ben/scrape-giant
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

added pm folder and tasks

Browse Source
This commit is contained in:
eulaly
2026-03-14 17:59:40 -04:00
parent 1df2dcec4b
commit 585d8c1e49
3 changed files with 307 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
.gitignore vendored
View File

@@ -21,7 +21,6 @@ env/
# --- project private data --- # --- project private data ---
/private/ /private/
/pm/
# --- django --- # --- django ---
db.sqlite3 db.sqlite3

107
pm/scrape-giant.org Normal file
View File

@@ -0,0 +1,107 @@
* python setup
venv install playwright, pandas
playwright install
1. scrape - raw giant json
2. enrich -
cols:
item_name_norm
brand_guess
size_value
size_unit
pack_qty
variant
is_store_brand
is_fee
measure_type
price_per_lb
price_per_oz
price_per_each
image_url
normalize abbreviationsta
extract size like 12z, 10ct, 5lb
detect fees like bag charges
infer whether something is sold by each vs weight
carry forward image url
3. build observed-product atble from enriched items
* item:
get:
/api/v6.0/user/369513017/order/history/detail/69a2e44a16be1142e74ad3cc
headers:
request:
GET /api/v6.0/user/369513017/order/history/detail/69a2e44a16be1142e74ad3cc?isInStore=true HTTP/2
Host: giantfood.com
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0
Accept: application/json, text/plain, */*
Accept-Language: en-US,en;q=0.9
Accept-Encoding: gzip, deflate, br, zstd
DNT: 1
Sec-GPC: 1
Connection: keep-alive
Referer: https://giantfood.com/account/history/invoice/in-store
Cookie: datadome=rDtvd3J2hO5AeghJMSFRRxGc6ifKCQYgMLcqPNr9rWiz2rdcXb032AY6GIZn8tUmYB96BKKbzh3_jSjEzYWLj8hDjl3oGYYAiu4jwdaxpf3vh2v4f7KH7kbqgsMWpkjt; cf_clearance=WEPyQokx9f0qoyS4Svsw4EkZ1TYOxjOwcUHspT3.rXw-1773348940-1.2.1.1-fPvERGxBlFUaBW83sUppbUWpwvFG7mZivag5vBvZb3kxUQv2WSVIV1tON0HV2n8bkVY0U8_BBl62a00Np.oJylYQcGME540gZlYEoL.gMs4WynLqApFe5BOXAEwOm01_6h6b62H90bl4ypRehVb_TXEi4qHaPLVSZhjZK_h.fv6RBqjgYch2j_8XnHe5HXvLziVjl1k2aJskozqy04KOyeHyc3OyIPTZd5On_KAzFIM; dvrctk=MnjKJVShVraEtbrBkkxWxLaZrXnIGNQlwB7QtZVPFeA=; __cflb=0H28vXMLFyydRmDMNgcPHijM6auXkCspCkuh58tVuJ3; __cf_bm=C6QbqiEvbbwdrYBpoJOkcWcedf60vcOfPfTPPbZzKbM-1773348202-1.0.1.1-cSHoYwi8ZjIHTdBItXQP_iXJdRJS6FYjFsGdl1eGHvS5pgfbcT4Lg19P6UStX.bZz1u0OXiS5ykdipPBtwP6OvZr68k4XSmjYpir05jNLhw; _dd_s=rum=0&expire=1773349846445; ppdtk=Uog72CR22mD85C7U4iZHlgOQeRmvHEYp0OdQc+0lEes1c5/LeqGT+ZUlXpSC6FpW; cartId=3820547
Sec-Fetch-Dest: empty
Sec-Fetch-Mode: cors
Sec-Fetch-Site: same-origin
Priority: u=0
TE: trailers
response:
HTTP/2 200
date: Thu, 12 Mar 2026 20:55:47 GMT
content-type: application/json
server: cloudflare
cf-ray: 9db5b3a5d84aff28-IAD
cf-cache-status: DYNAMIC
content-encoding: gzip
set-cookie: datadome=MXMri0hss6PlQ0_oS7gG2iMdOKnNkbDmGvOxelgN~nCcupgkJQOqjcjcgdprIaI7hSlt_w8E9Ri_RAzPFrGqtUfqAJ_szB_aNZ2FdC26qmI3870Nn4~T0vtx8Gj3dEZR; Max-Age=31536000; Domain=.giantfood.com; Path=/; Secure; SameSite=Lax
