docs.sheetjs.com/16-postgresql.md at 9230a968c33ec6a53c30aa5721f7529ef68c573f

LankyMoose/docs.sheetjs.com

Fork 0

forked from sheetjs/docs.sheetjs.com

SheetJS e3ca16d997 node-sea

2024-03-19 05:00:03 -04:00

12 KiB

Raw Blame History

title

sidebar_label

pagination_prev

pagination_next

sidebar_custom_props

Sheets with PostgreSQL

PostgreSQL

demos/cli/index

demos/local/index

sql
true

import current from '/version.js'; import CodeBlock from '@theme/CodeBlock';

PostgreSQL (colloquially referenced as "Postgres") is an open source object-relational database system.

SheetJS is a JavaScript library for reading and writing data from spreadsheets.

This demo uses SheetJS to exchange data between spreadsheets and PostgreSQL databases. We'll explore how to save tables from a database to spreadsheets and how to add data from spreadsheets into a database.

:::caution pass

It is strongly recommended to use PostgreSQL with a query builder or ORM.

While it is possible to generate SQL statements directly, there are many subtle details and pitfalls. Battle-tested solutions generally provide mitigations against SQL injection and other vulnerabilities.

:::

:::note Tested Deployments

This demo was tested in the following environments:

Postgres	Connector Library	Date
`16.0.1`	`pg` (`8.11.3`)	2023-10-30
`15.5`	`pg` (`8.11.3`)	2023-12-04

:::

Integration Details

The SheetJS NodeJS module can be loaded in NodeJS scripts that connect to PostgreSQL databases.

This demo uses the pg connector module¹, but the same mechanics apply to other PostgreSQL libraries.

Exporting Data

Client#query returns a Promise that resolves to a result set. The rows property of the result is an array of objects.

The SheetJS json_to_sheet method² can generate a worksheet object³ from the array of objects:

const table_name = "Tabeller1"; // name of table

/* fetch all data from specified table */
const res = await client.query(`SELECT * FROM ${table_name}`);

/* generate a SheetJS worksheet object from the data */
const worksheet = XLSX.utils.json_to_sheet(res.rows);

A workbook object can be built from the worksheet using utility functions⁴. The workbook can be exported using the SheetJS writeFile method⁵:

/* create a new workbook and add the worksheet */
const wb = XLSX.utils.book_new();
XLSX.utils.book_append_sheet(wb, worksheet, "Sheet1");

/* export workbook to XLSX */
XLSX.writeFile(wb, "SheetJSPGExport.xlsx");

Importing Data

The SheetJS sheet_to_json function⁶ takes a worksheet object and generates an array of objects.

Queries must be manually generated from the objects. Assuming the field names in the object match the column headers, a loop can generate INSERT queries.

:::warning pass

PostgreSQL does not allow parameterized queries with variable column names

INSERT INTO table_name (?) VALUES (?);
-- ---------------------^ variable column names are not valid

Queries are generated manually. To help prevent SQL injection vulnerabilities, the pg-format⁷ module escapes identifiers and fields.

:::

/* generate an array of arrays from the worksheet */
const aoo = XLSX.utils.sheet_to_json(ws);

const table_name = "Blatte1"; // name of table

/* loop through the data rows */
for(let row of aoo) {

  /* generate format helper strings */
  const ent = Object.entries(row);
  const Istr = Array.from({length: entries.length}, ()=>"%I").join(", ");
  const Lstr = Array.from({length: entries.length}, ()=>"%L").join(", ");

  /* generate INSERT statement */
  let query = format.withArray(
    `INSERT INTO %I (${Istr}) VALUES(${Lstr})`,
    [ table_name, ...ent.map(x => x[0]), ...ent.map(x => x[1]) ]
  );

  /* execute INSERT statement */
  await client.query(query);
}

Creating a Table

The array of objects can be scanned to determine column names and types. With the names and types, a CREATE TABLE query can be written.

