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Reusing Open Food Facts Data (view source)
Revision as of 15:55, 25 November 2021
, 15:55, 25 November 2021Eg: Filtering barcodes which are different from a code containing 1 to 13 digits
==== jq ====
==== jq ====
* start decompress the file (be carreful => 14GB after decompression):
* start decompress the file (be careful => 14GB after decompression):
$ gunzip openfoodfacts-products.jsonl.gz
$ gunzip openfoodfacts-products.jsonl.gz
* work on a small subset to test. E.g. for 100 products:
* work on a small subset to test. E.g. for 100 products:
$ zcat openfoodfacts-products.jsonl.gz | jq -r '. | select(.misc_tags[]? == "en:nutriscore-computed" and .popularity_tags[]? == "top-90-percent-scans-2020") | [.code,.scans_n] | @csv' > displayed.ns.in.top90.2020.world.csv
$ zcat openfoodfacts-products.jsonl.gz | jq -r '. | select(.misc_tags[]? == "en:nutriscore-computed" and .popularity_tags[]? == "top-90-percent-scans-2020") | [.code,.scans_n] | @csv' > displayed.ns.in.top90.2020.world.csv
Filtering barcodes which are different from a code containing 1 to 13 digits:
zcat openfoodfacts-products.jsonl.gz | jq -r '. | select(.code|test("^[0-9]{1,13}$") | not) | .code' > ean_gt_13.csv
These operations can be quite long (more than 10 minutes depending on your computer and your selection).
These operations can be quite long (more than 10 minutes depending on your computer and your selection).