
SOURCE_NAME = "gs1"
|
||||
GS1_HOMEPAGE = "https://www.gs1.org"
|
||||
GS1_LICENSE = "proprietary"
|
||||
# GS1 is the authoritative barcode registry -> high trust.
|
||||
GS1_TRUST = 0.9
|
||||
|
||||
# Keys of a normalized supplement record.
|
||||
_SUPPLEMENT_KEYS = (
|
||||
"gtin",
|
||||
"name",
|
||||
"brand",
|
||||
"manufacturer",
|
||||
"gpc_brick_code",
|
||||
"country_of_origin",
|
||||
"net_content_value",
|
||||
"net_content_unit",
|
||||
)
|
||||
|
||||
|
||||
def _normalize(code: str, data: dict) -> dict:
|
||||
"""Project a raw mapping/record onto the supplement schema (non-empty only)."""
|
||||
rec: dict = {"gtin": code}
|
||||
for key in _SUPPLEMENT_KEYS:
|
||||
if key == "gtin":
|
||||
continue
|
||||
value = data.get(key)
|
||||
if value not in (None, "", []):
|
||||
rec[key] = value
|
||||
return rec
|
||||
|
||||
|
||||
def _parse_api(code: str, payload: dict) -> dict:
|
||||
"""Best-effort mapping of a Verified-by-GS1 style payload to our schema."""
|
||||
item = payload
|
||||
if isinstance(payload.get("gtinRecords"), list) and payload["gtinRecords"]:
|
||||
item = payload["gtinRecords"][0]
|
||||
return _normalize(
|
||||
code,
|
||||
{
|
||||
"name": item.get("productDescription") or item.get("description"),
|
||||
"brand": item.get("brandName"),
|
||||
"manufacturer": item.get("companyName") or item.get("licenseeName"),
|
||||
"gpc_brick_code": item.get("gpcCategoryCode"),
|
||||
"country_of_origin": item.get("countryOfSaleCode") or item.get("countryCode"),
|
||||
"net_content_value": item.get("netContent"),
|
||||
"net_content_unit": item.get("netContentUnit"),
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
class GS1Adapter:
|
||||
"""Look up GTIN supplements from a local mapping or a GS1-style API."""
|
||||
|
||||
source_name = SOURCE_NAME
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
mapping: dict | None = None,
|
||||
*,
|
||||
client: httpx.Client | None = None,
|
||||
base_url: str | None = None,
|
||||
api_key: str | None = None,
|
||||
) -> None:
|
||||
self._mapping = mapping or {}
|
||||
self._client = client
|
||||
self._base_url = base_url.rstrip("/") if base_url else None
|
||||
self._api_key = api_key
|
||||
|
||||
@classmethod
|
||||
def from_file(cls, path: str | Path) -> GS1Adapter:
|
||||
"""Build an offline adapter from a JSON ``{gtin: {...}}`` mapping file."""
|
||||
data = json.loads(Path(path).read_text(encoding="utf-8"))
|
||||
return cls(mapping=data)
|
||||
|
||||
def fetch_barcode(self, code: str) -> dict | None:
|
||||
"""Return a normalized supplement dict for ``code`` (or ``None``)."""
|
||||
if self._base_url and self._client is not None:
|
||||
headers = {"apikey": self._api_key} if self._api_key else {}
|
||||
resp = self._client.get(f"{self._base_url}/{code}", headers=headers)
|
||||
if resp.status_code == 404:
|
||||
return None
|
||||
resp.raise_for_status()
|
||||
rec = _parse_api(code, resp.json())
|
||||
else:
|
||||
data = self._mapping.get(code)
|
||||
if not data:
|
||||
return None
|
||||
rec = _normalize(code, data)
|
||||
# A record with only the GTIN carries no supplement.
|
||||
return rec if len(rec) > 1 else None
|
||||
|
||||
def fetch(self, barcodes: list[str]) -> Iterator[dict]:
|
||||
"""Yield supplement records for the given barcodes."""
|
||||
for code in barcodes:
|
||||
rec = self.fetch_barcode(code)
|
||||
if rec is not None:
|
||||
yield rec
|
||||
@@ -0,0 +1,135 @@
|
||||
"""Open Food Facts (OFF) source adapter.
|
||||
|
||||
Fetches raw product records either from the OFF read API (one product per
|
||||
barcode) or from a downloaded JSONL dump file. OFF data is licensed under the
|
||||
Open Database License (ODbL); product images are CC-BY-SA. We record OFF as the
|
||||
source for every field we ingest.
|
||||
|
||||
The adapter is read-only and rate-limited to stay well within OFF's API limits
|
||||
(<= ~15 req/min/IP for product reads) and to be a good citizen.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import time
|
||||
from collections.abc import Iterator
|
||||
from pathlib import Path
|
||||
|
||||
import httpx
|
||||
|
||||
SOURCE_NAME = "openfoodfacts"
|
||||
OFF_LICENSE = "ODbL"
|
||||
USER_AGENT = "OpenGoods/0.1 (+https://github.com/baicai2026-baicai/goods) public-good product API"
|
||||
|
||||
# Conservative client-side spacing between API calls (seconds).
|
||||
_DEFAULT_MIN_INTERVAL = 4.0
|
||||
_API_URL = "https://world.openfoodfacts.org/api/v2/product/{barcode}.json"
|
||||
_SEARCH_URL = "https://world.openfoodfacts.org/api/v2/search"
|
||||
|
||||
# Fields requested from the search API so a returned product can be transformed
|
||||
# without an extra per-barcode round trip.
|
||||
_SEARCH_FIELDS = (
|
||||
"code,product_name,product_name_en,product_name_zh,brands,quantity,"
|
||||
"categories,categories_tags,countries,ingredients_text,allergens_tags,"
|
||||
"additives_tags,nutriments,nutriscore_grade,serving_size,"
|
||||
"image_front_url,image_url,last_modified_t"
|
||||
)
|
||||
|
||||
|
||||
class OpenFoodFactsAdapter:
|
||||
"""Read product records from the OFF API."""
|
||||
|
||||
source_name = SOURCE_NAME
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
client: httpx.Client | None = None,
|
||||
min_interval: float = _DEFAULT_MIN_INTERVAL,
|
||||
) -> None:
|
||||
self._client = client or httpx.Client(headers={"User-Agent": USER_AGENT}, timeout=30.0)
|
||||
self._min_interval = min_interval
|
||||
self._last_call = 0.0
|
||||
|
||||
def _throttle(self) -> None:
|
||||
elapsed = time.monotonic() - self._last_call
|
||||
wait = self._min_interval - elapsed
|
||||
if wait > 0:
|
||||
time.sleep(wait)
|
||||
self._last_call = time.monotonic()
|
||||
|
||||
def fetch_barcode(self, barcode: str) -> dict | None:
|
||||
"""Fetch a single product by barcode; return the raw `product` dict."""
|
||||
self._throttle()
|
||||
resp = self._client.get(_API_URL.format(barcode=barcode))
|
||||
resp.raise_for_status()
|
||||
payload = resp.json()
|
||||
if payload.get("status") != 1:
|
||||
return None
|
||||
return payload["product"]
|
||||
|
||||
def fetch(self, barcodes: list[str]) -> Iterator[dict]:
|
||||
"""Yield raw product records for the given barcodes."""
|
||||
for code in barcodes:
|
||||
record = self.fetch_barcode(code)
|
||||
if record is not None:
|
||||
yield record
|
||||
|
||||
def fetch_modified_since(
|
||||
self,
|
||||
since_t: int,
|
||||
*,
|
||||
page_size: int = 100,
|
||||
max_pages: int = 10,
|
||||
) -> Iterator[dict]:
|
||||
"""Yield products modified after ``since_t`` (unix ``last_modified_t``).
|
||||
|
||||
Uses the OFF search API sorted by ``last_modified_t`` (most recent
|
||||
first) and paginates until it reaches products at or before the
|
||||
watermark, an empty/short page, or ``max_pages``. This is the
|
||||
incremental ingestion path: callers persist the highest
|
||||
``last_modified_t`` they processed as the next watermark.
|
||||
"""
|
||||
for page in range(1, max_pages + 1):
|
||||
self._throttle()
|
||||
resp = self._client.get(
|
||||
_SEARCH_URL,
|
||||
params={
|
||||
"fields": _SEARCH_FIELDS,
|
||||
"sort_by": "last_modified_t",
|
||||
"page": page,
|
||||
"page_size": page_size,
|
||||
},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
products = resp.json().get("products") or []
|
||||
if not products:
|
||||
return
|
||||
reached_old = False
|
||||
for prod in products:
|
||||
if int(prod.get("last_modified_t") or 0) <= since_t:
|
||||
reached_old = True
|
||||
break
|
||||
yield prod
|
||||
if reached_old or len(products) < page_size:
|
||||
return
|
||||
|
||||
|
||||
def read_dump(path: str | Path) -> Iterator[dict]:
|
||||
"""Yield raw product records from an OFF JSONL dump file.
|
||||
|
||||
Each line is one product JSON object (the format of OFF's .jsonl export).
|
||||
Supports plain or .gz files.
|
||||
"""
|
||||
p = Path(path)
|
||||
if p.suffix == ".gz":
|
||||
import gzip
|
||||
|
||||
opener = lambda: gzip.open(p, "rt", encoding="utf-8") # noqa: E731
|
||||
else:
|
||||
opener = lambda: open(p, encoding="utf-8") # noqa: E731
|
||||
with opener() as fh:
|
||||
for line in fh:
|
||||
line = line.strip()
|
||||
if line:
|
||||
yield json.loads(line)
|
||||
@@ -0,0 +1,139 @@
|
||||
"""Duplicate detection and product merging.
|
||||
|
||||
Barcodes (GTIN) are already unique at the schema level, so duplicates here are
|
||||
non-GTIN records that describe the same product (same normalized name + brand +
|
||||
net content). For each duplicate group we keep the highest-quality product as
|
||||
canonical and merge the rest into it: child rows (provenance, images, MSRP) are
|
||||
re-pointed to the canonical product, the merged product is marked ``merged``
|
||||
with ``canonical_id`` set, and a row is written to ``merge_log``.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import psycopg
|
||||
|
||||
from opengoods.etl.quality import update_quality
|
||||
|
||||
|
||||
def _norm(text: str | None) -> str:
|
||||
return " ".join((text or "").lower().split())
|
||||
|
||||
|
||||
def product_signature(name: str | None, brand: str | None, net_canonical: Any | None) -> str | None:
|
||||
"""Stable signature for non-GTIN dedup, or ``None`` if too sparse to match."""
|
||||
n = _norm(name)
|
||||
if not n:
|
||||
return None
|
||||
net = "" if net_canonical is None else str(net_canonical)
|
||||
return f"{n}|{_norm(brand)}|{net}"
|
||||
|
||||
|
||||
def choose_canonical(members: list[dict]) -> dict:
|
||||
"""Pick the canonical product: best quality, then oldest, then lowest id."""
|
||||
return min(
|
||||
members,
|
||||
key=lambda m: (
|
||||
-float(m.get("quality_score") or 0.0),
|
||||
m.get("created_at"),
|
||||
str(m.get("id")),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def find_duplicate_groups(conn: psycopg.Connection) -> list[list[dict]]:
|
||||
"""Return groups (size >= 2) of active products sharing a signature."""
|
||||
rows = conn.execute(
|
||||
"""
|
||||
SELECT p.id, p.name, b.normalized_name, p.net_content_canonical,
|
||||
p.quality_score, p.created_at
|
||||
FROM product p
|
||||
LEFT JOIN brand b ON b.id = p.brand_id
|
||||
WHERE p.status = 'active'
|
||||
"""
|
||||
).fetchall()
|
||||
|
||||
groups: dict[str, list[dict]] = {}
|
||||
for r in rows:
|
||||
sig = product_signature(r[1], r[2], r[3])
|
||||
if sig is None:
|
||||
continue
|
||||
member = {
|
||||
"id": r[0],
|
||||
"name": r[1],
|
||||
"quality_score": r[4],
|
||||
"created_at": r[5],
|
||||
}
|
||||
groups.setdefault(sig, []).append(member)
|
||||
|
||||
return [m for m in groups.values() if len(m) >= 2]
|
||||
|
||||
|
||||
def merge_products(
|
||||
conn: psycopg.Connection,
|
||||
kept_id: str,
|
||||
merged_id: str,
|
||||
reason: str = "auto-dedup",
|
||||
actor: str = "ingestion",
|
||||
) -> None:
|
||||
"""Merge ``merged_id`` into ``kept_id`` (re-point children, mark merged)."""
