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The Swagger automatic API client generation is not working, nor likely to work anytime soon (see #62 ). This patch deprecates the automatic Swagger client generation, and includes custom example code for using the API in Matlab (already written), Python (fixed), and Julia (new). The Julia code should close #96 when acceptable.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,159 @@ | ||
| import React, {useState, useEffect} from "react"; | ||
| import SyntaxHighlighter from 'react-syntax-highlighter'; | ||
| import { docco } from 'react-syntax-highlighter/dist/cjs/styles/hljs'; | ||
| import Typography from '@mui/material/Typography'; | ||
| import Connection from "./APIConnection"; | ||
| import {CircularProgress} from "@mui/material"; | ||
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| export default function GetDatasetJulia({dataset}) { | ||
| const token = Connection.user?.token; | ||
| const [columns, setColumns] = useState("") | ||
| const [code, setCode] = useState(<CircularProgress/>) | ||
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| let domain = window.location.href.split('/')[2]; | ||
| domain = domain.split(':')[0] | ||
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| const host = `http://api.${domain}` | ||
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| useEffect(() => { | ||
| Promise.all(dataset.columns.map(column => | ||
| Connection.fetch(column) | ||
| .then(r => r.content) | ||
| .then(col => ` '${col.name}': ${col.id},`) | ||
| )) | ||
| .then(cols => setColumns(cols.join('\n'))) | ||
| }, [dataset]) | ||
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| useEffect(() => { | ||
| if (!columns) | ||
| setCode(<CircularProgress/>) | ||
| else | ||
| setCode( | ||
| <SyntaxHighlighter language="julia" style={docco}>{ | ||
| `# SPDX-License-Identifier: BSD-2-Clause | ||
| # Copyright (c) 2020-2023, The Chancellor, Masters and Scholars of the University | ||
| # of Oxford, and the 'Galv' Developers. All rights reserved. | ||
| using HTTP | ||
| using JSON | ||
| host = "${host}" | ||
| headers = Dict{String, String}("Authorization" => "Bearer ${token}") | ||
| # Configuration | ||
| verbose = true | ||
| dataset_ids = [${dataset.id}] | ||
| api_data = Dict{Int, Dict{String, Any}}() | ||
| function vprintln(s) | ||
| if verbose | ||
| println(s) | ||
| end | ||
| end | ||
| function get_column_values(dataset_id, column) | ||
| url = column["values"] | ||
| if url == "" | ||
| return | ||
| end | ||
| column_name = column["name"] | ||
| dtype = column["data_type"] | ||
| vprintln("Downloading values for column $dataset_id:$column_name [$url]") | ||
| response = HTTP.request("GET", url, headers) | ||
| try | ||
| body = String(response.body) | ||
| str_values = split(body, '\n') | ||
| values = Vector{String}(str_values[begin:end-1]) | ||
| if dtype == "float" | ||
| return map((x -> parse(Float64, x)), values) | ||
| elseif dtype == "int" | ||
| return map((x -> parse(Int64, x)), values) | ||
| else | ||
| return convert(String, values) | ||
| end | ||
| catch | ||
| println("Error parsing values $dataset_id:$column_name [$url]") | ||
| return | ||
| end | ||
| end | ||
| function get_column(dataset_id, url) | ||
| vprintln("Downloading column $url") | ||
| response = HTTP.request("GET", url, headers) | ||
| column = Dict{String, Any}() | ||
| try | ||
| column = JSON.parse(String(response.body)) | ||
| catch | ||
| println("Error parsing JSON for column $url") | ||
| return | ||
| end | ||
| # Download column values | ||
| values = get_column_values(dataset_id, column) | ||
| pop!(column, "values", "") | ||
| column["values"] = values | ||
| return column | ||
| end | ||
| function get_dataset(id) | ||
| vprintln("Downloading dataset $id") | ||
| response = HTTP.request("GET", "$host/datasets/$id", headers) | ||
| body = Dict{String, Any}() | ||
| try | ||
| body = JSON.parse(String(response.body)) | ||
| catch | ||
| println("Error parsing JSON for dataset $id") | ||
| return | ||
| end | ||
| api_data[id] = body | ||
| # Download columns | ||
| columns = api_data[id]["columns"] | ||
| len = length(columns) | ||
| vprintln("Downloading $len columns for dataset $id") | ||
| for (i, col) in enumerate(columns) | ||
| timings = @timed column = get_column(id, col) | ||
| api_data[id]["columns"][i] = column | ||
| n = column["name"] | ||
| s = round(timings.time, digits = 2) | ||
| vprintln("Column $n completed in $s seconds") | ||
| end | ||
| vprintln("Completed.") | ||
| end | ||
| for id in dataset_ids | ||
| timings = @timed get_dataset(id) | ||
| s = round(timings.time, digits = 2) | ||
| vprintln("Completed dataset $id in $s seconds") | ||
| end | ||
| vprintln("All datasets complete.") | ||
| ` | ||
| }</SyntaxHighlighter> | ||
| ) | ||
| }, [columns, dataset.id, host, token]) | ||
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||
| return ( | ||
| <React.Fragment> | ||
| <Typography> | ||
| Julia Code | ||
| </Typography> | ||
|
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| {code} | ||
| </React.Fragment> | ||
| ) | ||
| } |
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