svilupp/create_measurement.jl Secret

## create_measurement.jl
# Converted from https://github.com/gunnarmorling/1brc/blob/main/src/main/java/dev/morling/onebrc/CreateMeasurements.java
# Call via CLI (last arg is how many rows to create)
# Example: `julia create_measurements.jl 1000000`

using Random

# Define a struct equivalent to the Java record
struct WeatherStation
    id::String
    meanTemperature::Float64
end

# Function to simulate measurement
function measurement(ws::WeatherStation)
    m = randn() * 10 + ws.meanTemperature
    return round(m, digits=1)
end

# Main function
function main()
    start = time()

    if length(ARGS) != 1
        println("Usage: create_measurements.jl <number of records to create>")
        return
    end

    size = try
        parse(Int, ARGS[1])
    catch
        println("Invalid value for <number of records to create>")
        println("Usage: create_measurements.jl <number of records to create>")
        return
    end

    # List of weather stations
    stations =
        [WeatherStation("Abha", 18.0),
            WeatherStation("Abidjan", 26.0),
            WeatherStation("Abéché", 29.4),
            WeatherStation("Accra", 26.4),
            WeatherStation("Addis Ababa", 16.0),
            WeatherStation("Adelaide", 17.3),
            WeatherStation("Aden", 29.1),
            WeatherStation("Ahvaz", 25.4),
            WeatherStation("Albuquerque", 14.0),
            WeatherStation("Alexandra", 11.0),
            WeatherStation("Alexandria", 20.0),
            WeatherStation("Algiers", 18.2),
            WeatherStation("Alice Springs", 21.0),
            WeatherStation("Almaty", 10.0),
            WeatherStation("Amsterdam", 10.2),
            WeatherStation("Anadyr", -6.9),
            WeatherStation("Anchorage", 2.8),
            WeatherStation("Andorra la Vella", 9.8),
            WeatherStation("Ankara", 12.0),
            WeatherStation("Antananarivo", 17.9),
            WeatherStation("Antsiranana", 25.2),
            WeatherStation("Arkhangelsk", 1.3),
            WeatherStation("Ashgabat", 17.1),
            WeatherStation("Asmara", 15.6),
            WeatherStation("Assab", 30.5),
            WeatherStation("Astana", 3.5),
            WeatherStation("Athens", 19.2),
            WeatherStation("Atlanta", 17.0),
            WeatherStation("Auckland", 15.2),
            WeatherStation("Austin", 20.7),
            WeatherStation("Baghdad", 22.77),
            WeatherStation("Baguio", 19.5),
            WeatherStation("Baku", 15.1),
            WeatherStation("Baltimore", 13.1),
            WeatherStation("Bamako", 27.8),
            WeatherStation("Bangkok", 28.6),
            WeatherStation("Bangui", 26.0),
            WeatherStation("Banjul", 26.0),
            WeatherStation("Barcelona", 18.2),
            WeatherStation("Bata", 25.1),
            WeatherStation("Batumi", 14.0),
            WeatherStation("Beijing", 12.9),
            WeatherStation("Beirut", 20.9),
            WeatherStation("Belgrade", 12.5),
            WeatherStation("Belize City", 26.7),
            WeatherStation("Benghazi", 19.9),
            WeatherStation("Bergen", 7.7),
            WeatherStation("Berlin", 10.3),
            WeatherStation("Bilbao", 14.7),
            WeatherStation("Birao", 26.5),
            WeatherStation("Bishkek", 11.3),
            WeatherStation("Bissau", 27.0),
            WeatherStation("Blantyre", 22.2),
            WeatherStation("Bloemfontein", 15.6),
            WeatherStation("Boise", 11.4),
            WeatherStation("Bordeaux", 14.2),
            WeatherStation("Bosaso", 30.0),
            WeatherStation("Boston", 10.9),
            WeatherStation("Bouaké", 26.0),
            WeatherStation("Bratislava", 10.5),
            WeatherStation("Brazzaville", 25.0),
            WeatherStation("Bridgetown", 27.0),
            WeatherStation("Brisbane", 21.4),
            WeatherStation("Brussels", 10.5),
            WeatherStation("Bucharest", 10.8),
            WeatherStation("Budapest", 11.3),
            WeatherStation("Bujumbura", 23.8),
            WeatherStation("Bulawayo", 18.9),
            WeatherStation("Burnie", 13.1),
            WeatherStation("Busan", 15.0),
            WeatherStation("Cabo San Lucas", 23.9),
            WeatherStation("Cairns", 25.0),
            WeatherStation("Cairo", 21.4),
            WeatherStation("Calgary", 4.4),
            WeatherStation("Canberra", 13.1),
            WeatherStation("Cape Town", 16.2),
            WeatherStation("Changsha", 17.4),
            WeatherStation("Charlotte", 16.1),
            WeatherStation("Chiang Mai", 25.8),
            WeatherStation("Chicago", 9.8),
            WeatherStation("Chihuahua", 18.6),
            WeatherStation("Chișinău", 10.2),
            WeatherStation("Chittagong", 25.9),
            WeatherStation("Chongqing", 18.6),
            WeatherStation("Christchurch", 12.2),
            WeatherStation("City of San Marino", 11.8),
            WeatherStation("Colombo", 27.4),
            WeatherStation("Columbus", 11.7),
            WeatherStation("Conakry", 26.4),
            WeatherStation("Copenhagen", 9.1),
            WeatherStation("Cotonou", 27.2),
            WeatherStation("Cracow", 9.3),
            WeatherStation("Da Lat", 17.9),
            WeatherStation("Da Nang", 25.8),
            WeatherStation("Dakar", 24.0),
            WeatherStation("Dallas", 19.0),
            WeatherStation("Damascus", 17.0),
            WeatherStation("Dampier", 26.4),
            WeatherStation("Dar es Salaam", 25.8),
            WeatherStation("Darwin", 27.6),
            WeatherStation("Denpasar", 23.7),
            WeatherStation("Denver", 10.4),
            WeatherStation("Detroit", 10.0),
            WeatherStation("Dhaka", 25.9),
            WeatherStation("Dikson", -11.1),
            WeatherStation("Dili", 26.6),
            WeatherStation("Djibouti", 29.9),
            WeatherStation("Dodoma", 22.7),
            WeatherStation("Dolisie", 24.0),
            WeatherStation("Douala", 26.7),
            WeatherStation("Dubai", 26.9),
            WeatherStation("Dublin", 9.8),
            WeatherStation("Dunedin", 11.1),
            WeatherStation("Durban", 20.6),
            WeatherStation("Dushanbe", 14.7),
            WeatherStation("Edinburgh", 9.3),
            WeatherStation("Edmonton", 4.2),
            WeatherStation("El Paso", 18.1),
            WeatherStation("Entebbe", 21.0),
            WeatherStation("Erbil", 19.5),
            WeatherStation("Erzurum", 5.1),
            WeatherStation("Fairbanks", -2.3),
            WeatherStation("Fianarantsoa", 17.9),
            WeatherStation("Flores,  Petén", 26.4),
            WeatherStation("Frankfurt", 10.6),
            WeatherStation("Fresno", 17.9),
            WeatherStation("Fukuoka", 17.0),
            WeatherStation("Gabès", 19.5),
            WeatherStation("Gaborone", 21.0),
            WeatherStation("Gagnoa", 26.0),
            WeatherStation("Gangtok", 15.2),
            WeatherStation("Garissa", 29.3),
            WeatherStation("Garoua", 28.3),
            WeatherStation("George Town", 27.9),
            WeatherStation("Ghanzi", 21.4),
            WeatherStation("Gjoa Haven", -14.4),
            WeatherStation("Guadalajara", 20.9),
            WeatherStation("Guangzhou", 22.4),
            WeatherStation("Guatemala City", 20.4),
            WeatherStation("Halifax", 7.5),
            WeatherStation("Hamburg", 9.7),
            WeatherStation("Hamilton", 13.8),
            WeatherStation("Hanga Roa", 20.5),
            WeatherStation("Hanoi", 23.6),
            WeatherStation("Harare", 18.4),
            WeatherStation("Harbin", 5.0),
            WeatherStation("Hargeisa", 21.7),
            WeatherStation("Hat Yai", 27.0),
            WeatherStation("Havana", 25.2),
            WeatherStation("Helsinki", 5.9),
            WeatherStation("Heraklion", 18.9),
            WeatherStation("Hiroshima", 16.3),
            WeatherStation("Ho Chi Minh City", 27.4),
            WeatherStation("Hobart", 12.7),
            WeatherStation("Hong Kong", 23.3),
            WeatherStation("Honiara", 26.5),
            WeatherStation("Honolulu", 25.4),
            WeatherStation("Houston", 20.8),
            WeatherStation("Ifrane", 11.4),
            WeatherStation("Indianapolis", 11.8),
            WeatherStation("Iqaluit", -9.3),
            WeatherStation("Irkutsk", 1.0),
            WeatherStation("Istanbul", 13.9),
            WeatherStation("İzmir", 17.9),
            WeatherStation("Jacksonville", 20.3),
            WeatherStation("Jakarta", 26.7),
            WeatherStation("Jayapura", 27.0),
            WeatherStation("Jerusalem", 18.3),
            WeatherStation("Johannesburg", 15.5),
            WeatherStation("Jos", 22.8),
            WeatherStation("Juba", 27.8),
            WeatherStation("Kabul", 12.1),
            WeatherStation("Kampala", 20.0),
            WeatherStation("Kandi", 27.7),
            WeatherStation("Kankan", 26.5),
            WeatherStation("Kano", 26.4),
            WeatherStation("Kansas City", 12.5),
            WeatherStation("Karachi", 26.0),
            WeatherStation("Karonga", 24.4),
            WeatherStation("Kathmandu", 18.3),
            WeatherStation("Khartoum", 29.9),
            WeatherStation("Kingston", 27.4),
            WeatherStation("Kinshasa", 25.3),
            WeatherStation("Kolkata", 26.7),
            WeatherStation("Kuala Lumpur", 27.3),
            WeatherStation("Kumasi", 26.0),
            WeatherStation("Kunming", 15.7),
            WeatherStation("Kuopio", 3.4),
            WeatherStation("Kuwait City", 25.7),
            WeatherStation("Kyiv", 8.4),
            WeatherStation("Kyoto", 15.8),
            WeatherStation("La Ceiba", 26.2),
            WeatherStation("La Paz", 23.7),
            WeatherStation("Lagos", 26.8),
            WeatherStation("Lahore", 24.3),
            WeatherStation("Lake Havasu City", 23.7),
            WeatherStation("Lake Tekapo", 8.7),
            WeatherStation("Las Palmas de Gran Canaria", 21.2),
            WeatherStation("Las Vegas", 20.3),
            WeatherStation("Launceston", 13.1),
            WeatherStation("Lhasa", 7.6),
            WeatherStation("Libreville", 25.9),
            WeatherStation("Lisbon", 17.5),
            WeatherStation("Livingstone", 21.8),
            WeatherStation("Ljubljana", 10.9),
            WeatherStation("Lodwar", 29.3),
            WeatherStation("Lomé", 26.9),
            WeatherStation("London", 11.3),
            WeatherStation("Los Angeles", 18.6),
            WeatherStation("Louisville", 13.9),
            WeatherStation("Luanda", 25.8),
            WeatherStation("Lubumbashi", 20.8),
            WeatherStation("Lusaka", 19.9),
            WeatherStation("Luxembourg City", 9.3),
            WeatherStation("Lviv", 7.8),
            WeatherStation("Lyon", 12.5),
            WeatherStation("Madrid", 15.0),
            WeatherStation("Mahajanga", 26.3),
            WeatherStation("Makassar", 26.7),
            WeatherStation("Makurdi", 26.0),
            WeatherStation("Malabo", 26.3),
            WeatherStation("Malé", 28.0),
            WeatherStation("Managua", 27.3),
            WeatherStation("Manama", 26.5),
            WeatherStation("Mandalay", 28.0),
            WeatherStation("Mango", 28.1),
            WeatherStation("Manila", 28.4),
            WeatherStation("Maputo", 22.8),
            WeatherStation("Marrakesh", 19.6),
            WeatherStation("Marseille", 15.8),
            WeatherStation("Maun", 22.4),
            WeatherStation("Medan", 26.5),
            WeatherStation("Mek'ele", 22.7),
            WeatherStation("Melbourne", 15.1),
            WeatherStation("Memphis", 17.2),
            WeatherStation("Mexicali", 23.1),
            WeatherStation("Mexico City", 17.5),
            WeatherStation("Miami", 24.9),
            WeatherStation("Milan", 13.0),
            WeatherStation("Milwaukee", 8.9),
            WeatherStation("Minneapolis", 7.8),
            WeatherStation("Minsk", 6.7),
            WeatherStation("Mogadishu", 27.1),
            WeatherStation("Mombasa", 26.3),
            WeatherStation("Monaco", 16.4),
            WeatherStation("Moncton", 6.1),
            WeatherStation("Monterrey", 22.3),
            WeatherStation("Montreal", 6.8),
            WeatherStation("Moscow", 5.8),
            WeatherStation("Mumbai", 27.1),
            WeatherStation("Murmansk", 0.6),
            WeatherStation("Muscat", 28.0),
            WeatherStation("Mzuzu", 17.7),
            WeatherStation("N'Djamena", 28.3),
            WeatherStation("Naha", 23.1),
            WeatherStation("Nairobi", 17.8),
            WeatherStation("Nakhon Ratchasima", 27.3),
            WeatherStation("Napier", 14.6),
            WeatherStation("Napoli", 15.9),
            WeatherStation("Nashville", 15.4),
            WeatherStation("Nassau", 24.6),
            WeatherStation("Ndola", 20.3),
            WeatherStation("New Delhi", 25.0),
            WeatherStation("New Orleans", 20.7),
            WeatherStation("New York City", 12.9),
            WeatherStation("Ngaoundéré", 22.0),
            WeatherStation("Niamey", 29.3),
            WeatherStation("Nicosia", 19.7),
            WeatherStation("Niigata", 13.9),
