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5.6 KiB
5.6 KiB
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SQL Connectors | demos/cli/index | demos/local/index |
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import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';
Generating Tables
This example will fetch https://sheetjs.com/data/cd.xls, scan the columns of the first worksheet to determine data types, and generate 6 PostgreSQL statements.
Explanation (click to show)
The relevant generate_sql
function takes a worksheet name and a table name:
// define mapping between determined types and PostgreSQL types
const PG = { "n": "float8", "s": "text", "b": "boolean" };
function generate_sql(ws, wsname) {
// generate an array of objects from the data
const aoo = XLSX.utils.sheet_to_json(ws);
// types will map column headers to types, while hdr holds headers in order
const types = {}, hdr = [];
// loop across each row object
aoo.forEach(row =>
// Object.entries returns a row of [key, value] pairs. Loop across those
Object.entries(row).forEach(([k,v]) => {
// If this is first time seeing key, mark unknown and append header array
if(!types[k]) { types[k] = "?"; hdr.push(k); }
// skip null and undefined
if(v == null) return;
// check and resolve type
switch(typeof v) {
case "string": // strings are the broadest type
types[k] = "s"; break;
case "number": // if column is not string, number is the broadest type
if(types[k] != "s") types[k] = "n"; break;
case "boolean": // only mark boolean if column is unknown or boolean
if("?b".includes(types[k])) types[k] = "b"; break;
default: types[k] = "s"; break; // default to string type
}
})
);
// The final array consists of the CREATE TABLE query and a series of INSERTs
return [
// generate CREATE TABLE query and return batch
`CREATE TABLE \`${wsname}\` (${hdr.map(h =>
// column name must be wrapped in backticks
`\`${h}\` ${PG[types[h]]}`
).join(", ")});`
].concat(aoo.map(row => { // generate INSERT query for each row
// entries will be an array of [key, value] pairs for the data in the row
const entries = Object.entries(row);
// fields will hold the column names and values will hold the values
const fields = [], values = [];
// check each key/value pair in the row
entries.forEach(([k,v]) => {
// skip null / undefined
if(v == null) return;
// column name must be wrapped in backticks
fields.push(`\`${k}\``);
// when the field type is numeric, `true` -> 1 and `false` -> 0
if(types[k] == "n") values.push(typeof v == "boolean" ? (v ? 1 : 0) : v);
// otherwise,
else values.push(`'${v.toString().replaceAll("'", "''")}'`);
})
if(fields.length) return `INSERT INTO \`${wsname}\` (${fields.join(", ")}) VALUES (${values.join(", ")})`;
})).filter(x => x); // filter out skipped rows
}
function SheetJSQLWriter() {
// define mapping between determined types and PostgreSQL types
const PG = { "n": "float8", "s": "text", "b": "boolean" };
function generate_sql(ws, wsname) {
const aoo = XLSX.utils.sheet_to_json(ws);
const types = {}, hdr = [];
// loop across each key in each column
aoo.forEach(row => Object.entries(row).forEach(([k,v]) => {
// set up type if header hasn't been seen
if(!types[k]) { types[k] = "?"; hdr.push(k); }
// check and resolve type
switch(typeof v) {
case "string": types[k] = "s"; break;
case "number": if(types[k] != "s") types[k] = "n"; break;
case "boolean": if("?b".includes(types[k])) types[k] = "b"; break;
default: types[k] = "s"; break;
}
}));
return [
// generate CREATE TABLE query and return batch
`CREATE TABLE \`${wsname}\` (${hdr.map(h => `\`${h}\` ${PG[types[h]]}`).join(", ")});`
].concat(aoo.map(row => {
const entries = Object.entries(row);
const fields = [], values = [];
entries.forEach(([k,v]) => {
if(v == null) return;
fields.push(`\`${k}\``);
if(types[k] == "n") values.push(typeof v == "boolean" ? (v ? 1 : 0) : v);
else values.push(`'${v.toString().replaceAll("'", "''")}'`);
})
if(fields.length) return `INSERT INTO \`${wsname}\` (${fields.join(", ")}) VALUES (${values.join(", ")})`;
})).filter(x => x).slice(0, 6);
}
const [url, setUrl] = React.useState("https://sheetjs.com/data/cd.xls");
const set_url = (evt) => setUrl(evt.target.value);
const [out, setOut] = React.useState("");
const xport = React.useCallback(async() => {
const ab = await (await fetch(url)).arrayBuffer();
const wb = XLSX.read(ab), wsname = wb.SheetNames[0];
setOut(generate_sql(wb.Sheets[wsname], wsname).join("\n"));
});
return ( <> {out && ( <><a href={url}>{url}</a><pre>{out}</pre></> )}
<b>URL: </b><input type="text" value={url} onChange={set_url} size="50"/>
<br/><button onClick={xport}><b>Fetch!</b></button>
</> );
}
Databases
Query Builders
Query builders are designed to simplify query generation and normalize field types and other database minutiae.
Knex
The exposition has been moved to a separate page.
Other SQL Databases
The generate_sql
function from "Building Schemas from Worksheets"
can be adapted to generate SQL statements for a variety of databases, including:
PostgreSQL
The exposition has been moved to a separate page.
MySQL / MariaDB