|
||||
if kept_id == merged_id:
|
||||
return
|
||||
|
||||
# Re-point provenance, images and MSRP to the canonical product.
|
||||
conn.execute(
|
||||
"UPDATE product_source SET product_id = %s WHERE product_id = %s",
|
||||
(kept_id, merged_id),
|
||||
)
|
||||
conn.execute(
|
||||
"UPDATE product_image SET product_id = %s WHERE product_id = %s",
|
||||
(kept_id, merged_id),
|
||||
)
|
||||
conn.execute(
|
||||
"UPDATE product_msrp SET product_id = %s WHERE product_id = %s",
|
||||
(kept_id, merged_id),
|
||||
)
|
||||
|
||||
# food_detail has product_id as PK, so it can only move if the canonical
|
||||
# product does not already have one.
|
||||
kept_has_food = conn.execute(
|
||||
"SELECT 1 FROM food_detail WHERE product_id = %s", (kept_id,)
|
||||
).fetchone()
|
||||
if not kept_has_food:
|
||||
conn.execute(
|
||||
"UPDATE food_detail SET product_id = %s WHERE product_id = %s",
|
||||
(kept_id, merged_id),
|
||||
)
|
||||
|
||||
conn.execute(
|
||||
"UPDATE product SET status = 'merged', canonical_id = %s WHERE id = %s",
|
||||
(kept_id, merged_id),
|
||||
)
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT INTO merge_log (kept_id, merged_id, reason, actor)
|
||||
VALUES (%s, %s, %s, %s)
|
||||
""",
|
||||
(kept_id, merged_id, reason, actor),
|
||||
)
|
||||
|
||||
# The canonical product gained sources, so its quality may have changed.
|
||||
update_quality(conn, kept_id)
|
||||
|
||||
|
||||
def dedup_all(
|
||||
conn: psycopg.Connection, actor: str = "ingestion", dry_run: bool = False
|
||||
) -> dict[str, int]:
|
||||
"""Merge every duplicate group. Returns counts of groups and merges."""
|
||||
groups = find_duplicate_groups(conn)
|
||||
merged = 0
|
||||
for members in groups:
|
||||
canonical = choose_canonical(members)
|
||||
for m in members:
|
||||
if m["id"] == canonical["id"]:
|
||||
continue
|
||||
if not dry_run:
|
||||
merge_products(conn, canonical["id"], m["id"], actor=actor)
|
||||
merged += 1
|
||||
return {"groups": len(groups), "merged": merged}
|
||||
@@ -0,0 +1,213 @@
|
||||
"""Load transformed product records into the OpenGoods PostgreSQL database.
|
||||
|
||||
Only the ingestion side writes to the database. Every load records OFF as the
|
||||
source with field-level provenance in `product_source`.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
from typing import Any
|
||||
|
||||
import psycopg
|
||||
from psycopg.types.json import Jsonb
|
||||
|
||||
from opengoods.adapters.openfoodfacts import OFF_LICENSE, SOURCE_NAME
|
||||
from opengoods.etl.quality import update_quality
|
||||
|
||||
OFF_HOMEPAGE = "https://world.openfoodfacts.org"
|
||||
|
||||
|
||||
def default_dsn() -> str:
|
||||
return os.environ.get(
|
||||
"OPENGOODS_DATABASE_URL",
|
||||
"postgres://opengoods:opengoods@localhost:5432/opengoods?sslmode=disable",
|
||||
)
|
||||
|
||||
|
||||
def _normalize_brand(name: str) -> str:
|
||||
return " ".join(name.lower().split())
|
||||
|
||||
|
||||
def ensure_source_named(
|
||||
conn: psycopg.Connection,
|
||||
name: str,
|
||||
homepage: str,
|
||||
license: str,
|
||||
trust_weight: float,
|
||||
) -> str:
|
||||
"""Upsert a source row by name and return its id."""
|
||||
row = conn.execute(
|
||||
"""
|
||||
INSERT INTO source (name, homepage, license, trust_weight)
|
||||
VALUES (%s, %s, %s, %s)
|
||||
ON CONFLICT (name) DO UPDATE SET homepage = EXCLUDED.homepage
|
||||
RETURNING id
|
||||
""",
|
||||
(name, homepage, license, trust_weight),
|
||||
).fetchone()
|
||||
return row[0]
|
||||
|
||||
|
||||
def ensure_source(conn: psycopg.Connection) -> str:
|
||||
"""Upsert the Open Food Facts source row and return its id."""
|
||||
return ensure_source_named(conn, SOURCE_NAME, OFF_HOMEPAGE, OFF_LICENSE, 0.7)
|
||||
|
||||
|
||||
def _ensure_brand(conn: psycopg.Connection, name: str | None) -> str | None:
|
||||
if not name:
|
||||
return None
|
||||
row = conn.execute(
|
||||
"""
|
||||
INSERT INTO brand (name, normalized_name)
|
||||
VALUES (%s, %s)
|
||||
ON CONFLICT (normalized_name) DO UPDATE SET name = brand.name
|
||||
RETURNING id
|
||||
""",
|
||||
(name, _normalize_brand(name)),
|
||||
).fetchone()
|
||||
return row[0]
|
||||
|
||||
|
||||
def _category_id(conn: psycopg.Connection, path: str | None) -> tuple[str | None, str | None]:
|
||||
if not path:
|
||||
return None, None
|
||||
row = conn.execute(
|
||||
"SELECT id, gpc_brick_code FROM category WHERE path = %s::ltree", (path,)
|
||||
).fetchone()
|
||||
return (row[0], row[1]) if row else (None, None)
|
||||
|
||||
|
||||
def load_record(conn: psycopg.Connection, rec: dict[str, Any], source_id: str, raw: dict) -> str:
|
||||
"""Upsert one transformed record; return the product id."""
|
||||
brand_id = _ensure_brand(conn, rec.get("brand"))
|
||||
category_id, gpc_brick = _category_id(conn, rec.get("category_path"))
|
||||
|
||||
fields = ["name", "brand", "net_content", "category", "country_of_origin"]
|
||||
|
||||
if rec.get("gtin"):
|
||||
prod = conn.execute(
|
||||
"""
|
||||
INSERT INTO product (gtin, name, brand_id, category_id, gpc_brick_code,
|
||||
net_content_value, net_content_unit, net_content_canonical,
|
||||
country_of_origin, attributes)
|
||||
VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
|
||||
ON CONFLICT (gtin) WHERE gtin IS NOT NULL DO UPDATE SET
|
||||
name = EXCLUDED.name,
|
||||
brand_id = COALESCE(EXCLUDED.brand_id, product.brand_id),
|
||||
category_id = COALESCE(EXCLUDED.category_id, product.category_id),
|
||||
gpc_brick_code = COALESCE(EXCLUDED.gpc_brick_code, product.gpc_brick_code),
|
||||
net_content_value = EXCLUDED.net_content_value,
|
||||
net_content_unit = EXCLUDED.net_content_unit,
|
||||
net_content_canonical = EXCLUDED.net_content_canonical,
|
||||
country_of_origin = EXCLUDED.country_of_origin
|
||||
RETURNING id
|
||||
""",
|
||||
(
|
||||
rec["gtin"],
|
||||
rec["name"],
|
||||
brand_id,
|
||||
category_id,
|
||||
gpc_brick,
|
||||
rec.get("net_content_value"),
|
||||
rec.get("net_content_unit"),
|
||||
rec.get("net_content_canonical"),
|
||||
rec.get("country_of_origin"),
|
||||
Jsonb({}),
|
||||
),
|
||||
).fetchone()
|
||||
else:
|
||||
prod = conn.execute(
|
||||
"""
|
||||
INSERT INTO product (name, brand_id, category_id, gpc_brick_code,
|
||||
net_content_value, net_content_unit, net_content_canonical,
|
||||
country_of_origin, attributes)
|
||||
VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s)
|
||||
RETURNING id
|
||||
""",
|
||||
(
|
||||
rec["name"],
|
||||
brand_id,
|
||||
category_id,
|
||||
gpc_brick,
|
||||
rec.get("net_content_value"),
|
||||
rec.get("net_content_unit"),
|
||||
rec.get("net_content_canonical"),
|
||||
rec.get("country_of_origin"),
|
||||
Jsonb({}),
|
||||
),
|
||||
).fetchone()
|
||||
product_id = prod[0]
|
||||
|
||||
food = rec.get("food") or {}
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT INTO food_detail (product_id, ingredients_text, allergens, additives,
|
||||
nutriments, nutrition_basis, serving_size, nutri_score)
|
||||
VALUES (%s,%s,%s,%s,%s,%s,%s,%s)
|
||||
ON CONFLICT (product_id) DO UPDATE SET
|
||||
ingredients_text = EXCLUDED.ingredients_text,
|
||||
allergens = EXCLUDED.allergens,
|
||||
additives = EXCLUDED.additives,
|
||||
nutriments = EXCLUDED.nutriments,
|
||||
nutrition_basis = EXCLUDED.nutrition_basis,
|
||||
serving_size = EXCLUDED.serving_size,
|
||||
nutri_score = EXCLUDED.nutri_score
|
||||
""",
|
||||
(
|
||||
product_id,
|
||||
food.get("ingredients_text"),
|
||||
food.get("allergens") or [],
|
||||
food.get("additives") or [],
|
||||
Jsonb(food.get("nutriments") or {}),
|
||||
food.get("nutrition_basis"),
|
||||
food.get("serving_size"),
|
||||
food.get("nutri_score"),
|
||||
),
|
||||
)
|
||||
|
||||
if rec.get("image_url"):
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT INTO product_image (product_id, url, kind, license, source_id)
|
||||
VALUES (%s,%s,'front',%s,%s)
|
||||
""",
|
||||
(product_id, rec["image_url"], "CC-BY-SA", source_id),
|
||||
)
|
||||
fields.append("image")
|
||||
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT INTO product_source (product_id, source_id, url, fields, fetched_at, raw)
|
||||
VALUES (%s,%s,%s,%s, now(), %s)
|
||||
""",
|
||||
(
|
||||
product_id,
|
||||
source_id,
|
||||
f"{OFF_HOMEPAGE}/product/{rec.get('gtin') or ''}",
|
||||
fields,
|
||||
Jsonb(_jsonable(raw)),
|
||||
),
|
||||
)
|
||||
|
||||
# Recompute the data-quality score now that all facts + provenance exist.
|
||||
update_quality(conn, product_id)
|
||||
return product_id
|
||||
|
||||
|
||||
def _jsonable(raw: dict) -> dict:
|
||||
"""Drop values that are not JSON-serializable from a raw record."""
|
||||
try:
|
||||
json.dumps(raw)
|
||||
return raw
|
||||
except (TypeError, ValueError):
|
||||
return {k: v for k, v in raw.items() if _is_jsonable(v)}
|
||||
|
||||
|
||||
def _is_jsonable(v: object) -> bool:
|
||||
try:
|
||||
json.dumps(v)
|
||||
return True
|
||||
except (TypeError, ValueError):
|
||||
return False
|
||||
@@ -0,0 +1,104 @@
|
||||
"""Field-level conflict resolution for multi-source records.
|
||||
|
||||
When more than one source describes the same product, each field may have
|
||||
several candidate values. We pick a winner per field by source trust first,
|
||||
then recency, ignoring empty values, and keep a provenance trail of which
|
||||
source won each field.
|
||||
|
||||
These are pure functions (no DB / no network) so they are easy to unit-test;
|
||||
the DB-level record merge lives in :mod:`opengoods.etl.dedup`.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class Candidate:
|
||||
"""One source's proposed value for a field."""
|
||||
|
||||
value: object
|
||||
source: str
|
||||
trust: float = 0.5
|
||||
fetched_at: datetime | None = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class FieldResolution:
|
||||
"""The winning value for a field plus the source it came from."""
|
||||
|
||||
value: object
|
||||
source: str | None = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class MergedRecord:
|
||||
"""A merged record with per-field provenance (field name -> source)."""
|
||||
|
||||
values: dict[str, object] = field(default_factory=dict)
|
||||
provenance: dict[str, str] = field(default_factory=dict)
|
||||
|
||||
|
||||
def _is_empty(value: object) -> bool:
|
||||
if value is None:
|
||||
return True
|
||||
if isinstance(value, str):
|
||||
return value.strip() == ""
|
||||
if isinstance(value, (list, dict, tuple, set)):
|
||||
return len(value) == 0
|
||||
return False
|
||||
|
||||
|
||||
def _sort_key(c: Candidate) -> tuple[float, float]:
|
||||
ts = c.fetched_at.timestamp() if c.fetched_at is not None else float("-inf")
|
||||
return (c.trust, ts)
|
||||
|
||||
|
||||
def resolve_field(candidates: list[Candidate]) -> FieldResolution | None:
|
||||
"""Pick the best non-empty candidate for one field.
|
||||
|
||||
Ranking: highest source trust, then most recent ``fetched_at``. Returns
|
||||
``None`` when there is no usable (non-empty) candidate.
|
||||
"""
|
||||
usable = [c for c in candidates if not _is_empty(c.value)]
|
||||
if not usable:
|
||||
return None
|
||||
winner = max(usable, key=_sort_key)
|
||||
return FieldResolution(value=winner.value, source=winner.source)
|
||||
|
||||
|
||||
def merge_records(records: list[dict], *, fields: list[str] | None = None) -> MergedRecord:
|
||||
"""Merge several ``{field: Candidate|value}`` records into one.
|
||||
|
||||
Each input record maps field name -> :class:`Candidate` (preferred) or a
|
||||
bare value (treated as trust 0.5, no timestamp). The result keeps, for each
|
||||
field, the winning value and the name of the source that supplied it.
|
||||
"""
|
||||
keys: list[str]
|
||||
if fields is not None:
|
||||
keys = list(fields)
|
||||
else:
|
||||
seen: dict[str, None] = {}
|
||||
for rec in records:
|
||||
for k in rec:
|
||||
seen.setdefault(k, None)
|
||||
keys = list(seen)
|
||||
|
||||
merged = MergedRecord()
|
||||
for key in keys:
|
||||
candidates: list[Candidate] = []
|
||||
for rec in records:
|
||||
if key not in rec:
|
||||
continue
|
||||
cand = rec[key]
|
||||
if not isinstance(cand, Candidate):
|
||||
cand = Candidate(value=cand, source="unknown")
|
||||
candidates.append(cand)
|
||||
resolution = resolve_field(candidates)
|
||||
if resolution is not None:
|
||||
merged.values[key] = resolution.value
|
||||
if resolution.source is not None:
|
||||
merged.provenance[key] = resolution.source
|
||||
return merged
|
||||
@@ -0,0 +1,176 @@
|
||||
"""Product data-quality scoring.
|
||||
|
||||
The quality score is a 0..1 number combining four signals, per the locked
|
||||
project decision:
|
||||
|
||||
quality = 0.4 * completeness
|
||||
+ 0.3 * source_trust
|
||||
+ 0.2 * multi_source_agreement
|
||||
+ 0.1 * freshness
|
||||
|
||||
Each component is itself normalized to 0..1. The pure helpers below are
|
||||
unit-testable; :func:`compute_quality` / :func:`update_quality` read the signals
|
||||
for a product out of the database and persist the result on ``product``.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
|
||||
import psycopg
|
||||
|
||||
W_COMPLETENESS = 0.4
|
||||
W_SOURCE_TRUST = 0.3
|
||||
W_AGREEMENT = 0.2
|
||||
W_FRESHNESS = 0.1
|
||||
|
||||
# Fields that count towards completeness (weighted equally).
|
||||
COMPLETENESS_FIELDS = (
|
||||
"name",
|
||||
"gtin",
|
||||
"brand",
|
||||
"category",
|
||||
"net_content",
|
||||
"country_of_origin",
|
||||
"nutriments",
|
||||
"ingredients",
|
||||
"image",
|
||||
)
|
||||
|
||||
|
||||
def completeness(present: set[str]) -> float:
|
||||
"""Fraction of :data:`COMPLETENESS_FIELDS` that are present for a product."""
|
||||
if not COMPLETENESS_FIELDS:
|
||||
return 0.0
|
||||
hits = sum(1 for f in COMPLETENESS_FIELDS if f in present)
|
||||
return hits / len(COMPLETENESS_FIELDS)
|
||||
|
||||
|
||||
def agreement_from_sources(source_count: int) -> float:
|
||||
"""Multi-source corroboration proxy from the number of distinct sources.
|
||||
|
||||
A single source cannot be corroborated, so it scores a neutral 0.5; more
|
||||
independent sources that describe the same product raise confidence.
|
||||
"""
|
||||
if source_count <= 1:
|
||||
return 0.5
|
||||
if source_count == 2:
|
||||
return 0.8
|
||||
return 1.0
|
||||
|
||||
|
||||
def freshness_from_age(age_days: float | None) -> float:
|
||||
"""Recency score from the age (in days) of the most recent source fetch."""
|
||||
if age_days is None:
|
||||
return 0.5
|
||||
if age_days <= 30:
|
||||
return 1.0
|
||||
if age_days <= 180:
|
||||
return 0.8
|
||||
if age_days <= 365:
|
||||
return 0.6
|
||||
if age_days <= 730:
|
||||
return 0.4
|
||||
return 0.2
|
||||
|
||||
|
||||
def score(
|
||||
*,
|
||||
completeness_score: float,
|
||||
source_trust: float,
|
||||
agreement: float,
|
||||
freshness: float,
|
||||
) -> float:
|
||||
"""Combine the four normalized components into a 0..1 quality score."""
|
||||
raw = (
|
||||
W_COMPLETENESS * completeness_score
|
||||
+ W_SOURCE_TRUST * source_trust
|
||||
+ W_AGREEMENT * agreement
|
||||
+ W_FRESHNESS * freshness
|
||||
)
|
||||
return round(max(0.0, min(1.0, raw)), 3)
|
||||
|
||||
|
||||
def _present_fields(prod: dict, has_image: bool) -> set[str]:
|
||||
present: set[str] = set()
|
||||
if prod.get("name"):
|
||||
present.add("name")
|
||||
if prod.get("gtin"):
|
||||
present.add("gtin")
|
||||
if prod.get("brand_id"):
|
||||
present.add("brand")
|
||||
if prod.get("category_id"):
|
||||
present.add("category")
|
||||
if prod.get("net_content_canonical") is not None:
|
||||
present.add("net_content")
|
||||
if prod.get("country_of_origin"):
|
||||
present.add("country_of_origin")
|
||||
if prod.get("nutriments"):
|
||||
present.add("nutriments")
|
||||
if prod.get("ingredients_text"):
|
||||
present.add("ingredients")
|
||||
if has_image:
|
||||
present.add("image")
|
||||
return present
|
||||
|
||||
|
||||
def compute_quality(conn: psycopg.Connection, product_id: str) -> float:
|
||||
"""Compute (but do not persist) the quality score for one product."""
|
||||
row = conn.execute(
|
||||
"""
|
||||
SELECT p.name, p.gtin, p.brand_id, p.category_id, p.net_content_canonical,
|
||||
p.country_of_origin, f.nutriments, f.ingredients_text,
|
||||
EXISTS (SELECT 1 FROM product_image pi WHERE pi.product_id = p.id)
|
||||
FROM product p
|
||||
LEFT JOIN food_detail f ON f.product_id = p.id
|
||||
WHERE p.id = %s
|
||||
""",
|
||||
(product_id,),
|
||||
).fetchone()
|
||||
if row is None:
|
||||
return 0.0
|
||||
prod = {
|
||||
"name": row[0],
|
||||
"gtin": row[1],
|
||||
"brand_id": row[2],
|
||||
"category_id": row[3],
|
||||
"net_content_canonical": row[4],
|
||||
"country_of_origin": row[5],
|
||||
"nutriments": row[6],
|
||||
"ingredients_text": row[7],
|
||||
}
|
||||
has_image = bool(row[8])
|
||||
|
||||
src = conn.execute(
|
||||
"""
|
||||
SELECT count(DISTINCT ps.source_id), COALESCE(max(s.trust_weight), 0), max(ps.fetched_at)
|
||||
FROM product_source ps
|
||||
LEFT JOIN source s ON s.id = ps.source_id
|
||||
WHERE ps.product_id = %s
|
||||
""",
|
||||
(product_id,),
|
||||
).fetchone()
|
||||
source_count = int(src[0] or 0)
|
||||
source_trust = float(src[1] or 0.0)
|
||||
last_fetched: datetime | None = src[2]
|
||||
|
||||
age_days: float | None = None
|
||||
if last_fetched is not None:
|
||||
now = datetime.now(UTC)
|
||||
if last_fetched.tzinfo is None:
|
||||
last_fetched = last_fetched.replace(tzinfo=UTC)
|
||||
age_days = max(0.0, (now - last_fetched).total_seconds() / 86400.0)
|
||||
|
||||
return score(
|
||||
completeness_score=completeness(_present_fields(prod, has_image)),
|
||||
source_trust=source_trust,
|
||||
agreement=agreement_from_sources(source_count),
|
||||
freshness=freshness_from_age(age_days),
|
||||
)
|
||||
|
||||
|
||||
def update_quality(conn: psycopg.Connection, product_id: str) -> float:
|
||||
"""Compute the quality score and write it to ``product.quality_score``."""
|
||||
value = compute_quality(conn, product_id)
|
||||
conn.execute("UPDATE product SET quality_score = %s WHERE id = %s", (value, product_id))
|
||||
return value
|
||||
@@ -0,0 +1,45 @@
|
||||
"""Persistent ingestion watermark stored in the ``ingest_state`` table.
|
||||
|
||||
The incremental updater uses this to remember how far it got for each source
|
||||
(e.g. Open Food Facts exposes a ``last_modified_t`` unix timestamp on every
|
||||
product) so repeated runs only fetch what changed.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import psycopg
|
||||
from psycopg.types.json import Jsonb
|
||||
|
||||
|
||||
def get_watermark(conn: psycopg.Connection, source: str) -> int:
|
||||
"""Return the last processed ``last_modified_t`` for *source* (0 if none)."""
|
||||
row = conn.execute(
|
||||
"SELECT last_modified_t FROM ingest_state WHERE source = %s", (source,)
|
||||
).fetchone()
|
||||
return int(row[0]) if row else 0
|
||||
|
||||
|
||||
def set_watermark(
|
||||
conn: psycopg.Connection,
|
||||
source: str,
|
||||
last_modified_t: int,
|
||||
stats: dict[str, Any] | None = None,
|
||||
) -> None:
|
||||
"""Upsert the watermark and run metadata for *source*.
|
||||
|
||||
The watermark only ever moves forward: a lower ``last_modified_t`` is
|
||||
ignored so an out-of-order or partial run cannot rewind progress.
|
||||
"""
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT INTO ingest_state (source, last_modified_t, last_run_at, stats)
|
||||
VALUES (%s, %s, now(), %s)
|
||||
ON CONFLICT (source) DO UPDATE SET
|
||||
last_modified_t = GREATEST(ingest_state.last_modified_t, EXCLUDED.last_modified_t),
|
||||
last_run_at = now(),
|
||||
stats = EXCLUDED.stats
|
||||
""",
|
||||
(source, int(last_modified_t), Jsonb(stats or {})),
|
||||
)
|
||||
@@ -0,0 +1,133 @@
|
||||
"""Apply GS1 (or other authoritative) supplements to existing products.
|
||||
|
||||
A supplement only fills *gaps*: a field is written only when the product does
|
||||
not already have a value. Each applied supplement records field-level provenance
|
||||
in ``product_source`` and refreshes the product's quality score.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from decimal import Decimal, InvalidOperation
|
||||
from typing import Any
|
||||
|
||||
import psycopg
|
||||
from psycopg.types.json import Jsonb
|
||||
|
||||
from opengoods import units
|
||||
from opengoods.adapters.gs1 import GS1_HOMEPAGE, GS1_LICENSE, GS1_TRUST, SOURCE_NAME
|
||||
from opengoods.etl.load import _ensure_brand, _normalize_brand, ensure_source_named
|
||||
from opengoods.etl.quality import update_quality
|
||||
|
||||
|
||||
def ensure_gs1_source(conn: psycopg.Connection) -> str:
|
||||
"""Upsert the GS1 source row and return its id."""
|
||||
return ensure_source_named(conn, SOURCE_NAME, GS1_HOMEPAGE, GS1_LICENSE, GS1_TRUST)
|
||||
|
||||
|
||||
def _ensure_manufacturer(conn: psycopg.Connection, name: str | None) -> str | None:
|
||||
if not name:
|
||||
return None
|
||||
row = conn.execute(
|
||||
"""
|
||||
INSERT INTO manufacturer (name, normalized_name)
|
||||
VALUES (%s, %s)
|
||||
ON CONFLICT (normalized_name) DO UPDATE SET name = manufacturer.name
|
||||
RETURNING id
|
||||
""",
|
||||
(name, _normalize_brand(name)),
|
||||
).fetchone()
|
||||
return row[0]
|
||||
|
||||
|
||||
def _net_content(rec: dict) -> tuple[Decimal, str, Decimal | None] | None:
|
||||
raw_value = rec.get("net_content_value")
|
||||
unit = rec.get("net_content_unit")
|
||||
if raw_value is None or not unit:
|
||||
return None
|
||||
try:
|
||||
value = Decimal(str(raw_value))
|
||||
except (InvalidOperation, ValueError):
|
||||
return None
|
||||
try:
|
||||
canonical = units.normalize(value, unit).canonical_value
|
||||
except units.UnitError:
|
||||
canonical = None
|
||||
return value, unit, canonical
|
||||
|
||||
|
||||
def apply_supplement(conn: psycopg.Connection, rec: dict[str, Any], source_id: str) -> list[str]:
|
||||
"""Fill missing fields of the GTIN-matched product from ``rec``.