Implementation Details (click to show)

The aoo_to_pg_table function:

scans each row object to determine column names and types
drops and creates a new table with the determined column names and types
loads the entire dataset into the new table

/* create table and load data given an array of objects and a PostgreSQL client */
async function aoo_to_pg_table(client, aoo, table_name) {
  /* define types that can be converted (e.g. boolean can be stored in float) */
  const T_FLOAT = ["float8", "boolean"];
  const T_BOOL = ["boolean"];

  /* types is a map from column headers to Knex schema column type */
  const types = {};

  /* names is an ordered list of the column header names */
  const names = [];

  /* loop across each row object */
  aoo.forEach(row =>
    /* Object.entries returns a row of [key, value] pairs */
    Object.entries(row).forEach(([k,v]) => {

      /* If this is first occurrence, mark unknown and append header to names */
      if(!types[k]) { types[k] = ""; names.push(k); }

      /* skip null and undefined values */
      if(v == null) return;

      /* check and resolve type */
      switch(typeof v) {
        /* change type if it is empty or can be stored in a float */
        case "number": if(!types[k] || T_FLOAT.includes(types[k])) types[k] = "float8"; break;
        /* change type if it is empty or can be stored in a boolean */
        case "boolean": if(!types[k] || T_BOOL.includes(types[k])) types[k] = "boolean"; break;
        /* no other type can hold strings */
        case "string": types[k] = "text"; break;
        default: types[k] = "text"; break;
      }
    })
  );

  /* Delete table if it exists in the DB */
  const query = format("DROP TABLE IF EXISTS %I;", table_name);
  await client.query(query);

  /* Create table */
  {
    const entries = Object.entries(types);
    const Istr = entries.map(e => format(`%I ${e[1]}`, e[0])).join(", ");
    let query = format.withArray(`CREATE TABLE %I (${Istr});`, [ table_name ]);
    await client.query(query);
  }

  /* Insert each row */
  for(let row of aoo) {
    const ent = Object.entries(row);
    const Istr = Array.from({length: ent.length}, ()=>"%I").join(", ");
    const Lstr = Array.from({length: ent.length}, ()=>"%L").join(", ");
    let query = format.withArray(
      `INSERT INTO %I (${Istr}) VALUES (${Lstr});`,
      [ table_name, ...ent.map(x => x[0]), ...ent.map(x => x[1]) ]
    );
    await client.query(query);
  }

  return client;
}

Complete Example

Install and start the PostgreSQL server.

Installation Notes (click to show)

On macOS, install the postgresql formula with Homebrew:

brew install postgresql@16

The last few lines of the installer explain how to start the database:

Or, if you don't want/need a background service you can just run:
// highlight-next-line
  LC_ALL="C" /usr/local/opt/postgresql@16/bin/postgres -D /usr/local/var/postgresql@16

Run the command to start a local database instance.

Drop any existing database with the name SheetJSPG:

dropdb SheetJSPG

:::info pass

If the server is running elsewhere, or if the username is different from the current user, command-line flags can override the defaults.

Option	Explanation
`-h HOSTNAME`	Name of the server
`-p PORT`	specifies the port number
`-U USERNAME`	specifies the username

:::

Create an empty SheetJSPG database using the createdb command:

createdb SheetJSPG

:::note pass

createdb supports the same -h, -p, and -U flags as dropdb.

:::

Connector Test

Create a project folder:

mkdir sheetjs-pg
cd sheetjs-pg
npm init -y

Install the pg connector module:

npm i --save pg@8.11.3

Save the following example codeblock to PGTest.js:

const pg = require("pg");
const client = new pg.Client({
  database:"SheetJSPG",
// highlight-start
  host: "127.0.0.1", // localhost
  port: 5432,
  //user: "",
  //password: ""
// highlight-end
});
(async() => {

await client.connect();
const res = await client.query('SELECT $1::text as message', ['Hello world!']);
console.log(res.rows[0].message); // Hello world!
await client.end();

})();

Edit the new PGTest.js script and modify the highlighted lines from the codeblock to reflect the database deployment settings.

The settings in the codeblock match the default configuration for macOS Homebrew PostgreSQL server. For other deployments:

If the server is not running on your computer, set host and port to the correct host name and port number.
If the server expects a different username and password, uncomment the user and password lines and replace the values with the username and password.

Run the script:

node PGTest.js

It should print Hello world!

:::caution pass

If the output is not Hello world! or if there is an error, please report the issue to the pg connector project for further diagnosis.

:::

Add SheetJS

Install dependencies:

{\ npm i --save https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz pg-format@1.0.4}

Download SheetJSPG.js:

curl -LO https://docs.sheetjs.com/postgresql/SheetJSPG.js

This script will:

read and parse the test file pres.numbers
create a connection to the SheetJSPG database on a local PostgreSQL server
load data from the first worksheet into a table with name Presidents
disconnect and reconnect to the database
dump data from the table Presidents
export the dataset to SheetJSPG.xlsx

Edit the SheetJSPG.js script.

The script defines an opts object:

const XLSX = require("xlsx");
const opts = {
  database:"SheetJSPG",
// highlight-start
  host: "127.0.0.1", // localhost
  port: 5432,
  //user: "",
  //password: ""
// highlight-end
};