            WeatherStation("Nouadhibou", 21.3),
            WeatherStation("Nouakchott", 25.7),
            WeatherStation("Novosibirsk", 1.7),
            WeatherStation("Nuuk", -1.4),
            WeatherStation("Odesa", 10.7),
            WeatherStation("Odienné", 26.0),
            WeatherStation("Oklahoma City", 15.9),
            WeatherStation("Omaha", 10.6),
            WeatherStation("Oranjestad", 28.1),
            WeatherStation("Oslo", 5.7),
            WeatherStation("Ottawa", 6.6),
            WeatherStation("Ouagadougou", 28.3),
            WeatherStation("Ouahigouya", 28.6),
            WeatherStation("Ouarzazate", 18.9),
            WeatherStation("Oulu", 2.7),
            WeatherStation("Palembang", 27.3),
            WeatherStation("Palermo", 18.5),
            WeatherStation("Palm Springs", 24.5),
            WeatherStation("Palmerston North", 13.2),
            WeatherStation("Panama City", 28.0),
            WeatherStation("Parakou", 26.8),
            WeatherStation("Paris", 12.3),
            WeatherStation("Perth", 18.7),
            WeatherStation("Petropavlovsk-Kamchatsky", 1.9),
            WeatherStation("Philadelphia", 13.2),
            WeatherStation("Phnom Penh", 28.3),
            WeatherStation("Phoenix", 23.9),
            WeatherStation("Pittsburgh", 10.8),
            WeatherStation("Podgorica", 15.3),
            WeatherStation("Pointe-Noire", 26.1),
            WeatherStation("Pontianak", 27.7),
            WeatherStation("Port Moresby", 26.9),
            WeatherStation("Port Sudan", 28.4),
            WeatherStation("Port Vila", 24.3),
            WeatherStation("Port-Gentil", 26.0),
            WeatherStation("Portland (OR)", 12.4),
            WeatherStation("Porto", 15.7),
            WeatherStation("Prague", 8.4),
            WeatherStation("Praia", 24.4),
            WeatherStation("Pretoria", 18.2),
            WeatherStation("Pyongyang", 10.8),
            WeatherStation("Rabat", 17.2),
            WeatherStation("Rangpur", 24.4),
            WeatherStation("Reggane", 28.3),
            WeatherStation("Reykjavík", 4.3),
            WeatherStation("Riga", 6.2),
            WeatherStation("Riyadh", 26.0),
            WeatherStation("Rome", 15.2),
            WeatherStation("Roseau", 26.2),
            WeatherStation("Rostov-on-Don", 9.9),
            WeatherStation("Sacramento", 16.3),
            WeatherStation("Saint Petersburg", 5.8),
            WeatherStation("Saint-Pierre", 5.7),
            WeatherStation("Salt Lake City", 11.6),
            WeatherStation("San Antonio", 20.8),
            WeatherStation("San Diego", 17.8),
            WeatherStation("San Francisco", 14.6),
            WeatherStation("San Jose", 16.4),
            WeatherStation("San José", 22.6),
            WeatherStation("San Juan", 27.2),
            WeatherStation("San Salvador", 23.1),
            WeatherStation("Sana'a", 20.0),
            WeatherStation("Santo Domingo", 25.9),
            WeatherStation("Sapporo", 8.9),
            WeatherStation("Sarajevo", 10.1),
            WeatherStation("Saskatoon", 3.3),
            WeatherStation("Seattle", 11.3),
            WeatherStation("Ségou", 28.0),
            WeatherStation("Seoul", 12.5),
            WeatherStation("Seville", 19.2),
            WeatherStation("Shanghai", 16.7),
            WeatherStation("Singapore", 27.0),
            WeatherStation("Skopje", 12.4),
            WeatherStation("Sochi", 14.2),
            WeatherStation("Sofia", 10.6),
            WeatherStation("Sokoto", 28.0),
            WeatherStation("Split", 16.1),
            WeatherStation("St. John's", 5.0),
            WeatherStation("St. Louis", 13.9),
            WeatherStation("Stockholm", 6.6),
            WeatherStation("Surabaya", 27.1),
            WeatherStation("Suva", 25.6),
            WeatherStation("Suwałki", 7.2),
            WeatherStation("Sydney", 17.7),
            WeatherStation("Tabora", 23.0),
            WeatherStation("Tabriz", 12.6),
            WeatherStation("Taipei", 23.0),
            WeatherStation("Tallinn", 6.4),
            WeatherStation("Tamale", 27.9),
            WeatherStation("Tamanrasset", 21.7),
            WeatherStation("Tampa", 22.9),
            WeatherStation("Tashkent", 14.8),
            WeatherStation("Tauranga", 14.8),
            WeatherStation("Tbilisi", 12.9),
            WeatherStation("Tegucigalpa", 21.7),
            WeatherStation("Tehran", 17.0),
            WeatherStation("Tel Aviv", 20.0),
            WeatherStation("Thessaloniki", 16.0),
            WeatherStation("Thiès", 24.0),
            WeatherStation("Tijuana", 17.8),
            WeatherStation("Timbuktu", 28.0),
            WeatherStation("Tirana", 15.2),
            WeatherStation("Toamasina", 23.4),
            WeatherStation("Tokyo", 15.4),
            WeatherStation("Toliara", 24.1),
            WeatherStation("Toluca", 12.4),
            WeatherStation("Toronto", 9.4),
            WeatherStation("Tripoli", 20.0),
            WeatherStation("Tromsø", 2.9),
            WeatherStation("Tucson", 20.9),
            WeatherStation("Tunis", 18.4),
            WeatherStation("Ulaanbaatar", -0.4),
            WeatherStation("Upington", 20.4),
            WeatherStation("Ürümqi", 7.4),
            WeatherStation("Vaduz", 10.1),
            WeatherStation("Valencia", 18.3),
            WeatherStation("Valletta", 18.8),
            WeatherStation("Vancouver", 10.4),
            WeatherStation("Veracruz", 25.4),
            WeatherStation("Vienna", 10.4),
            WeatherStation("Vientiane", 25.9),
            WeatherStation("Villahermosa", 27.1),
            WeatherStation("Vilnius", 6.0),
            WeatherStation("Virginia Beach", 15.8),
            WeatherStation("Vladivostok", 4.9),
            WeatherStation("Warsaw", 8.5),
            WeatherStation("Washington, D.C.", 14.6),
            WeatherStation("Wau", 27.8),
            WeatherStation("Wellington", 12.9),
            WeatherStation("Whitehorse", -0.1),
            WeatherStation("Wichita", 13.9),
            WeatherStation("Willemstad", 28.0),
            WeatherStation("Winnipeg", 3.0),
            WeatherStation("Wrocław", 9.6),
            WeatherStation("Xi'an", 14.1),
            WeatherStation("Yakutsk", -8.8),
            WeatherStation("Yangon", 27.5),
            WeatherStation("Yaoundé", 23.8),
            WeatherStation("Yellowknife", -4.3),
            WeatherStation("Yerevan", 12.4),
            WeatherStation("Yinchuan", 9.0),
            WeatherStation("Zagreb", 10.7),
            WeatherStation("Zanzibar City", 26.0),
            WeatherStation("Zürich", 9.3)]


    open("measurements.txt", "w") do file
        for i in 1:size
            if i > 1 && i % 50_000_000 == 0
                println("Wrote $i measurements in $(time() - start) s")
            end
            station = stations[rand(1:length(stations))]
            write(file, station.id * ";" * string(measurement(station)) * "\n")
        end
    end

    println("Created file with $size measurements in $(time() - start) s")
end

main()

## with_dataframes.jl
# Naive solution with DataFrames.jl

using CSV, DataFrames, Statistics

function main()
    df = CSV.read("measurements.txt", DataFrame; header=[:station, :temperature], delim=";")
    df_out = combine(groupby(df, :station), :temperature => mean, :temperature => minimum, :temperature => maximum)
    transform!(df_out, [:temperature_mean, :temperature_minimum, :temperature_maximum] .=> ByRow(x -> round(x; digits=1)), renamecols=false)
    sort!(df_out, :station)
    for row in eachrow(df_out)
        # print on new lines, instead of comma separated as the original challenge
        println(row.station, "=", row.temperature_mean, "/", row.temperature_minimum, "/", row.temperature_maximum)
    end
end

@time main()
# 1M rows: 0.9s
# 10M rows: 9.3s

## with_gpt4.jl
# generated with GPT4 to read the stream

function calculate_stations(filename)
    totals = Dict{String,Float64}()
    counts = Dict{String,Int}()
    mins = Dict{String,Float64}()
    maxs = Dict{String,Float64}()

    open(filename, "r") do file
        while !eof(file)
            station = readuntil(file, ';')
            temp_str = readuntil(file, '\n')
            temp = parse(Float64, temp_str)

            # Update totals and counts
            totals[station] = get(totals, station, 0.0) + temp
            counts[station] = get(counts, station, 0) + 1

            # Update minimum temperature
            if !haskey(mins, station) || temp < mins[station]
                mins[station] = temp
            end

            # Update maximum temperature
            if !haskey(maxs, station) || temp > maxs[station]
                maxs[station] = temp
            end
        end
    end

    # Calculate mean and sort the stations
    sorted_stations = sort(collect(keys(totals)))
    for station in sorted_stations
        mean_temp = round(totals[station] / counts[station], digits=1)
        min_temp = round(mins[station], digits=1)
        max_temp = round(maxs[station], digits=1)
        println("$station=$min_temp/$mean_temp/$max_temp")
    end
end

# Usage
@time calculate_stations("measurements.txt")

# 10M rows: 5s
# 100M rows: 27s
	# Converted from https://github.com/gunnarmorling/1brc/blob/main/src/main/java/dev/morling/onebrc/CreateMeasurements.java
	# Call via CLI (last arg is how many rows to create)
	# Example: `julia create_measurements.jl 1000000`

	using Random

	# Define a struct equivalent to the Java record
	struct WeatherStation
	id::String
	meanTemperature::Float64
	end

	# Function to simulate measurement
	function measurement(ws::WeatherStation)
	m = randn() * 10 + ws.meanTemperature
	return round(m, digits=1)
	end

	# Main function
	function main()
	start = time()

	if length(ARGS) != 1
	println("Usage: create_measurements.jl <number of records to create>")
	return
	end

	size = try
	parse(Int, ARGS[1])
	catch
	println("Invalid value for <number of records to create>")
	println("Usage: create_measurements.jl <number of records to create>")
	return
	end

	# List of weather stations
	stations =
	[WeatherStation("Abha", 18.0),
	WeatherStation("Abidjan", 26.0),
	WeatherStation("Abéché", 29.4),
	WeatherStation("Accra", 26.4),
	WeatherStation("Addis Ababa", 16.0),
	WeatherStation("Adelaide", 17.3),
	WeatherStation("Aden", 29.1),
	WeatherStation("Ahvaz", 25.4),
	WeatherStation("Albuquerque", 14.0),
	WeatherStation("Alexandra", 11.0),
	WeatherStation("Alexandria", 20.0),
	WeatherStation("Algiers", 18.2),
	WeatherStation("Alice Springs", 21.0),
	WeatherStation("Almaty", 10.0),
	WeatherStation("Amsterdam", 10.2),
	WeatherStation("Anadyr", -6.9),
	WeatherStation("Anchorage", 2.8),
	WeatherStation("Andorra la Vella", 9.8),
	WeatherStation("Ankara", 12.0),
	WeatherStation("Antananarivo", 17.9),
	WeatherStation("Antsiranana", 25.2),
	WeatherStation("Arkhangelsk", 1.3),
	WeatherStation("Ashgabat", 17.1),
	WeatherStation("Asmara", 15.6),
	WeatherStation("Assab", 30.5),
	WeatherStation("Astana", 3.5),
	WeatherStation("Athens", 19.2),
	WeatherStation("Atlanta", 17.0),
	WeatherStation("Auckland", 15.2),
	WeatherStation("Austin", 20.7),
	WeatherStation("Baghdad", 22.77),
	WeatherStation("Baguio", 19.5),
	WeatherStation("Baku", 15.1),
	WeatherStation("Baltimore", 13.1),
	WeatherStation("Bamako", 27.8),
	WeatherStation("Bangkok", 28.6),
	WeatherStation("Bangui", 26.0),
	WeatherStation("Banjul", 26.0),
	WeatherStation("Barcelona", 18.2),
	WeatherStation("Bata", 25.1),
	WeatherStation("Batumi", 14.0),
	WeatherStation("Beijing", 12.9),
	WeatherStation("Beirut", 20.9),
	WeatherStation("Belgrade", 12.5),
	WeatherStation("Belize City", 26.7),
	WeatherStation("Benghazi", 19.9),
	WeatherStation("Bergen", 7.7),
	WeatherStation("Berlin", 10.3),
	WeatherStation("Bilbao", 14.7),
	WeatherStation("Birao", 26.5),
	WeatherStation("Bishkek", 11.3),
	WeatherStation("Bissau", 27.0),
	WeatherStation("Blantyre", 22.2),
	WeatherStation("Bloemfontein", 15.6),
	WeatherStation("Boise", 11.4),
	WeatherStation("Bordeaux", 14.2),
	WeatherStation("Bosaso", 30.0),
	WeatherStation("Boston", 10.9),
	WeatherStation("Bouaké", 26.0),
	WeatherStation("Bratislava", 10.5),
	WeatherStation("Brazzaville", 25.0),
	WeatherStation("Bridgetown", 27.0),
	WeatherStation("Brisbane", 21.4),
	WeatherStation("Brussels", 10.5),
	WeatherStation("Bucharest", 10.8),
	WeatherStation("Budapest", 11.3),
	WeatherStation("Bujumbura", 23.8),
	WeatherStation("Bulawayo", 18.9),
	WeatherStation("Burnie", 13.1),
	WeatherStation("Busan", 15.0),
	WeatherStation("Cabo San Lucas", 23.9),
	WeatherStation("Cairns", 25.0),
	WeatherStation("Cairo", 21.4),
	WeatherStation("Calgary", 4.4),
	WeatherStation("Canberra", 13.1),
	WeatherStation("Cape Town", 16.2),
	WeatherStation("Changsha", 17.4),
	WeatherStation("Charlotte", 16.1),
	WeatherStation("Chiang Mai", 25.8),
	WeatherStation("Chicago", 9.8),
	WeatherStation("Chihuahua", 18.6),
	WeatherStation("Chișinău", 10.2),
	WeatherStation("Chittagong", 25.9),
	WeatherStation("Chongqing", 18.6),
	WeatherStation("Christchurch", 12.2),
	WeatherStation("City of San Marino", 11.8),
	WeatherStation("Colombo", 27.4),
	WeatherStation("Columbus", 11.7),
	WeatherStation("Conakry", 26.4),
	WeatherStation("Copenhagen", 9.1),
	WeatherStation("Cotonou", 27.2),
	WeatherStation("Cracow", 9.3),
	WeatherStation("Da Lat", 17.9),
	WeatherStation("Da Nang", 25.8),
	WeatherStation("Dakar", 24.0),
	WeatherStation("Dallas", 19.0),
	WeatherStation("Damascus", 17.0),
	WeatherStation("Dampier", 26.4),
	WeatherStation("Dar es Salaam", 25.8),
	WeatherStation("Darwin", 27.6),
	WeatherStation("Denpasar", 23.7),
	WeatherStation("Denver", 10.4),
	WeatherStation("Detroit", 10.0),
	WeatherStation("Dhaka", 25.9),
	WeatherStation("Dikson", -11.1),
	WeatherStation("Dili", 26.6),
	WeatherStation("Djibouti", 29.9),
	WeatherStation("Dodoma", 22.7),
	WeatherStation("Dolisie", 24.0),
	WeatherStation("Douala", 26.7),
	WeatherStation("Dubai", 26.9),
	WeatherStation("Dublin", 9.8),
	WeatherStation("Dunedin", 11.1),
	WeatherStation("Durban", 20.6),
	WeatherStation("Dushanbe", 14.7),
	WeatherStation("Edinburgh", 9.3),
	WeatherStation("Edmonton", 4.2),
	WeatherStation("El Paso", 18.1),
	WeatherStation("Entebbe", 21.0),
	WeatherStation("Erbil", 19.5),
	WeatherStation("Erzurum", 5.1),
	WeatherStation("Fairbanks", -2.3),
	WeatherStation("Fianarantsoa", 17.9),
	WeatherStation("Flores, Petén", 26.4),
	WeatherStation("Frankfurt", 10.6),
	WeatherStation("Fresno", 17.9),
	WeatherStation("Fukuoka", 17.0),
	WeatherStation("Gabès", 19.5),
	WeatherStation("Gaborone", 21.0),
	WeatherStation("Gagnoa", 26.0),
	WeatherStation("Gangtok", 15.2),
	WeatherStation("Garissa", 29.3),
	WeatherStation("Garoua", 28.3),
	WeatherStation("George Town", 27.9),
	WeatherStation("Ghanzi", 21.4),
	WeatherStation("Gjoa Haven", -14.4),
	WeatherStation("Guadalajara", 20.9),
	WeatherStation("Guangzhou", 22.4),
	WeatherStation("Guatemala City", 20.4),
	WeatherStation("Halifax", 7.5),
	WeatherStation("Hamburg", 9.7),
	WeatherStation("Hamilton", 13.8),
	WeatherStation("Hanga Roa", 20.5),
	WeatherStation("Hanoi", 23.6),
	WeatherStation("Harare", 18.4),
	WeatherStation("Harbin", 5.0),
	WeatherStation("Hargeisa", 21.7),
	WeatherStation("Hat Yai", 27.0),
	WeatherStation("Havana", 25.2),
	WeatherStation("Helsinki", 5.9),
	WeatherStation("Heraklion", 18.9),
	WeatherStation("Hiroshima", 16.3),
	WeatherStation("Ho Chi Minh City", 27.4),
	WeatherStation("Hobart", 12.7),
	WeatherStation("Hong Kong", 23.3),
	WeatherStation("Honiara", 26.5),
	WeatherStation("Honolulu", 25.4),
	WeatherStation("Houston", 20.8),
	WeatherStation("Ifrane", 11.4),
	WeatherStation("Indianapolis", 11.8),
	WeatherStation("Iqaluit", -9.3),
	WeatherStation("Irkutsk", 1.0),
	WeatherStation("Istanbul", 13.9),
	WeatherStation("İzmir", 17.9),
	WeatherStation("Jacksonville", 20.3),
	WeatherStation("Jakarta", 26.7),
	WeatherStation("Jayapura", 27.0),
	WeatherStation("Jerusalem", 18.3),
	WeatherStation("Johannesburg", 15.5),
	WeatherStation("Jos", 22.8),
	WeatherStation("Juba", 27.8),
	WeatherStation("Kabul", 12.1),
	WeatherStation("Kampala", 20.0),
	WeatherStation("Kandi", 27.7),
	WeatherStation("Kankan", 26.5),
	WeatherStation("Kano", 26.4),
	WeatherStation("Kansas City", 12.5),
	WeatherStation("Karachi", 26.0),
	WeatherStation("Karonga", 24.4),
	WeatherStation("Kathmandu", 18.3),
	WeatherStation("Khartoum", 29.9),
	WeatherStation("Kingston", 27.4),
	WeatherStation("Kinshasa", 25.3),
	WeatherStation("Kolkata", 26.7),
	WeatherStation("Kuala Lumpur", 27.3),
	WeatherStation("Kumasi", 26.0),
	WeatherStation("Kunming", 15.7),
	WeatherStation("Kuopio", 3.4),
	WeatherStation("Kuwait City", 25.7),
	WeatherStation("Kyiv", 8.4),
	WeatherStation("Kyoto", 15.8),
	WeatherStation("La Ceiba", 26.2),
	WeatherStation("La Paz", 23.7),
	WeatherStation("Lagos", 26.8),
	WeatherStation("Lahore", 24.3),
	WeatherStation("Lake Havasu City", 23.7),
	WeatherStation("Lake Tekapo", 8.7),
	WeatherStation("Las Palmas de Gran Canaria", 21.2),
	WeatherStation("Las Vegas", 20.3),
	WeatherStation("Launceston", 13.1),
	WeatherStation("Lhasa", 7.6),
	WeatherStation("Libreville", 25.9),
	WeatherStation("Lisbon", 17.5),
	WeatherStation("Livingstone", 21.8),
	WeatherStation("Ljubljana", 10.9),
	WeatherStation("Lodwar", 29.3),
	WeatherStation("Lomé", 26.9),
	WeatherStation("London", 11.3),
	WeatherStation("Los Angeles", 18.6),
	WeatherStation("Louisville", 13.9),
	WeatherStation("Luanda", 25.8),
	WeatherStation("Lubumbashi", 20.8),
	WeatherStation("Lusaka", 19.9),
	WeatherStation("Luxembourg City", 9.3),
	WeatherStation("Lviv", 7.8),
	WeatherStation("Lyon", 12.5),
	WeatherStation("Madrid", 15.0),
	WeatherStation("Mahajanga", 26.3),
	WeatherStation("Makassar", 26.7),
	WeatherStation("Makurdi", 26.0),
	WeatherStation("Malabo", 26.3),
	WeatherStation("Malé", 28.0),
	WeatherStation("Managua", 27.3),
	WeatherStation("Manama", 26.5),
	WeatherStation("Mandalay", 28.0),
	WeatherStation("Mango", 28.1),
	WeatherStation("Manila", 28.4),
	WeatherStation("Maputo", 22.8),
	WeatherStation("Marrakesh", 19.6),
	WeatherStation("Marseille", 15.8),
	WeatherStation("Maun", 22.4),
	WeatherStation("Medan", 26.5),
	WeatherStation("Mek'ele", 22.7),
	WeatherStation("Melbourne", 15.1),
	WeatherStation("Memphis", 17.2),
	WeatherStation("Mexicali", 23.1),
	WeatherStation("Mexico City", 17.5),
	WeatherStation("Miami", 24.9),
	WeatherStation("Milan", 13.0),
	WeatherStation("Milwaukee", 8.9),
	WeatherStation("Minneapolis", 7.8),
	WeatherStation("Minsk", 6.7),
	WeatherStation("Mogadishu", 27.1),
	WeatherStation("Mombasa", 26.3),
	WeatherStation("Monaco", 16.4),
	WeatherStation("Moncton", 6.1),
	WeatherStation("Monterrey", 22.3),
	WeatherStation("Montreal", 6.8),
	WeatherStation("Moscow", 5.8),
	WeatherStation("Mumbai", 27.1),
	WeatherStation("Murmansk", 0.6),
	WeatherStation("Muscat", 28.0),
	WeatherStation("Mzuzu", 17.7),
	WeatherStation("N'Djamena", 28.3),
	WeatherStation("Naha", 23.1),
	WeatherStation("Nairobi", 17.8),
	WeatherStation("Nakhon Ratchasima", 27.3),
	WeatherStation("Napier", 14.6),
	WeatherStation("Napoli", 15.9),
	WeatherStation("Nashville", 15.4),
	WeatherStation("Nassau", 24.6),
	WeatherStation("Ndola", 20.3),
	WeatherStation("New Delhi", 25.0),
	WeatherStation("New Orleans", 20.7),
	WeatherStation("New York City", 12.9),
	WeatherStation("Ngaoundéré", 22.0),
	WeatherStation("Niamey", 29.3),