|
||||
|
||||
Returns the list of field names actually filled (empty if the product is
|
||||
unknown or already complete for the supplied fields).
|
||||
"""
|
||||
gtin = rec.get("gtin")
|
||||
if not gtin:
|
||||
return []
|
||||
prod = conn.execute(
|
||||
"""
|
||||
SELECT id, brand_id, manufacturer_id, gpc_brick_code, country_of_origin,
|
||||
net_content_value
|
||||
FROM product
|
||||
WHERE gtin = %s AND status = 'active'
|
||||
""",
|
||||
(gtin,),
|
||||
).fetchone()
|
||||
if prod is None:
|
||||
return []
|
||||
|
||||
product_id, brand_id, manufacturer_id, gpc, country, net_value = prod
|
||||
sets: list[str] = []
|
||||
params: list[Any] = []
|
||||
filled: list[str] = []
|
||||
|
||||
if brand_id is None and rec.get("brand"):
|
||||
new_brand_id = _ensure_brand(conn, rec["brand"])
|
||||
if new_brand_id is not None:
|
||||
sets.append("brand_id = %s")
|
||||
params.append(new_brand_id)
|
||||
filled.append("brand")
|
||||
|
||||
if manufacturer_id is None and rec.get("manufacturer"):
|
||||
new_mfr_id = _ensure_manufacturer(conn, rec["manufacturer"])
|
||||
if new_mfr_id is not None:
|
||||
sets.append("manufacturer_id = %s")
|
||||
params.append(new_mfr_id)
|
||||
filled.append("manufacturer")
|
||||
|
||||
if gpc is None and rec.get("gpc_brick_code"):
|
||||
sets.append("gpc_brick_code = %s")
|
||||
params.append(rec["gpc_brick_code"])
|
||||
filled.append("gpc_brick_code")
|
||||
|
||||
if country is None and rec.get("country_of_origin"):
|
||||
sets.append("country_of_origin = %s")
|
||||
params.append(rec["country_of_origin"])
|
||||
filled.append("country_of_origin")
|
||||
|
||||
if net_value is None:
|
||||
net = _net_content(rec)
|
||||
if net is not None:
|
||||
value, unit, canonical = net
|
||||
sets += [
|
||||
"net_content_value = %s",
|
||||
"net_content_unit = %s",
|
||||
"net_content_canonical = %s",
|
||||
]
|
||||
params += [value, unit, canonical]
|
||||
filled.append("net_content")
|
||||
|
||||
if not filled:
|
||||
return []
|
||||
|
||||
params.append(product_id)
|
||||
conn.execute(f"UPDATE product SET {', '.join(sets)} WHERE id = %s", params)
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT INTO product_source (product_id, source_id, url, fields, fetched_at, raw)
|
||||
VALUES (%s, %s, %s, %s, now(), %s)
|
||||
""",
|
||||
(product_id, source_id, GS1_HOMEPAGE, filled, Jsonb(rec)),
|
||||
)
|
||||
update_quality(conn, product_id)
|
||||
return filled
|
||||
@@ -0,0 +1,159 @@
|
||||
"""Transform raw Open Food Facts records into the OpenGoods internal shape.
|
||||
|
||||
Pure functions (no DB, no network) so they are easy to unit-test against
|
||||
fixtures. The output dict mirrors the columns the loader writes.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
from decimal import Decimal
|
||||
|
||||
from opengoods.units import UnitError, normalize
|
||||
|
||||
# OFF nutriment key -> our attribute key. Energy handled separately.
|
||||
_NUTRIMENT_KEYS = {
|
||||
"proteins_100g": "proteins",
|
||||
"fat_100g": "fat",
|
||||
"saturated-fat_100g": "saturated_fat",
|
||||
"carbohydrates_100g": "carbohydrates",
|
||||
"sugars_100g": "sugars",
|
||||
"salt_100g": "salt",
|
||||
}
|
||||
|
||||
# Very small keyword -> category path map (starter; replaced by a proper
|
||||
# OFF taxonomy -> GPC mapping table later).
|
||||
_CATEGORY_KEYWORDS: list[tuple[tuple[str, ...], str]] = [
|
||||
(("water", "eau", "饮用水", "矿泉水"), "food.beverages.water"),
|
||||
(("soda", "carbonated", "汽水", "碳酸"), "food.beverages.carbonated"),
|
||||
(("juice", "jus", "果汁"), "food.beverages.juice"),
|
||||
(("milk", "lait", "牛奶"), "food.dairy.milk"),
|
||||
(("yogurt", "yoghurt", "yaourt", "酸奶"), "food.dairy.yogurt"),
|
||||
(("cheese", "fromage", "奶酪", "干酪"), "food.dairy.cheese"),
|
||||
(("bread", "pain", "面包"), "food.bakery.bread"),
|
||||
(("biscuit", "cookie", "饼干"), "food.bakery.biscuits"),
|
||||
(("chips", "crisps", "薯片", "膨化"), "food.snacks.chips"),
|
||||
(("chocolate", "chocolat", "巧克力"), "food.snacks.chocolate"),
|
||||
(("rice", "riz", "大米", "稻米"), "food.staple.rice"),
|
||||
(("noodle", "pasta", "面条", "挂面"), "food.staple.noodles"),
|
||||
(("oil", "huile", "食用油", "食油"), "food.staple.cooking_oil"),
|
||||
(("soy sauce", "酱油"), "food.condiments.soy_sauce"),
|
||||
(("salt", "sel", "食盐"), "food.condiments.salt"),
|
||||
]
|
||||
|
||||
_QTY_RE = re.compile(r"(?P<value>\d+(?:[.,]\d+)?)\s*(?P<unit>[a-zA-Z\u4e00-\u9fff%]+)")
|
||||
|
||||
|
||||
def is_valid_gtin(code: str) -> bool:
|
||||
"""Validate a GTIN-8/12/13/14 using the standard check digit."""
|
||||
if not code.isdigit() or len(code) not in (8, 12, 13, 14):
|
||||
return False
|
||||
digits = [int(c) for c in code]
|
||||
check = digits[-1]
|
||||
body = digits[:-1][::-1]
|
||||
total = sum(d * (3 if i % 2 == 0 else 1) for i, d in enumerate(body))
|
||||
return (10 - total % 10) % 10 == check
|
||||
|
||||
|
||||
def parse_quantity(text: str) -> tuple[Decimal, str] | None:
|
||||
"""Parse a free-text quantity like '500 g' or '1,5 L' -> (value, unit)."""
|
||||
if not text:
|
||||
return None
|
||||
m = _QTY_RE.search(text)
|
||||
if not m:
|
||||
return None
|
||||
value = Decimal(m.group("value").replace(",", "."))
|
||||
return value, m.group("unit")
|
||||
|
||||
|
||||
def map_category(raw: dict) -> str | None:
|
||||
"""Best-effort map OFF categories/name to a self-built category path."""
|
||||
haystack = " ".join(
|
||||
str(raw.get(k, ""))
|
||||
for k in ("categories", "categories_tags", "product_name", "product_name_en")
|
||||
).lower()
|
||||
for keywords, path in _CATEGORY_KEYWORDS:
|
||||
if any(kw.lower() in haystack for kw in keywords):
|
||||
return path
|
||||
return None
|
||||
|
||||
|
||||
def _clean_tags(tags: list[str] | None, prefix: str = "") -> list[str]:
|
||||
out: list[str] = []
|
||||
for t in tags or []:
|
||||
v = t.split(":", 1)[-1] if ":" in t else t
|
||||
v = v.strip().replace("-", " ")
|
||||
if v:
|
||||
out.append(v)
|
||||
return out
|
||||
|
||||
|
||||
def transform_nutriments(off_nutriments: dict) -> dict:
|
||||
"""Build a nutriments dict on a per_100g basis with dual energy units."""
|
||||
out: dict[str, object] = {}
|
||||
for off_key, our_key in _NUTRIMENT_KEYS.items():
|
||||
if off_key in off_nutriments and off_nutriments[off_key] is not None:
|
||||
out[our_key] = float(off_nutriments[off_key])
|
||||
|
||||
kj = off_nutriments.get("energy-kj_100g")
|
||||
kcal = off_nutriments.get("energy-kcal_100g")
|
||||
if kj is None and kcal is not None:
|
||||
kj = float(Decimal(str(kcal)) * Decimal("4.184"))
|
||||
if kcal is None and kj is not None:
|
||||
kcal = float(Decimal(str(kj)) / Decimal("4.184"))
|
||||
if kj is not None:
|
||||
out["energy_kj"] = round(float(kj), 3)
|
||||
if kcal is not None:
|
||||
out["energy_kcal"] = round(float(kcal), 3)
|
||||
return out
|
||||
|
||||
|
||||
def transform(raw: dict) -> dict | None:
|
||||
"""Transform one raw OFF product record into an internal product dict.
|
||||
|
||||
Returns None if the record lacks a usable name.
|
||||
"""
|
||||
name = raw.get("product_name_zh") or raw.get("product_name") or raw.get("product_name_en")
|
||||
if not name:
|
||||
return None
|
||||
|
||||
code = str(raw.get("code", "")).strip()
|
||||
gtin = code if code and is_valid_gtin(code) else None
|
||||
|
||||
brands = raw.get("brands") or ""
|
||||
brand = brands.split(",")[0].strip() or None
|
||||
|
||||
net_value = net_unit = net_canonical = None
|
||||
parsed = parse_quantity(raw.get("quantity", ""))
|
||||
if parsed:
|
||||
value, unit = parsed
|
||||
try:
|
||||
norm = normalize(value, unit)
|
||||
net_value, net_unit, net_canonical = (
|
||||
norm.value,
|
||||
norm.unit,
|
||||
norm.canonical_value,
|
||||
)
|
||||
except UnitError:
|
||||
net_value, net_unit = value, unit
|
||||
|
||||
return {
|
||||
"gtin": gtin,
|
||||
"name": str(name).strip(),
|
||||
"brand": brand,
|
||||
"category_path": map_category(raw),
|
||||
"net_content_value": net_value,
|
||||
"net_content_unit": net_unit,
|
||||
"net_content_canonical": net_canonical,
|
||||
"country_of_origin": (raw.get("countries") or "").split(",")[0].strip() or None,
|
||||
"food": {
|
||||
"ingredients_text": raw.get("ingredients_text") or None,
|
||||
"allergens": _clean_tags(raw.get("allergens_tags")),
|
||||
"additives": _clean_tags(raw.get("additives_tags")),
|
||||
"nutriments": transform_nutriments(raw.get("nutriments") or {}),
|
||||
"nutrition_basis": "per_100g",
|
||||
"serving_size": raw.get("serving_size") or None,
|
||||
"nutri_score": (raw.get("nutriscore_grade") or "").upper()[:1] or None,
|
||||
},
|
||||
"image_url": raw.get("image_front_url") or raw.get("image_url") or None,
|
||||
}
|
||||
@@ -0,0 +1,40 @@
|
||||
"""Deduplicate products: merge non-GTIN duplicates into a canonical record.
|
||||
|
||||
Usage:
|
||||
python -m opengoods.jobs.dedup --dry-run
|
||||
python -m opengoods.jobs.dedup --actor nightly
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import sys
|
||||
|
||||
import psycopg
|
||||
|
||||
from opengoods.etl.dedup import dedup_all
|
||||
from opengoods.etl.load import default_dsn
|
||||
|
||||
|
||||
def run(args: argparse.Namespace) -> int:
|
||||
with psycopg.connect(args.dsn, autocommit=False) as conn:
|
||||
summary = dedup_all(conn, actor=args.actor, dry_run=args.dry_run)
|
||||
if args.dry_run:
|
||||
conn.rollback()
|
||||
else:
|
||||
conn.commit()
|
||||
mode = "dry-run" if args.dry_run else "applied"
|
||||
print(f"{mode} groups={summary['groups']} merged={summary['merged']}")
|
||||
return 0
|
||||
|
||||
|
||||
def main(argv: list[str] | None = None) -> int:
|
||||
parser = argparse.ArgumentParser(description="Deduplicate OpenGoods products")
|
||||
parser.add_argument("--actor", default="ingestion", help="merge_log actor label")
|
||||
parser.add_argument("--dry-run", action="store_true", help="report only, do not write")
|
||||
parser.add_argument("--dsn", default=default_dsn(), help="PostgreSQL DSN")
|
||||
return run(parser.parse_args(argv))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,66 @@
|
||||
"""Lightweight recurring ingestion scheduler.
|
||||
|
||||
Runs one ingestion cycle (incremental OFF update, then dedup) on a fixed
|
||||
interval. Dependency-free: a plain sleep loop rather than a cron/APScheduler
|
||||
dependency, so it is trivial to run in a container or under systemd/supervisor.
|
||||
|
||||
Usage:
|
||||
python -m opengoods.jobs.schedule --once # single cycle, then exit
|
||||
python -m opengoods.jobs.schedule --interval 3600 # every hour
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import sys
|
||||
import time
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from opengoods.etl.load import default_dsn
|
||||
from opengoods.jobs import dedup as dedup_job
|
||||
from opengoods.jobs import update_off as update_job
|
||||
|
||||
|
||||
def _cycle(args: argparse.Namespace) -> None:
|
||||
ts = datetime.now(UTC).isoformat(timespec="seconds")
|
||||
print(f"[{ts}] cycle start")
|
||||
update_job.run(
|
||||
argparse.Namespace(
|
||||
since=None,
|
||||
page_size=args.page_size,
|
||||
max_pages=args.max_pages,
|
||||
min_interval=args.min_interval,
|
||||
dsn=args.dsn,
|
||||
)
|
||||
)
|
||||
if not args.skip_dedup:
|
||||
dedup_job.run(argparse.Namespace(actor="scheduler", dry_run=False, dsn=args.dsn))
|
||||
|
||||
|
||||
def run(args: argparse.Namespace) -> int:
|
||||
_cycle(args)
|
||||
if args.once:
|
||||
return 0
|
||||
while True:
|
||||
time.sleep(args.interval)
|
||||
try:
|
||||
_cycle(args)
|
||||
except Exception as exc: # noqa: BLE001 - keep the loop alive across failures
|
||||
print(f"cycle error: {exc}", file=sys.stderr)
|
||||
return 0
|
||||
|
||||
|
||||
def main(argv: list[str] | None = None) -> int:
|
||||
parser = argparse.ArgumentParser(description="Recurring OpenGoods ingestion")
|
||||
parser.add_argument("--interval", type=int, default=3600, help="seconds between cycles")
|
||||
parser.add_argument("--once", action="store_true", help="run a single cycle and exit")
|
||||
parser.add_argument("--skip-dedup", action="store_true", help="run update only")
|
||||
parser.add_argument("--page-size", type=int, default=100, help="search page size")
|
||||
parser.add_argument("--max-pages", type=int, default=10, help="max pages to scan")
|
||||
parser.add_argument("--min-interval", type=float, default=4.0, help="API throttle seconds")
|
||||
parser.add_argument("--dsn", default=default_dsn(), help="PostgreSQL DSN")
|
||||
return run(parser.parse_args(argv))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,66 @@
|
||||
"""Seed the database with Open Food Facts data.
|
||||
|
||||
Usage:
|
||||
# from a list of barcodes via the OFF API
|
||||
python -m opengoods.jobs.seed_off --barcodes 3017624010701 5449000000996
|
||||
|
||||
# from a downloaded OFF JSONL dump (optionally .gz), limited to N records
|
||||
python -m opengoods.jobs.seed_off --dump products.jsonl.gz --limit 1000
|
||||
|
||||
The OFF read API is rate-limited client-side; for large imports use a dump.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import sys
|
||||
from collections.abc import Iterator
|
||||
|
||||
import psycopg
|
||||
|
||||
from opengoods.adapters.openfoodfacts import OpenFoodFactsAdapter, read_dump
|
||||
from opengoods.etl.load import default_dsn, ensure_source, load_record
|
||||
from opengoods.etl.transform import transform
|
||||
|
||||
|
||||
def _raw_records(args: argparse.Namespace) -> Iterator[dict]:
|
||||
if args.dump:
|
||||
records = read_dump(args.dump)
|
||||
else:
|
||||
adapter = OpenFoodFactsAdapter(min_interval=args.min_interval)
|
||||
records = adapter.fetch(args.barcodes)
|
||||
for i, rec in enumerate(records):
|
||||
if args.limit and i >= args.limit:
|
||||
break
|
||||
yield rec
|
||||
|
||||
|
||||
def run(args: argparse.Namespace) -> int:
|
||||
loaded = skipped = 0
|
||||
with psycopg.connect(args.dsn, autocommit=False) as conn:
|
||||
source_id = ensure_source(conn)
|
||||
for raw in _raw_records(args):
|
||||
rec = transform(raw)
|
||||
if rec is None:
|
||||
skipped += 1
|
||||
continue
|
||||
load_record(conn, rec, source_id, raw)
|
||||
loaded += 1
|
||||
conn.commit()
|
||||
print(f"loaded={loaded} skipped={skipped}")
|
||||
return 0
|
||||
|
||||
|
||||
def main(argv: list[str] | None = None) -> int:
|
||||
parser = argparse.ArgumentParser(description="Seed OpenGoods from Open Food Facts")
|
||||
src = parser.add_mutually_exclusive_group(required=True)
|
||||
src.add_argument("--barcodes", nargs="+", help="barcodes to fetch via the OFF API")
|
||||
src.add_argument("--dump", help="path to an OFF JSONL dump (.jsonl or .jsonl.gz)")
|
||||
parser.add_argument("--limit", type=int, default=0, help="max records to load (0 = all)")
|
||||
parser.add_argument("--min-interval", type=float, default=4.0, help="API throttle seconds")
|
||||
parser.add_argument("--dsn", default=default_dsn(), help="PostgreSQL DSN")
|
||||
return run(parser.parse_args(argv))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,65 @@
|
||||
"""Incremental Open Food Facts update.
|
||||
|
||||
Fetches products modified since the persisted watermark, loads them, then
|
||||
advances the watermark to the newest ``last_modified_t`` processed so the next
|
||||
run only sees what changed.
|
||||
|
||||
Usage:
|
||||
python -m opengoods.jobs.update_off --max-pages 5
|
||||
python -m opengoods.jobs.update_off --since 1700000000 # override watermark
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import sys
|
||||
|
||||
import psycopg
|
||||
|
||||
from opengoods.adapters.openfoodfacts import SOURCE_NAME, OpenFoodFactsAdapter
|
||||
from opengoods.etl.load import default_dsn, ensure_source, load_record
|
||||
from opengoods.etl.state import get_watermark, set_watermark
|
||||
from opengoods.etl.transform import transform
|
||||
|
||||
|
||||
def run(args: argparse.Namespace) -> int:
|
||||
adapter = OpenFoodFactsAdapter(min_interval=args.min_interval)
|
||||
loaded = skipped = 0
|
||||
high_watermark = 0
|
||||
with psycopg.connect(args.dsn, autocommit=False) as conn:
|
||||
source_id = ensure_source(conn)
|
||||
since = args.since if args.since is not None else get_watermark(conn, SOURCE_NAME)
|
||||
high_watermark = since
|
||||
for raw in adapter.fetch_modified_since(
|
||||
since, page_size=args.page_size, max_pages=args.max_pages
|
||||
):
|
||||
high_watermark = max(high_watermark, int(raw.get("last_modified_t") or 0))
|
||||
rec = transform(raw)
|
||||
if rec is None:
|
||||
skipped += 1
|
||||
continue
|
||||
load_record(conn, rec, source_id, raw)
|
||||
loaded += 1
|
||||
set_watermark(
|
||||
conn,
|
||||
SOURCE_NAME,
|
||||
high_watermark,
|
||||
stats={"loaded": loaded, "skipped": skipped, "since": since},
|
||||
)
|
||||
conn.commit()
|
||||
print(f"since={since} loaded={loaded} skipped={skipped} watermark={high_watermark}")
|
||||
return 0
|
||||
|
||||
|
||||
def main(argv: list[str] | None = None) -> int:
|
||||
parser = argparse.ArgumentParser(description="Incremental OFF update")
|
||||
parser.add_argument("--since", type=int, default=None, help="override watermark (unix ts)")
|
||||
parser.add_argument("--page-size", type=int, default=100, help="search page size")
|
||||
parser.add_argument("--max-pages", type=int, default=10, help="max pages to scan")
|
||||
parser.add_argument("--min-interval", type=float, default=4.0, help="API throttle seconds")
|
||||
parser.add_argument("--dsn", default=default_dsn(), help="PostgreSQL DSN")
|
||||
return run(parser.parse_args(argv))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -5,6 +5,7 @@ description = "OpenGoods (天工·商品标签) ingestion & ETL: collect product
|
||||
requires-python = ">=3.11"
|
||||
dependencies = [
|
||||
"httpx>=0.27",
|
||||
"psycopg[binary]>=3.2",
|
||||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
|
||||
@@ -0,0 +1,31 @@
|
||||
"""Shared test fixtures.
|
||||
|
||||
`db_conn` yields a psycopg connection inside a transaction that is rolled back
|
||||
after each test, so DB tests stay isolated and leave no residue. Tests are
|
||||
skipped automatically when no database is reachable or M4 migrations are not
|
||||
applied (e.g. local runs without docker).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import psycopg
|
||||
import pytest
|
||||
|
||||
from opengoods.etl.load import default_dsn
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def db_conn():
|
||||
try:
|
||||
conn = psycopg.connect(default_dsn(), connect_timeout=3)
|
||||
except psycopg.OperationalError as exc: # pragma: no cover - env dependent
|
||||
pytest.skip(f"no database available: {exc}")
|
||||
has_state = conn.execute("SELECT to_regclass('public.ingest_state') IS NOT NULL").fetchone()[0]
|
||||
if not has_state:
|
||||
conn.close()
|
||||
pytest.skip("M4 migrations not applied")
|
||||
try:
|
||||
yield conn
|
||||
finally:
|
||||
conn.rollback()
|
||||
conn.close()
|
||||
+14
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"06901234567892": {
|
||||
"name": "示例矿泉水 550ml",
|
||||
"brand": "示例品牌",
|
||||
"manufacturer": "示例饮品有限公司",
|
||||
"gpc_brick_code": "10000224",
|
||||
"country_of_origin": "China",
|
||||
"net_content_value": 550,
|
||||
"net_content_unit": "ml"
|
||||
},
|
||||
"00000000000000": {
|
||||
"brand": ""
|
||||
}
|
||||
}
|
||||
+26
@@ -0,0 +1,26 @@
|
||||
{
|
||||
"code": "3017624010701",
|
||||
"product_name": "Nutella",
|
||||
"product_name_en": "Nutella hazelnut spread",
|
||||
"brands": "Ferrero, Nutella",
|
||||
"quantity": "400 g",
|
||||
"countries": "France, China",
|
||||
"categories": "Spreads, Hazelnut spreads, Chocolate spreads",
|
||||
"categories_tags": ["en:spreads", "en:chocolate-spreads"],
|
||||
"ingredients_text": "Sugar, palm oil, hazelnuts, cocoa, skimmed milk powder",
|
||||
"allergens_tags": ["en:milk", "en:nuts"],
|
||||
"additives_tags": ["en:e322"],
|
||||
"serving_size": "15 g",
|
||||
"nutriscore_grade": "e",
|
||||
"image_front_url": "https://images.openfoodfacts.org/images/products/301/762/401/0701/front_en.jpg",
|
||||
"nutriments": {
|
||||
"energy-kj_100g": 2252,
|
||||
"energy-kcal_100g": 539,
|
||||
"fat_100g": 30.9,
|
||||
"saturated-fat_100g": 10.6,
|
||||
"carbohydrates_100g": 57.5,
|
||||
"sugars_100g": 56.3,
|
||||
"proteins_100g": 6.3,
|
||||
"salt_100g": 0.107
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,62 @@
|
||||
from opengoods.etl.dedup import choose_canonical, dedup_all, product_signature
|
||||
from opengoods.etl.load import _ensure_brand, ensure_source
|
||||
|
||||
|
||||
def test_product_signature_normalization():
|
||||
a = product_signature(" Spring Water ", "Acme", 500)
|
||||
b = product_signature("spring water", "acme", 500)
|
||||
assert a == b
|
||||
assert product_signature("", "x", 1) is None
|
||||
|
||||
|
||||
def test_choose_canonical_prefers_quality():
|
||||
members = [
|
||||
{"id": "a", "quality_score": 0.2, "created_at": 1},
|
||||
{"id": "b", "quality_score": 0.9, "created_at": 2},
|
||||
]
|
||||
assert choose_canonical(members)["id"] == "b"
|
||||
|
||||
|
||||
def test_dedup_merges_duplicates(db_conn):
|
||||
brand_id = _ensure_brand(db_conn, "DupBrand")
|
||||
|
||||
def mk(quality):
|
||||
return db_conn.execute(
|
||||
"""
|
||||
INSERT INTO product (name, brand_id, net_content_canonical, quality_score)
|
||||
VALUES (%s, %s, %s, %s) RETURNING id
|
||||
""",
|
||||
("Dup Snack", brand_id, 100, quality),
|
||||
).fetchone()[0]
|
||||
|
||||
keep = mk(0.9)
|
||||
drop = mk(0.2)
|
||||
|
||||
src = ensure_source(db_conn)
|
||||
db_conn.execute(
|
||||
"INSERT INTO product_source (product_id, source_id, fields) VALUES (%s, %s, %s)",
|
||||
(drop, src, ["name"]),
|
||||
)
|
||||
|
||||
summary = dedup_all(db_conn)
|
||||
assert summary == {"groups": 1, "merged": 1}
|
||||
|
||||
keep_status = db_conn.execute("SELECT status FROM product WHERE id = %s", (keep,)).fetchone()[0]
|
||||
drop_status, canonical_id = db_conn.execute(
|
||||
"SELECT status, canonical_id FROM product WHERE id = %s", (drop,)
|
||||
).fetchone()
|
||||
assert keep_status == "active"
|
||||
assert drop_status == "merged"
|
||||
assert str(canonical_id) == str(keep)