strict-transport-security: max-age=31536000; includeSubDomains
vary: Origin, Access-Control-Request-Method, Access-Control-Request-Headers, accept-encoding
accept-ch: Sec-CH-UA,Sec-CH-UA-Mobile,Sec-CH-UA-Platform,Sec-CH-UA-Arch,Sec-CH-UA-Full-Version-List,Sec-CH-UA-Model,Sec-CH-Device-Memory
x-datadome: protected
request-context: appId=cid-v1:75750625-0c81-4f08-9f5d-ce4f73198e54
X-Firefox-Spdy: h2
* history:
GET
https://giantfood.com/api/v6.0/user/369513017/order/history?filter=instore&loyaltyNumber=440155630880
headers:
request:
GET /api/v6.0/user/369513017/order/history?filter=instore&loyaltyNumber=440155630880 HTTP/2
Host: giantfood.com
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0
Accept: application/json, text/plain, */*
Accept-Language: en-US,en;q=0.9
Accept-Encoding: gzip, deflate, br, zstd
DNT: 1
Sec-GPC: 1
Connection: keep-alive
Referer: https://giantfood.com/account/history/invoice/in-store
Cookie: datadome=OH2XjtCoI6XjE3Qsz_b0F1YULKLatAC0Ea~VMeDGBP0N9Z~CeI3RqEbvkGmNW_VCOU~vRb6p0kqibvF2tLbWnzyAGIdO7jsC41KiYbp7USpJDnefZhIg0e1ypAugvDSw; cf_clearance=WEPyQokx9f0qoyS4Svsw4EkZ1TYOxjOwcUHspT3.rXw-1773348940-1.2.1.1-fPvERGxBlFUaBW83sUppbUWpwvFG7mZivag5vBvZb3kxUQv2WSVIV1tON0HV2n8bkVY0U8_BBl62a00Np.oJylYQcGME540gZlYEoL.gMs4WynLqApFe5BOXAEwOm01_6h6b62H90bl4ypRehVb_TXEi4qHaPLVSZhjZK_h.fv6RBqjgYch2j_8XnHe5HXvLziVjl1k2aJskozqy04KOyeHyc3OyIPTZd5On_KAzFIM; dvrctk=MnjKJVShVraEtbrBkkxWxLaZrXnIGNQlwB7QtZVPFeA=; __cflb=0H28vXMLFyydRmDMNgcPHijM6auXkCspCkuh58tVuJ3; __cf_bm=C6QbqiEvbbwdrYBpoJOkcWcedf60vcOfPfTPPbZzKbM-1773348202-1.0.1.1-cSHoYwi8ZjIHTdBItXQP_iXJdRJS6FYjFsGdl1eGHvS5pgfbcT4Lg19P6UStX.bZz1u0OXiS5ykdipPBtwP6OvZr68k4XSmjYpir05jNLhw; _dd_s=rum=0&expire=1773349842848; ppdtk=Uog72CR22mD85C7U4iZHlgOQeRmvHEYp0OdQc+0lEes1c5/LeqGT+ZUlXpSC6FpW; cartId=3820547
Sec-Fetch-Dest: empty
Sec-Fetch-Mode: cors
Sec-Fetch-Site: same-origin
Priority: u=0
TE: trailers
response:
HTTP/2 200
date: Thu, 12 Mar 2026 20:55:43 GMT
content-type: application/json
server: cloudflare
cf-ray: 9db5b38f7eebff28-IAD
cf-cache-status: DYNAMIC
content-encoding: gzip
set-cookie: datadome=rDtvd3J2hO5AeghJMSFRRxGc6ifKCQYgMLcqPNr9rWiz2rdcXb032AY6GIZn8tUmYB96BKKbzh3_jSjEzYWLj8hDjl3oGYYAiu4jwdaxpf3vh2v4f7KH7kbqgsMWpkjt; Max-Age=31536000; Domain=.giantfood.com; Path=/; Secure; SameSite=Lax
strict-transport-security: max-age=31536000; includeSubDomains
vary: Origin, Access-Control-Request-Method, Access-Control-Request-Headers, accept-encoding
accept-ch: Sec-CH-UA,Sec-CH-UA-Mobile,Sec-CH-UA-Platform,Sec-CH-UA-Arch,Sec-CH-UA-Full-Version-List,Sec-CH-UA-Model,Sec-CH-Device-Memory
x-datadome: protected
request-context: appId=cid-v1:75750625-0c81-4f08-9f5d-ce4f73198e54
X-Firefox-Spdy: h2

