A repo using the Flat Data approach, scraping Greek oil refinery prices from http://oil.mindev.gov.gr (note the lack of HTTPS) and assembling them in a number of more usable forms.

While I make no guarantees about the data structure formats and reserve the right to change them to suit my needs, it's been stable for quite a while now.

A Flat Data Github action approach that uses Deno, Typescript and Github to fetch periodically (twice per day) data from the RSS feed of http://oil.mindev.gov.gr, parses it and appends it to a set of flat data files (JSON and CSV) as well as an SQLite database.

The data exists in 3 formats, JSON, CSV and SQLite.

The most verbose. An example entry below. For an elasticsearch compatible mapping, see elasticsearch_mapping.json

{
  "date": "2023-04-07T00:00:00.000Z",
  "category": "Βενζίνες",
  "notes": "τιμές σε €/m3, συμπεριλ. φόρων – τελών, προ ΦΠΑ",
  "fuel": "UNLEADED 95 BIO",
  "elpePrice": 1454.368,
  "motoroilPrice": null,
  "meanPrice": 1454.368,
  "vatPrice": 1803.416,
  "unit": "Κυβικό Μέτρο"
},

Filename: fuels.json

Note that some fields could be null. Pretty much ready to be posted to elasticsearch (albeit not in the bulk endpoint)

I wish I could say that CSV is a "standard" format, however CSVs can be very ambiguously defined. Nevertheless, I try to offer that too. An example of a few entries is below, first row is the CSV header

date,category,notes,fuel,elpePrice,motoroilPrice,unit,meanPrice,vatPrice
2018-12-17T00:00:00.000Z,Βενζίνες,"τιμές σε €/m3, συμπεριλ. φόρων – τελών, προ ΦΠΑ",UNLEADED LRP,1090.851,1131.593,Κυβικό Μέτρο,1111.222,1377.915
2018-12-17T00:00:00.000Z,Βενζίνες,"τιμές σε €/m3, συμπεριλ. φόρων – τελών, προ ΦΠΑ",UNLEADED 95,1087.75,1086.936,Κυβικό Μέτρο,1087.343,1348.305
2018-12-17T00:00:00.000Z,Βενζίνες,"τιμές σε €/m3, συμπεριλ. φόρων – τελών, προ ΦΠΑ",UNLEADED 100,1154.984,1155.034,Κυβικό Μέτρο,1155.009,1432.211
2018-12-17T00:00:00.000Z,Πετρέλαια,"τιμές σε €/m3, συμπεριλ. φόρων – τελών, προ ΦΠΑ",DIΕSEL AUTO BIO,944.67,943.684,Κυβικό Μέτρο,944.177,1170.779
2018-12-17T00:00:00.000Z,Πετρέλαια,"τιμές σε €/m3, συμπεριλ. φόρων – τελών, προ ΦΠΑ",HEATING GASOIL (ΧΠ),742.484,741.396,Κυβικό Μέτρο,741.94,920.006
2018-12-17T00:00:00.000Z,Υγραέρια – LPG,"τιμές σε €/μ.τ., συμπεριλ. φόρων – τελών, προ ΦΠΑ",LPG AUTO,877.716,878.133,Μετρικός Τόνος,877.925,1088.627

Filename: fuels.csv

We provide a number of variants here

The table schema is the following. The table is in 1st normal form. TL;DR no cell contains tables

CREATE TABLE IF NOT EXISTS fuels (
  date TEXT NOT NULL,
  category TEXT NOT NULL,
  notes TEXT NOT NULL,
  fuel TEXT NOT NULL,
  elpePrice REAL,
  motoroilPrice REAL,
  meanPrice REAL,
  vatPrice REAL,
  unit TEXT NOT NULL);
CREATE INDEX IF NOT EXISTS idx_fuels_date ON fuels(date);

Filename: fuels.db

The table schema is the following. The tables are in 2nd normal form, that means already in 1NF and all non-key attributes functionally dependent on the primary key.

  CREATE TABLE IF NOT EXISTS categories (
    id integer PRIMARY KEY AUTOINCREMENT,
    category TEXT NOT NULL,
    notes TEXT NOT NULL,
    unit TEXT NOT NULL);

  CREATE TABLE IF NOT EXISTS fuels (
    date TEXT NOT NULL,
    category_id integer NOT NULL,
    fuel TEXT NOT NULL,
    elpePrice REAL,
    motoroilPrice REAL,
    meanPrice REAL,
    vatPrice REAL,
    FOREIGN KEY (category_id) REFERENCES categories(id));
  CREATE INDEX IF NOT EXISTS idx_fuels_date ON fuels(date);

Just go to https://flatgithub.com/akosiaris/greek-oil-refinery-prices , pick the data file you want and get a basic UI for exploring it.

You can also choose to feed the 3 different formats we provide it to whatever datastore you like

• Up to now, we kinda parse 1 "format" (for some definition of format). And it starts at ~end of 2018. Previous dates are unparsed yet.

• Parsing dates that are human entered is error prone, this continually breaks for one reason or another, e.g. a different operator replaces the usual one, the operator makes an unaccounted for typo, alters habbits significantly, etc.

• At various points in time and for various reasons, values could be null

• Doesn't handle what upstream calls "correct repetition" (ΟΡΘΗ ΕΠΑΝΑΛΗΨΗ) of entries. So no corrected updates