|
||||
|
||||
# The merged product's source row was re-pointed to the canonical product.
|
||||
reattached = db_conn.execute(
|
||||
"SELECT count(*) FROM product_source WHERE product_id = %s", (keep,)
|
||||
).fetchone()[0]
|
||||
assert reattached == 1
|
||||
|
||||
logged = db_conn.execute(
|
||||
"SELECT count(*) FROM merge_log WHERE kept_id = %s AND merged_id = %s",
|
||||
(keep, drop),
|
||||
).fetchone()[0]
|
||||
assert logged == 1
|
||||
@@ -0,0 +1,53 @@
|
||||
from pathlib import Path
|
||||
|
||||
from opengoods.adapters.gs1 import GS1Adapter
|
||||
from opengoods.etl.supplement import apply_supplement, ensure_gs1_source
|
||||
|
||||
MAPPING = Path(__file__).parent / "fixtures" / "gs1_mapping.json"
|
||||
GTIN = "06901234567892"
|
||||
|
||||
|
||||
def test_gs1_adapter_offline_lookup():
|
||||
adapter = GS1Adapter.from_file(MAPPING)
|
||||
rec = adapter.fetch_barcode(GTIN)
|
||||
assert rec["brand"] == "示例品牌"
|
||||
assert rec["net_content_value"] == 550
|
||||
assert rec["net_content_unit"] == "ml"
|
||||
# An entry that only has empty values yields no supplement.
|
||||
assert adapter.fetch_barcode("00000000000000") is None
|
||||
# Unknown barcode -> None.
|
||||
assert adapter.fetch_barcode("99999999999999") is None
|
||||
|
||||
|
||||
def test_gs1_supplement_fills_only_gaps(db_conn):
|
||||
pid = db_conn.execute(
|
||||
"INSERT INTO product (gtin, name) VALUES (%s, %s) RETURNING id", (GTIN, "水")
|
||||
).fetchone()[0]
|
||||
|
||||
adapter = GS1Adapter.from_file(MAPPING)
|
||||
rec = adapter.fetch_barcode(GTIN)
|
||||
source_id = ensure_gs1_source(db_conn)
|
||||
|
||||
filled = apply_supplement(db_conn, rec, source_id)
|
||||
assert {"brand", "country_of_origin", "net_content"} <= set(filled)
|
||||
|
||||
brand_id, country, net_value, net_unit = db_conn.execute(
|
||||
"""
|
||||
SELECT brand_id, country_of_origin, net_content_value, net_content_unit
|
||||
FROM product WHERE id = %s
|
||||
""",
|
||||
(pid,),
|
||||
).fetchone()
|
||||
assert brand_id is not None
|
||||
assert country == "China"
|
||||
assert float(net_value) == 550.0
|
||||
assert net_unit == "ml"
|
||||
|
||||
fields = db_conn.execute(
|
||||
"SELECT fields FROM product_source WHERE product_id = %s AND source_id = %s",
|
||||
(pid, source_id),
|
||||
).fetchone()[0]
|
||||
assert "brand" in fields
|
||||
|
||||
# Re-applying does nothing because the gaps are now filled.
|
||||
assert apply_supplement(db_conn, rec, source_id) == []
|
||||
@@ -0,0 +1,61 @@
|
||||
"""Integration test for the DB loader.
|
||||
|
||||
Skipped automatically when no database is reachable (e.g. local runs without
|
||||
docker, or CI jobs without a postgres service). Requires migrations applied.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from opengoods.etl.load import default_dsn, ensure_source, load_record
|
||||
from opengoods.etl.transform import transform
|
||||
|
||||
psycopg = pytest.importorskip("psycopg")
|
||||
|
||||
FIXTURE = json.loads((Path(__file__).parent / "fixtures" / "off_product.json").read_text())
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def conn():
|
||||
try:
|
||||
c = psycopg.connect(default_dsn(), connect_timeout=3)
|
||||
except psycopg.OperationalError as exc: # pragma: no cover - env dependent
|
||||
pytest.skip(f"no database available: {exc}")
|
||||
# ensure schema present
|
||||
has_product = c.execute("SELECT to_regclass('public.product') IS NOT NULL").fetchone()[0]
|
||||
if not has_product:
|
||||
c.close()
|
||||
pytest.skip("migrations not applied")
|
||||
yield c
|
||||
c.rollback()
|
||||
c.close()
|
||||
|
||||
|
||||
def test_load_record_roundtrip(conn):
|
||||
source_id = ensure_source(conn)
|
||||
rec = transform(FIXTURE)
|
||||
product_id = load_record(conn, rec, source_id, FIXTURE)
|
||||
|
||||
row = conn.execute(
|
||||
"SELECT name, gtin, net_content_unit FROM product WHERE id = %s", (product_id,)
|
||||
).fetchone()
|
||||
assert row[0] == "Nutella"
|
||||
assert row[1] == "3017624010701"
|
||||
assert row[2] == "g"
|
||||
|
||||
nutri = conn.execute(
|
||||
"SELECT nutriments ->> 'energy_kcal' FROM food_detail WHERE product_id = %s",
|
||||
(product_id,),
|
||||
).fetchone()
|
||||
assert nutri[0] == "539.0"
|
||||
|
||||
prov = conn.execute(
|
||||
"SELECT count(*) FROM product_source WHERE product_id = %s", (product_id,)
|
||||
).fetchone()
|
||||
assert prov[0] >= 1
|
||||
|
||||
conn.rollback() # keep the test DB clean
|
||||
@@ -0,0 +1,62 @@
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from opengoods.etl.merge import Candidate, merge_records, resolve_field
|
||||
|
||||
|
||||
def _ts(y, m, d):
|
||||
return datetime(y, m, d, tzinfo=UTC)
|
||||
|
||||
|
||||
def test_resolve_field_prefers_trust_then_recency():
|
||||
cands = [
|
||||
Candidate(value="A", source="off", trust=0.7, fetched_at=_ts(2024, 1, 1)),
|
||||
Candidate(value="B", source="gs1", trust=0.9, fetched_at=_ts(2023, 1, 1)),
|
||||
]
|
||||
res = resolve_field(cands)
|
||||
assert res is not None
|
||||
assert res.value == "B"
|
||||
assert res.source == "gs1"
|
||||
|
||||
|
||||
def test_resolve_field_recency_tiebreak_on_equal_trust():
|
||||
cands = [
|
||||
Candidate(value="old", source="a", trust=0.7, fetched_at=_ts(2023, 1, 1)),
|
||||
Candidate(value="new", source="b", trust=0.7, fetched_at=_ts(2024, 6, 1)),
|
||||
]
|
||||
assert resolve_field(cands).value == "new"
|
||||
|
||||
|
||||
def test_resolve_field_skips_empty():
|
||||
cands = [
|
||||
Candidate(value="", source="a", trust=0.99),
|
||||
Candidate(value=None, source="b", trust=0.99),
|
||||
Candidate(value="kept", source="c", trust=0.1),
|
||||
]
|
||||
assert resolve_field(cands).value == "kept"
|
||||
assert resolve_field([Candidate(value="", source="a")]) is None
|
||||
|
||||
|
||||
def test_merge_records_provenance():
|
||||
records = [
|
||||
{
|
||||
"name": Candidate("Water", "off", 0.7, _ts(2024, 1, 1)),
|
||||
"brand": Candidate("", "off", 0.7),
|
||||
},
|
||||
{
|
||||
"brand": Candidate("Acme", "gs1", 0.9, _ts(2024, 2, 1)),
|
||||
"gtin": Candidate("123", "gs1", 0.9),
|
||||
},
|
||||
]
|
||||
merged = merge_records(records)
|
||||
assert merged.values["name"] == "Water"
|
||||
assert merged.values["brand"] == "Acme"
|
||||
assert merged.values["gtin"] == "123"
|
||||
assert merged.provenance["brand"] == "gs1"
|
||||
assert merged.provenance["name"] == "off"
|
||||
|
||||
|
||||
def test_merge_records_accepts_bare_values():
|
||||
merged = merge_records([{"x": 1}, {"x": 2}])
|
||||
# both bare -> trust tie, no timestamps -> first max() wins deterministically
|
||||
assert merged.values["x"] in (1, 2)
|
||||
assert merged.provenance["x"] == "unknown"
|
||||
@@ -0,0 +1,44 @@
|
||||
import httpx
|
||||
|
||||
from opengoods.adapters.openfoodfacts import OpenFoodFactsAdapter
|
||||
|
||||
|
||||
def _product(code, lm):
|
||||
return {"code": code, "product_name": f"P{code}", "last_modified_t": lm}
|
||||
|
||||
|
||||
def _adapter(pages):
|
||||
"""Build an adapter whose search endpoint serves the given pages."""
|
||||
|
||||
def handler(request: httpx.Request) -> httpx.Response:
|
||||
page = int(request.url.params.get("page", "1"))
|
||||
products = pages.get(page, [])
|
||||
return httpx.Response(200, json={"products": products, "page": page})
|
||||
|
||||
client = httpx.Client(transport=httpx.MockTransport(handler))
|
||||
return OpenFoodFactsAdapter(client=client, min_interval=0)
|
||||
|
||||
|
||||
def test_incremental_yields_only_newer_and_stops_at_watermark():
|
||||
pages = {
|
||||
1: [_product("1", 300), _product("2", 250), _product("3", 100)],
|
||||
}
|
||||
adapter = _adapter(pages)
|
||||
got = list(adapter.fetch_modified_since(200, page_size=3, max_pages=5))
|
||||
codes = [p["code"] for p in got]
|
||||
assert codes == ["1", "2"] # 100 <= 200 stops iteration
|
||||
|
||||
|
||||
def test_incremental_paginates_until_short_page():
|
||||
pages = {
|
||||
1: [_product("1", 900), _product("2", 800)],
|
||||
2: [_product("3", 700)], # short page -> stop after
|
||||
}
|
||||
adapter = _adapter(pages)
|
||||
got = list(adapter.fetch_modified_since(0, page_size=2, max_pages=5))
|
||||
assert [p["code"] for p in got] == ["1", "2", "3"]
|
||||
|
||||
|
||||
def test_incremental_empty_first_page():
|
||||
adapter = _adapter({1: []})
|
||||
assert list(adapter.fetch_modified_since(0, page_size=10, max_pages=3)) == []
|
||||
@@ -0,0 +1,38 @@
|
||||
from opengoods.etl.quality import (
|
||||
COMPLETENESS_FIELDS,
|
||||
agreement_from_sources,
|
||||
completeness,
|
||||
freshness_from_age,
|
||||
score,
|
||||
)
|
||||
|
||||
|
||||
def test_completeness_bounds():
|
||||
assert completeness(set()) == 0.0
|
||||
assert completeness(set(COMPLETENESS_FIELDS)) == 1.0
|
||||
half = set(list(COMPLETENESS_FIELDS)[: len(COMPLETENESS_FIELDS) // 2])
|
||||
assert 0.0 < completeness(half) < 1.0
|
||||
|
||||
|
||||
def test_agreement_from_sources():
|
||||
assert agreement_from_sources(0) == 0.5
|
||||
assert agreement_from_sources(1) == 0.5
|
||||
assert agreement_from_sources(2) == 0.8
|
||||
assert agreement_from_sources(5) == 1.0
|
||||
|
||||
|
||||
def test_freshness_from_age():
|
||||
assert freshness_from_age(None) == 0.5
|
||||
assert freshness_from_age(1) == 1.0
|
||||
assert freshness_from_age(100) == 0.8
|
||||
assert freshness_from_age(300) == 0.6
|
||||
assert freshness_from_age(700) == 0.4
|
||||
assert freshness_from_age(5000) == 0.2
|
||||
|
||||
|
||||
def test_score_weighted_sum_and_bounds():
|
||||
assert score(completeness_score=0, source_trust=0, agreement=0, freshness=0) == 0.0
|
||||
assert score(completeness_score=1, source_trust=1, agreement=1, freshness=1) == 1.0
|
||||
# 0.4*1 + 0.3*0.5 + 0.2*0.5 + 0.1*1 = 0.75
|
||||
got = score(completeness_score=1.0, source_trust=0.5, agreement=0.5, freshness=1.0)
|
||||
assert got == 0.75
|
||||
@@ -0,0 +1,21 @@
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
from opengoods.etl.load import ensure_source, load_record
|
||||
from opengoods.etl.quality import compute_quality
|
||||
from opengoods.etl.transform import transform
|
||||
|
||||
FIXTURE = json.loads((Path(__file__).parent / "fixtures" / "off_product.json").read_text())
|
||||
|
||||
|
||||
def test_quality_score_set_on_load(db_conn):
|
||||
source_id = ensure_source(db_conn)
|
||||
rec = transform(FIXTURE)
|
||||
pid = load_record(db_conn, rec, source_id, FIXTURE)
|
||||
|
||||
stored = float(
|
||||
db_conn.execute("SELECT quality_score FROM product WHERE id = %s", (pid,)).fetchone()[0]
|
||||
)
|
||||
assert 0.0 < stored <= 1.0
|
||||
# The persisted value matches a fresh recomputation.
|
||||
assert abs(stored - compute_quality(db_conn, pid)) < 1e-9
|
||||
@@ -0,0 +1,16 @@
|
||||
from opengoods.etl.state import get_watermark, set_watermark
|
||||
|
||||
|
||||
def test_watermark_roundtrip_and_monotonic(db_conn):
|
||||
src = "test-source"
|
||||
assert get_watermark(db_conn, src) == 0
|
||||
|
||||
set_watermark(db_conn, src, 100, stats={"loaded": 1})
|
||||
assert get_watermark(db_conn, src) == 100
|
||||
|
||||
# A lower watermark must not rewind progress.
|
||||
set_watermark(db_conn, src, 50)
|
||||
assert get_watermark(db_conn, src) == 100
|
||||
|
||||
set_watermark(db_conn, src, 150)
|
||||
assert get_watermark(db_conn, src) == 150
|
||||
@@ -0,0 +1,67 @@
|
||||
import json
|
||||
from decimal import Decimal
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from opengoods.etl.transform import (
|
||||
is_valid_gtin,
|
||||
map_category,
|
||||
parse_quantity,
|
||||
transform,
|
||||
transform_nutriments,
|
||||
)
|
||||
|
||||
FIXTURE = json.loads((Path(__file__).parent / "fixtures" / "off_product.json").read_text())
|
||||
|
||||
|
||||
def test_is_valid_gtin():
|
||||
assert is_valid_gtin("3017624010701") # real EAN-13
|
||||
assert is_valid_gtin("5449000000996") # Coca-Cola
|
||||
assert not is_valid_gtin("3017624010700") # bad check digit
|
||||
assert not is_valid_gtin("123")
|
||||
assert not is_valid_gtin("notanumber")
|
||||
|
||||
|
||||
def test_parse_quantity():
|
||||
assert parse_quantity("400 g") == (Decimal("400"), "g")
|
||||
assert parse_quantity("1,5 L") == (Decimal("1.5"), "L")
|
||||
assert parse_quantity("") is None
|
||||
assert parse_quantity("family size") is None
|
||||
|
||||
|
||||
def test_map_category():
|
||||
assert map_category({"product_name": "Spring Water"}) == "food.beverages.water"
|
||||
assert map_category({"categories": "Dark chocolate"}) == "food.snacks.chocolate"
|
||||
assert map_category({"product_name": "Mystery"}) is None
|
||||
|
||||
|
||||
def test_transform_nutriments_dual_energy():
|
||||
out = transform_nutriments(FIXTURE["nutriments"])
|
||||
assert out["energy_kj"] == 2252.0
|
||||
assert out["energy_kcal"] == 539.0
|
||||
assert out["fat"] == 30.9
|
||||
assert out["salt"] == 0.107
|
||||
|
||||
|
||||
def test_transform_nutriments_fills_missing_energy():
|
||||
out = transform_nutriments({"energy-kcal_100g": 100})
|
||||
assert out["energy_kj"] == pytest.approx(418.4)
|
||||
|
||||
|
||||
def test_transform_full_record():
|
||||
rec = transform(FIXTURE)
|
||||
assert rec is not None
|
||||
assert rec["gtin"] == "3017624010701"
|
||||
assert rec["name"] == "Nutella"
|
||||
assert rec["brand"] == "Ferrero"
|
||||
assert rec["net_content_unit"] == "g"
|
||||
assert rec["net_content_canonical"] == Decimal("400")
|
||||
assert rec["country_of_origin"] == "France"
|
||||
assert rec["food"]["nutri_score"] == "E"
|
||||
assert "milk" in rec["food"]["allergens"]
|
||||
assert rec["image_url"].endswith(".jpg")
|
||||
|
||||
|
||||
def test_transform_drops_unnamed():
|
||||
assert transform({"code": "0000000000000"}) is None
|
||||
@@ -0,0 +1,21 @@
|
||||
DROP TRIGGER IF EXISTS trg_product_sync ON product;
|
||||
DROP FUNCTION IF EXISTS product_sync_tsv();
|
||||
|
||||
DROP TABLE IF EXISTS merge_log;
|
||||
DROP TABLE IF EXISTS product_source;
|
||||
DROP TABLE IF EXISTS product_image;
|
||||
DROP TABLE IF EXISTS product_msrp;
|
||||
DROP TABLE IF EXISTS food_detail;
|
||||
DROP TABLE IF EXISTS product;
|
||||
DROP TABLE IF EXISTS attribute_definition;
|
||||
DROP TABLE IF EXISTS unit;
|
||||
DROP TABLE IF EXISTS category_schema;
|
||||
DROP TABLE IF EXISTS category;
|
||||
DROP TABLE IF EXISTS manufacturer;
|
||||
DROP TABLE IF EXISTS brand;
|
||||
DROP TABLE IF EXISTS source;
|
||||
|
||||
DROP EXTENSION IF EXISTS ltree;
|
||||
DROP EXTENSION IF EXISTS pg_trgm;
|
||||
-- keep pgcrypto (commonly shared); drop only if you are sure:
|
||||
-- DROP EXTENSION IF EXISTS pgcrypto;
|
||||
@@ -0,0 +1,182 @@
|
||||
-- OpenGoods (天工·商品标签) initial schema.
|
||||
-- Public-good product information store: facts only, no commerce.
|
||||
|
||||
CREATE EXTENSION IF NOT EXISTS pgcrypto; -- gen_random_uuid()
|
||||
CREATE EXTENSION IF NOT EXISTS pg_trgm; -- fuzzy name search
|
||||
CREATE EXTENSION IF NOT EXISTS ltree; -- category subtree queries
|
||||
|
||||
-- Data sources (Open Food Facts / USDA / GS1 ...) with trust + license.
|
||||
CREATE TABLE source (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
name TEXT NOT NULL,
|
||||
homepage TEXT,
|
||||
license TEXT,
|
||||
trust_weight NUMERIC(3,2) NOT NULL DEFAULT 0.5,
|
||||
notes TEXT,
|
||||
UNIQUE (name)
|
||||
);
|
||||
|
||||
CREATE TABLE brand (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
name TEXT NOT NULL,
|
||||
normalized_name TEXT NOT NULL,
|
||||
aliases TEXT[] NOT NULL DEFAULT '{}',
|
||||
UNIQUE (normalized_name)
|
||||
);
|
||||
|
||||
CREATE TABLE manufacturer (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
name TEXT NOT NULL,
|
||||
normalized_name TEXT NOT NULL,
|
||||
country VARCHAR(64),
|
||||
UNIQUE (normalized_name)
|
||||
);
|
||||
|
||||
-- Self-built category tree, each node optionally mapped to a GS1 GPC brick.
|
||||
CREATE TABLE category (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
name_zh TEXT NOT NULL,
|
||||
name_en TEXT,
|
||||
parent_id UUID REFERENCES category(id),
|
||||
path LTREE NOT NULL,
|
||||
gpc_brick_code VARCHAR(10),
|
||||
level INT NOT NULL DEFAULT 0,
|
||||
UNIQUE (path)
|
||||
);
|
||||
|
||||
-- Parameter template / constraints per category.
|
||||
CREATE TABLE category_schema (
|
||||
category_id UUID PRIMARY KEY REFERENCES category(id) ON DELETE CASCADE,
|
||||
required_attributes TEXT[] NOT NULL DEFAULT '{}',
|
||||
recommended_attributes TEXT[] NOT NULL DEFAULT '{}',
|
||||
nutriment_basis VARCHAR(16)
|
||||
);
|
||||
|
||||
-- Unit dictionary: each unit maps to a canonical unit within its dimension.
|
||||
CREATE TABLE unit (
|
||||
code VARCHAR(16) PRIMARY KEY,
|
||||
dimension VARCHAR(16) NOT NULL,
|
||||
canonical VARCHAR(16) NOT NULL,
|
||||
to_canonical_factor NUMERIC,
|
||||
aliases TEXT[] NOT NULL DEFAULT '{}',
|
||||
display TEXT
|
||||
);
|
||||
|
||||
-- Parameter dictionary: standard attribute keys with default unit.
|
||||
CREATE TABLE attribute_definition (
|
||||
key VARCHAR(64) PRIMARY KEY,
|
||||
label_zh TEXT,
|
||||
label_en TEXT,
|
||||
dimension VARCHAR(16),
|
||||
default_unit VARCHAR(16) REFERENCES unit(code),
|
||||
aliases TEXT[] NOT NULL DEFAULT '{}'
|
||||
);
|
||||
|
||||
CREATE TABLE product (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
gtin VARCHAR(14),
|
||||
name TEXT NOT NULL,
|
||||
brand_id UUID REFERENCES brand(id),
|
||||
manufacturer_id UUID REFERENCES manufacturer(id),
|
||||
category_id UUID REFERENCES category(id),
|
||||
gpc_brick_code VARCHAR(10),
|
||||
net_content_value NUMERIC,
|
||||
net_content_unit VARCHAR(16),
|
||||
net_content_canonical NUMERIC,
|
||||
country_of_origin VARCHAR(64),
|
||||
shelf_life_days INT,
|
||||
storage TEXT,
|
||||
attributes JSONB NOT NULL DEFAULT '{}',
|
||||
quality_score NUMERIC(4,3) NOT NULL DEFAULT 0,
|
||||
status VARCHAR(16) NOT NULL DEFAULT 'active',
|
||||
canonical_id UUID REFERENCES product(id),
|
||||
search_tsv TSVECTOR,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
|
||||
updated_at TIMESTAMPTZ NOT NULL DEFAULT now(),
|
||||
CONSTRAINT product_status_chk CHECK (status IN ('active','merged','deprecated')),
|
||||
CONSTRAINT product_quality_chk CHECK (quality_score >= 0 AND quality_score <= 1)
|
||||
);
|
||||
|
||||
CREATE TABLE food_detail (
|
||||
product_id UUID PRIMARY KEY REFERENCES product(id) ON DELETE CASCADE,
|
||||
ingredients_text TEXT,
|
||||
ingredients JSONB,
|
||||
allergens TEXT[] NOT NULL DEFAULT '{}',
|
||||
additives TEXT[] NOT NULL DEFAULT '{}',
|
||||
nutriments JSONB,
|
||||
nutrition_basis VARCHAR(16),
|
||||
serving_size VARCHAR(32),
|
||||
nutri_score CHAR(1),
|
||||
labels TEXT[] NOT NULL DEFAULT '{}',
|
||||
CONSTRAINT food_basis_chk CHECK (nutrition_basis IS NULL OR nutrition_basis IN ('per_100g','per_100ml','per_serving'))
|
||||
);
|
||||
|
||||
-- Official manufacturer-suggested retail price snapshot (no purchase link).
|
||||
CREATE TABLE product_msrp (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
product_id UUID NOT NULL REFERENCES product(id) ON DELETE CASCADE,
|
||||
amount NUMERIC(12,2) NOT NULL,
|
||||
currency CHAR(3) NOT NULL,
|
||||
region VARCHAR(8) NOT NULL DEFAULT 'CN',
|
||||
source_id UUID REFERENCES source(id),
|
||||
source_url TEXT,
|
||||
effective_date DATE,
|
||||
note TEXT,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
|
||||
);
|
||||
|
||||
CREATE TABLE product_image (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
product_id UUID NOT NULL REFERENCES product(id) ON DELETE CASCADE,
|
||||
url TEXT NOT NULL,
|
||||
kind VARCHAR(16) NOT NULL DEFAULT 'other',
|
||||
license TEXT,
|
||||
source_id UUID REFERENCES source(id),
|
||||
CONSTRAINT image_kind_chk CHECK (kind IN ('front','ingredients','nutrition','other'))
|
||||
);
|
||||
|
||||
-- Field-level provenance: which source provided which fields.
|
||||
CREATE TABLE product_source (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
product_id UUID NOT NULL REFERENCES product(id) ON DELETE CASCADE,
|
||||
source_id UUID REFERENCES source(id),
|
||||
url TEXT,
|
||||
fields TEXT[] NOT NULL DEFAULT '{}',
|
||||
fetched_at TIMESTAMPTZ,
|
||||
raw JSONB
|
||||
);
|
||||
|
||||
CREATE TABLE merge_log (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
kept_id UUID,
|
||||
merged_id UUID,
|
||||
reason TEXT,
|
||||
actor TEXT,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
|
||||
);
|
||||
|
||||
-- Indexes
|
||||
CREATE UNIQUE INDEX idx_product_gtin ON product (gtin) WHERE gtin IS NOT NULL;
|
||||
CREATE INDEX idx_product_name_trgm ON product USING gin (name gin_trgm_ops);
|
||||
CREATE INDEX idx_product_attrs ON product USING gin (attributes);
|
||||
CREATE INDEX idx_product_tsv ON product USING gin (search_tsv);
|
||||
CREATE INDEX idx_product_category ON product (category_id);
|
||||
CREATE INDEX idx_product_brand ON product (brand_id);
|
||||
CREATE INDEX idx_product_updated ON product (updated_at);
|
||||
CREATE INDEX idx_food_nutriments ON food_detail USING gin (nutriments);
|
||||
CREATE INDEX idx_category_path ON category USING gist (path);
|
||||
CREATE INDEX idx_msrp_product ON product_msrp (product_id);
|
||||
CREATE INDEX idx_psource_product ON product_source (product_id);
|
||||
|
||||
-- Keep search_tsv and updated_at in sync.
|
||||
CREATE OR REPLACE FUNCTION product_sync_tsv() RETURNS trigger AS $$
|
||||
BEGIN
|
||||
NEW.search_tsv := to_tsvector('simple', coalesce(NEW.name, ''));
|
||||
NEW.updated_at := now();
|
||||
RETURN NEW;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
CREATE TRIGGER trg_product_sync
|
||||
BEFORE INSERT OR UPDATE ON product
|
||||
FOR EACH ROW EXECUTE FUNCTION product_sync_tsv();
|
||||
@@ -0,0 +1,2 @@
|
||||
DELETE FROM attribute_definition;
|
||||
DELETE FROM unit;
|
||||
@@ -0,0 +1,29 @@
|
||||
-- Unit dictionary seed. Keep factors aligned with ingestion/opengoods/units.py.
|
||||
|
||||
INSERT INTO unit (code, dimension, canonical, to_canonical_factor, aliases, display) VALUES
|
||||
('mg', 'mass', 'g', 0.001, ARRAY['毫克'], 'mg'),
|
||||
('g', 'mass', 'g', 1, ARRAY['克','gram','grams'], 'g'),
|
||||
('kg', 'mass', 'g', 1000, ARRAY['kgs','千克','公斤'], 'kg'),
|
||||
('ml', 'volume', 'ml', 1, ARRAY['毫升','milliliter'], 'mL'),
|
||||
('cl', 'volume', 'ml', 10, ARRAY['厘升'], 'cL'),
|
||||
('l', 'volume', 'ml', 1000, ARRAY['L','升','litre','liter'], 'L'),
|
||||
('kj', 'energy', 'kJ', 1, ARRAY['kJ','千焦'], 'kJ'),
|
||||
('kcal', 'energy', 'kJ', 4.184, ARRAY['千卡','大卡'], 'kcal'),
|
||||
('pct', 'ratio', 'pct', 1, ARRAY['%','percent','百分比'], '%'),
|
||||
('unit', 'count', 'unit',1, ARRAY['个','件','pcs','piece'], '个'),
|
||||
('mm', 'length', 'mm', 1, ARRAY['毫米'], 'mm'),
|
||||
('cm', 'length', 'mm', 10, ARRAY['厘米'], 'cm'),
|
||||
('day', 'duration', 'day', 1, ARRAY['天','日','days'], 'day')
|
||||
ON CONFLICT (code) DO NOTHING;
|
||||
|
||||
-- A few common food attribute definitions referencing the unit dictionary.
|
||||
INSERT INTO attribute_definition (key, label_zh, label_en, dimension, default_unit, aliases) VALUES
|
||||
('energy', '能量', 'Energy', 'energy', 'kj', ARRAY['energy_kj']),
|
||||
('proteins', '蛋白质', 'Proteins', 'mass', 'g', ARRAY['protein']),
|
||||
('fat', '脂肪', 'Fat', 'mass', 'g', ARRAY['fats']),
|
||||
('saturated_fat', '饱和脂肪','Saturated fat','mass', 'g', ARRAY['saturated-fat']),
|
||||
('carbohydrates', '碳水化合物','Carbohydrates','mass', 'g', ARRAY['carbs']),
|
||||
('sugars', '糖', 'Sugars', 'mass', 'g', ARRAY['sugar']),
|
||||
('salt', '盐', 'Salt', 'mass', 'g', ARRAY['sodium_salt']),
|
||||
('net_content', '净含量', 'Net content', NULL, NULL, ARRAY['quantity'])
|
||||
ON CONFLICT (key) DO NOTHING;
|
||||
@@ -0,0 +1,3 @@
|
||||
-- remove seeded categories (children first via path depth)
|
||||
DELETE FROM category_schema;
|
||||
DELETE FROM category;
|
||||
@@ -0,0 +1,53 @@
|
||||
-- Seed a FOOD-focused category skeleton.
|
||||
-- Structure = GS1 GPC backbone (segment/family/class) mapped to a self-built
|
||||
-- Chinese tree. ltree labels are english slugs (ltree forbids spaces/CJK);
|
||||
-- Chinese names live in name_zh. gpc_brick_code on leaves is a representative
|
||||
-- starter value to be replaced by a full official GPC import later.
|
||||
|
||||
-- Root segment: Food/Beverage/Tobacco (GPC segment 50000000)
|
||||
INSERT INTO category (name_zh, name_en, parent_id, path, gpc_brick_code, level)
|
||||
VALUES ('食品饮料', 'Food/Beverage', NULL, 'food', '50000000', 0);
|
||||
|
||||
-- Families (level 1)
|
||||
INSERT INTO category (name_zh, name_en, parent_id, path, gpc_brick_code, level)
|
||||
SELECT v.name_zh, v.name_en, c.id, v.path::ltree, v.code, 1
|
||||
FROM (VALUES
|
||||
('饮料', 'Beverages', 'food.beverages', '50130000'),
|
||||
('乳制品蛋类','Dairy/Eggs', 'food.dairy', '50180000'),
|
||||
('烘焙', 'Bakery', 'food.bakery', '50100000'),
|
||||
('零食', 'Snacks', 'food.snacks', '50190000'),
|
||||
('粮油', 'Staples/Oils', 'food.staple', '50160000'),
|
||||
('调味品', 'Condiments', 'food.condiments', '50170000')
|
||||
) AS v(name_zh, name_en, path, code)
|
||||
JOIN category c ON c.path = 'food';
|
||||
|
||||
-- Classes / leaves (level 2) with representative GPC brick codes
|
||||
INSERT INTO category (name_zh, name_en, parent_id, path, gpc_brick_code, level)
|
||||
SELECT v.name_zh, v.name_en, c.id, v.path::ltree, v.code, 2
|
||||
FROM (VALUES
|
||||
('包装饮用水', 'Bottled water', 'food.beverages.water', '10000224', 'food.beverages'),
|
||||
('碳酸饮料', 'Carbonated', 'food.beverages.carbonated', '10000225', 'food.beverages'),
|
||||
('果汁', 'Juice', 'food.beverages.juice', '10000226', 'food.beverages'),
|
||||
('牛奶', 'Milk', 'food.dairy.milk', '10000158', 'food.dairy'),
|
||||
('酸奶', 'Yogurt', 'food.dairy.yogurt', '10000159', 'food.dairy'),
|
||||
('奶酪', 'Cheese', 'food.dairy.cheese', '10000160', 'food.dairy'),
|
||||
('面包', 'Bread', 'food.bakery.bread', '10000040', 'food.bakery'),
|
||||
('饼干', 'Biscuits', 'food.bakery.biscuits', '10000041', 'food.bakery'),
|
||||
('薯片膨化', 'Chips/Snacks', 'food.snacks.chips', '10000310', 'food.snacks'),
|
||||
('巧克力', 'Chocolate', 'food.snacks.chocolate', '10000311', 'food.snacks'),
|
||||
('大米', 'Rice', 'food.staple.rice', '10000500', 'food.staple'),
|
||||
('面条', 'Noodles', 'food.staple.noodles', '10000501', 'food.staple'),
|
||||
('食用油', 'Cooking oil', 'food.staple.cooking_oil', '10000502', 'food.staple'),
|
||||
('酱油', 'Soy sauce', 'food.condiments.soy_sauce', '10000600', 'food.condiments'),
|
||||
('食盐', 'Table salt', 'food.condiments.salt', '10000601', 'food.condiments')
|
||||
) AS v(name_zh, name_en, path, code, parent_path)
|
||||
JOIN category c ON c.path = v.parent_path::ltree;
|
||||
|
||||
-- Parameter templates: leaf food categories use per_100g/ml nutrition basis.
|
||||
INSERT INTO category_schema (category_id, required_attributes, recommended_attributes, nutriment_basis)
|
||||
SELECT id,
|
||||
ARRAY['net_content'],
|
||||
ARRAY['energy','proteins','fat','carbohydrates','sugars','salt'],
|
||||
CASE WHEN path <@ 'food.beverages' THEN 'per_100ml' ELSE 'per_100g' END
|
||||
FROM category
|
||||
WHERE level = 2;
|
||||
@@ -0,0 +1 @@
|
||||
DROP TABLE IF EXISTS ingest_state;
|
||||
@@ -0,0 +1,10 @@
|
||||
-- M4 ingestion management: persistent per-source incremental watermark.
|
||||
-- The updater reads/writes one row per source to resume incremental imports
|
||||
-- (e.g. Open Food Facts `last_modified_t`) and to record run statistics.
|
||||
CREATE TABLE ingest_state (
|
||||
source TEXT PRIMARY KEY,
|
||||
last_modified_t BIGINT NOT NULL DEFAULT 0,
|
||||
last_run_at TIMESTAMPTZ,
|
||||
cursor TEXT,
|
||||
stats JSONB NOT NULL DEFAULT '{}'
|
||||
);
|
||||
+26
-1
@@ -1,3 +1,28 @@
|
||||
# Database migrations (golang-migrate)
|
||||
|
||||
SQL migrations live here from milestone M1. Format: `NNNN_description.up.sql` / `.down.sql`.
|
||||
SQL migrations for the OpenGoods database, applied with
|
||||
[golang-migrate](https://github.com/golang-migrate/migrate).
|
||||
Naming: `NNNN_description.up.sql` / `NNNN_description.down.sql`.
|
||||
|
||||
## Files
|
||||
| Version | Up | 内容 |
|
||||
|---------|----|------|
|
||||
| 0001 | `0001_init` | 扩展(pgcrypto/pg_trgm/ltree) + 全部核心表 + 索引 + tsvector 触发器 |
|
||||
| 0002 | `0002_seed_units` | 单位字典(与 `ingestion/opengoods/units.py` 一致)+ 常用营养参数定义 |
|
||||
| 0003 | `0003_seed_categories` | 食品品类骨架(GS1 GPC 映射 + 自建中文树)+ 品类参数模板 |
|
||||
|
||||
## 运行
|
||||
|
||||
先起本地依赖:`docker compose up -d postgres`
|
||||
|
||||
```bash
|
||||
export DBURL="postgres://opengoods:opengoods@localhost:5432/opengoods?sslmode=disable"
|
||||
migrate -path migrations -database "$DBURL" up # 升级到最新
|
||||
migrate -path migrations -database "$DBURL" down -all # 全部回滚
|
||||
migrate -path migrations -database "$DBURL" version # 查看当前版本
|
||||
```
|
||||
|
||||
安装 CLI:`go install -tags 'postgres' github.com/golang-migrate/migrate/v4/cmd/migrate@v4.18.1`
|
||||
|
||||
> ltree 标签为英文 slug(不支持空格/中文),中文名存于 `category.name_zh`。
|
||||
> `gpc_brick_code` 为食品子集的代表值,后续用官方 GPC 全量导入替换。
|
||||
|
||||
Reference in New Issue
Block a user