	WeatherStation("Nicosia", 19.7),
	WeatherStation("Niigata", 13.9),
	WeatherStation("Nouadhibou", 21.3),
	WeatherStation("Nouakchott", 25.7),
	WeatherStation("Novosibirsk", 1.7),
	WeatherStation("Nuuk", -1.4),
	WeatherStation("Odesa", 10.7),
	WeatherStation("Odienné", 26.0),
	WeatherStation("Oklahoma City", 15.9),
	WeatherStation("Omaha", 10.6),
	WeatherStation("Oranjestad", 28.1),
	WeatherStation("Oslo", 5.7),
	WeatherStation("Ottawa", 6.6),
	WeatherStation("Ouagadougou", 28.3),
	WeatherStation("Ouahigouya", 28.6),
	WeatherStation("Ouarzazate", 18.9),
	WeatherStation("Oulu", 2.7),
	WeatherStation("Palembang", 27.3),
	WeatherStation("Palermo", 18.5),
	WeatherStation("Palm Springs", 24.5),
	WeatherStation("Palmerston North", 13.2),
	WeatherStation("Panama City", 28.0),
	WeatherStation("Parakou", 26.8),
	WeatherStation("Paris", 12.3),
	WeatherStation("Perth", 18.7),
	WeatherStation("Petropavlovsk-Kamchatsky", 1.9),
	WeatherStation("Philadelphia", 13.2),
	WeatherStation("Phnom Penh", 28.3),
	WeatherStation("Phoenix", 23.9),
	WeatherStation("Pittsburgh", 10.8),
	WeatherStation("Podgorica", 15.3),
	WeatherStation("Pointe-Noire", 26.1),
	WeatherStation("Pontianak", 27.7),
	WeatherStation("Port Moresby", 26.9),
	WeatherStation("Port Sudan", 28.4),
	WeatherStation("Port Vila", 24.3),
	WeatherStation("Port-Gentil", 26.0),
	WeatherStation("Portland (OR)", 12.4),
	WeatherStation("Porto", 15.7),
	WeatherStation("Prague", 8.4),
	WeatherStation("Praia", 24.4),
	WeatherStation("Pretoria", 18.2),
	WeatherStation("Pyongyang", 10.8),
	WeatherStation("Rabat", 17.2),
	WeatherStation("Rangpur", 24.4),
	WeatherStation("Reggane", 28.3),
	WeatherStation("Reykjavík", 4.3),
	WeatherStation("Riga", 6.2),
	WeatherStation("Riyadh", 26.0),
	WeatherStation("Rome", 15.2),
	WeatherStation("Roseau", 26.2),
	WeatherStation("Rostov-on-Don", 9.9),
	WeatherStation("Sacramento", 16.3),
	WeatherStation("Saint Petersburg", 5.8),
	WeatherStation("Saint-Pierre", 5.7),
	WeatherStation("Salt Lake City", 11.6),
	WeatherStation("San Antonio", 20.8),
	WeatherStation("San Diego", 17.8),
	WeatherStation("San Francisco", 14.6),
	WeatherStation("San Jose", 16.4),
	WeatherStation("San José", 22.6),
	WeatherStation("San Juan", 27.2),
	WeatherStation("San Salvador", 23.1),
	WeatherStation("Sana'a", 20.0),
	WeatherStation("Santo Domingo", 25.9),
	WeatherStation("Sapporo", 8.9),
	WeatherStation("Sarajevo", 10.1),
	WeatherStation("Saskatoon", 3.3),
	WeatherStation("Seattle", 11.3),
	WeatherStation("Ségou", 28.0),
	WeatherStation("Seoul", 12.5),
	WeatherStation("Seville", 19.2),
	WeatherStation("Shanghai", 16.7),
	WeatherStation("Singapore", 27.0),
	WeatherStation("Skopje", 12.4),
	WeatherStation("Sochi", 14.2),
	WeatherStation("Sofia", 10.6),
	WeatherStation("Sokoto", 28.0),
	WeatherStation("Split", 16.1),
	WeatherStation("St. John's", 5.0),
	WeatherStation("St. Louis", 13.9),
	WeatherStation("Stockholm", 6.6),
	WeatherStation("Surabaya", 27.1),
	WeatherStation("Suva", 25.6),
	WeatherStation("Suwałki", 7.2),
	WeatherStation("Sydney", 17.7),
	WeatherStation("Tabora", 23.0),
	WeatherStation("Tabriz", 12.6),
	WeatherStation("Taipei", 23.0),
	WeatherStation("Tallinn", 6.4),
	WeatherStation("Tamale", 27.9),
	WeatherStation("Tamanrasset", 21.7),
	WeatherStation("Tampa", 22.9),
	WeatherStation("Tashkent", 14.8),
	WeatherStation("Tauranga", 14.8),
	WeatherStation("Tbilisi", 12.9),
	WeatherStation("Tegucigalpa", 21.7),
	WeatherStation("Tehran", 17.0),
	WeatherStation("Tel Aviv", 20.0),
	WeatherStation("Thessaloniki", 16.0),
	WeatherStation("Thiès", 24.0),
	WeatherStation("Tijuana", 17.8),
	WeatherStation("Timbuktu", 28.0),
	WeatherStation("Tirana", 15.2),
	WeatherStation("Toamasina", 23.4),
	WeatherStation("Tokyo", 15.4),
	WeatherStation("Toliara", 24.1),
	WeatherStation("Toluca", 12.4),
	WeatherStation("Toronto", 9.4),
	WeatherStation("Tripoli", 20.0),
	WeatherStation("Tromsø", 2.9),
	WeatherStation("Tucson", 20.9),
	WeatherStation("Tunis", 18.4),
	WeatherStation("Ulaanbaatar", -0.4),
	WeatherStation("Upington", 20.4),
	WeatherStation("Ürümqi", 7.4),
	WeatherStation("Vaduz", 10.1),
	WeatherStation("Valencia", 18.3),
	WeatherStation("Valletta", 18.8),
	WeatherStation("Vancouver", 10.4),
	WeatherStation("Veracruz", 25.4),
	WeatherStation("Vienna", 10.4),
	WeatherStation("Vientiane", 25.9),
	WeatherStation("Villahermosa", 27.1),
	WeatherStation("Vilnius", 6.0),
	WeatherStation("Virginia Beach", 15.8),
	WeatherStation("Vladivostok", 4.9),
	WeatherStation("Warsaw", 8.5),
	WeatherStation("Washington, D.C.", 14.6),
	WeatherStation("Wau", 27.8),
	WeatherStation("Wellington", 12.9),
	WeatherStation("Whitehorse", -0.1),
	WeatherStation("Wichita", 13.9),
	WeatherStation("Willemstad", 28.0),
	WeatherStation("Winnipeg", 3.0),
	WeatherStation("Wrocław", 9.6),
	WeatherStation("Xi'an", 14.1),
	WeatherStation("Yakutsk", -8.8),
	WeatherStation("Yangon", 27.5),
	WeatherStation("Yaoundé", 23.8),
	WeatherStation("Yellowknife", -4.3),
	WeatherStation("Yerevan", 12.4),
	WeatherStation("Yinchuan", 9.0),
	WeatherStation("Zagreb", 10.7),
	WeatherStation("Zanzibar City", 26.0),
	WeatherStation("Zürich", 9.3)]


	open("measurements.txt", "w") do file
	for i in 1:size
	if i > 1 && i % 50_000_000 == 0
	println("Wrote $i measurements in $(time() - start) s")
	end
	station = stations[rand(1:length(stations))]
	write(file, station.id * ";" * string(measurement(station)) * "\n")
	end
	end

	println("Created file with $size measurements in $(time() - start) s")
	end

	main()
	# Naive solution with DataFrames.jl

	using CSV, DataFrames, Statistics

	function main()
	df = CSV.read("measurements.txt", DataFrame; header=[:station, :temperature], delim=";")
	df_out = combine(groupby(df, :station), :temperature => mean, :temperature => minimum, :temperature => maximum)
	transform!(df_out, [:temperature_mean, :temperature_minimum, :temperature_maximum] .=> ByRow(x -> round(x; digits=1)), renamecols=false)
	sort!(df_out, :station)
	for row in eachrow(df_out)
	# print on new lines, instead of comma separated as the original challenge
	println(row.station, "=", row.temperature_mean, "/", row.temperature_minimum, "/", row.temperature_maximum)
	end
	end

	@time main()
	# 1M rows: 0.9s
	# 10M rows: 9.3s
	# generated with GPT4 to read the stream

	function calculate_stations(filename)
	totals = Dict{String,Float64}()
	counts = Dict{String,Int}()
	mins = Dict{String,Float64}()
	maxs = Dict{String,Float64}()

	open(filename, "r") do file
	while !eof(file)
	station = readuntil(file, ';')
	temp_str = readuntil(file, '\n')
	temp = parse(Float64, temp_str)

	# Update totals and counts
	totals[station] = get(totals, station, 0.0) + temp
	counts[station] = get(counts, station, 0) + 1

	# Update minimum temperature
	if !haskey(mins, station) \|\| temp < mins[station]
	mins[station] = temp
	end

	# Update maximum temperature
	if !haskey(maxs, station) \|\| temp > maxs[station]
	maxs[station] = temp
	end
	end
	end

	# Calculate mean and sort the stations
	sorted_stations = sort(collect(keys(totals)))
	for station in sorted_stations
	mean_temp = round(totals[station] / counts[station], digits=1)
	min_temp = round(mins[station], digits=1)
	max_temp = round(maxs[station], digits=1)
	println("$station=$min_temp/$mean_temp/$max_temp")
	end
	end

	# Usage
	@time calculate_stations("measurements.txt")

	# 10M rows: 5s
	# 100M rows: 27s