200
pm/tasks.org Normal file
View File

@@ -0,0 +1,200 @@
* [ ] t1.1: harden giant receipt fetch cli (2-4 commits)
** acceptance criteria
- giant scraper runs from cli with prompts or env-backed defaults for `user_id` and `loyalty`
- script reuses current browser session via firefox cookies + `curl_cffi`
- script only fetches unseen orders
- script appends to `orders.csv` and `items.csv` without duplicating prior visits
- script prints a note that giant only exposes the most recent 50 visits
** notes
- keep this giant-specific
- no canonical product logic here
- raw json archive remains source of truth
** evidence
- commit:
- tests:
- date:
* [ ] t1.2: define grocery data model and file layout (1-2 commits)
** acceptance criteria
- decide and document the files/directories for:
- retailer raw exports
- enriched line items
- observed products
- canonical products
- product links
- define stable column schemas for each file
- explicitly separate retailer-specific parsing from cross-retailer canonicalization
** notes
- this is the guardrail task so we don’t make giant-specific hacks the system of record
- keep schema minimal but extensible
** evidence
- commit:
- tests:
- date:
* [ ] t1.3: build giant parser/enricher from raw json (2-4 commits)
** acceptance criteria
- parser reads giant raw order json files
- outputs `items_enriched.csv`
- preserves core raw values plus parsed fields such as:
- normalized item name
- image url
- size value/unit guesses
- pack/count guesses
- fee/store-brand flags
- per-unit/per-weight derived price where possible
- parser is deterministic and rerunnable
** notes
- do not attempt canonical cross-store matching yet
- parser should preserve ambiguity rather than hallucinating precision
** evidence
- commit:
- tests:
- date:
* [ ] t1.4: generate observed-product layer from enriched items (2-3 commits)
** acceptance criteria
- distinct observed products are generated from enriched giant items
- each observed product has a stable `observed_product_id`
- observed products aggregate:
- first seen / last seen
- times seen
- representative upc
- representative image url
- representative normalized name
- outputs `products_observed.csv`
** notes
- observed product is retailer-facing, not yet canonical
- likely key is some combo of retailer + upc + normalized name
** evidence
- commit:
- tests:
- date:
* [ ] t1.5: build review queue for unresolved or low-confidence products (1-3 commits)
** acceptance criteria
- produce a review file containing observed products needing manual review
- include enough context to review quickly:
- raw names
- parsed names
- upc
- image url
- example prices
- seen count
- reviewed status can be stored and reused
** notes
- this is where human-in-the-loop starts
- optimize for “approve once, remember forever”
** evidence
- commit:
- tests:
- date:
* [ ] t1.6: create canonical product layer and observed→canonical links (2-4 commits)
** acceptance criteria
- define and create `products_canonical.csv`
- define and create `product_links.csv`
- support linking one or more observed products to one canonical product
- canonical product schema supports food-cost comparison fields such as:
- product type
- variant
- size
- measure type
- normalized quantity basis
** notes
- this is the first cross-retailer abstraction layer
- do not require llm assistance for v1
** evidence
- commit:
- tests:
- date:
* [ ] t1.7: implement auto-link rules for easy matches (2-3 commits)
** acceptance criteria
- auto-link can match observed products to canonical products using deterministic rules
- rules include at least:
- exact upc
- exact normalized name
- exact size/unit match where available
- low-confidence cases remain unlinked for review
** notes
- keep the rules conservative
- false positives are worse than unresolved items
** evidence
- commit:
- tests:
- date:
* [ ] t1.8: support costco raw ingest path (2-5 commits)
** acceptance criteria
- add a costco-specific raw ingest/export path
- output costco line items into the same shared raw/enriched schema family
- confirm at least one product class can exist as:
- giant observed product
- costco observed product
- one shared canonical product
** notes
- this is the proof that the architecture generalizes
- don’t chase perfection before the second retailer lands
** evidence
- commit:
- tests:
- date:
* [ ] t1.9: compute normalized comparison metrics (2-3 commits)
** acceptance criteria
- derive normalized comparison fields where possible:
- price per lb
- price per oz
- price per each
- price per count
- metrics are attached at canonical or linked-observed level as appropriate
- emit obvious nulls when basis is unknown rather than inventing values
** notes
- this is where “gala apples 5 lb bag vs other gala apples” becomes possible
- units discipline matters a lot here
** evidence
- commit:
- tests:
- date:
* [ ] t1.10: add optional llm-assisted suggestion workflow for unresolved products (2-4 commits)
** acceptance criteria
- llm suggestions are generated only for unresolved observed products
- llm outputs are stored as suggestions, not auto-applied truth
- reviewer can approve/edit/reject suggestions
- approved decisions are persisted into canonical/link files
** notes
- bounded assistant, not autonomous goblin
- image urls may become useful here
** evidence
- commit:
- tests:
- date: