141 lines
1.8 KiB
Julia
141 lines
1.8 KiB
Julia
# ---------------------------------------------- 100 --------------------------------------------- #
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using JSON3, MQTTClient, Dates, UUIDs, PrettyPrinting, LibPQ, Base64, DataFrames
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using GeneralUtils
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config = copy(JSON3.read("config.json"))
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msgMeta = GeneralUtils.generate_msgMeta(
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"/yiem_branch_1/agent/wine/backend/db/api/v1/testing";
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senderName = "wine_assistant_admin",
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senderId= string(uuid4()),
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mqttBrokerAddress= config[:mqttServerInfo][:broker],
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mqttBrokerPort= config[:mqttServerInfo][:port],
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)
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outgoingMsg = Dict(
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:msgMeta=> msgMeta,
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:payload=> Dict(
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:functioncall=> "search_materWineTable",
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:args=> Dict(
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:columnname=> "wine_name",
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:searchkeyword=> "Yarra",
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)
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)
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)
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raw = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
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sql =
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"""
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SELECT * FROM wine WHERE wine_name ILIKE '%yarra%';
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"""
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DBconnection = LibPQ.Connection("host=192.168.88.12 port=5432 dbname=yiem_wine_assistant user=yiem password=yiem@Postgres_0.0")
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result = LibPQ.execute(DBconnection, sql)
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LibPQ.close(DBconnection)
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a = columntable(result)
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""" Convert a DataFrame into a list of JSON rows.
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# Arguments
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- `df::DataFrame`
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The input DataFrame to be converted.
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# Return
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- `rows::Vector{Dict{String, Any}}`
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A vector of dictionaries, where each dictionary represents a row in JSON format.
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# Example
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```jldoctest
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julia> using DataFrame, JSON3
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julia> df = DataFrame(A = [1, 2, 3], B = ["apple", "banana", "cherry"])
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julia> json_rows = dfToJSONRows(df)
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```
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# Signature
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"""
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function dfToJSONRows(df::DataFrame)
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rows = []
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for row in eachrow(df)
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json_row = Dict{String, Any}()
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for col in names(df)
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json_row[col] = row[col]
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end
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push!(rows, json_row)
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end
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return rows
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end
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open("d.json", "w") do io
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JSON3.pretty(io, result)
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end
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