Skip to main content

ActualQL Examples

Searching by month or year​

ActualQL supports various functions to convert data, as well as the ability to convert field data. For example, saying { $month: '2021-01-01' } would come back with the month of 2021-01. But we need a way to apply that to the date field, and we use $transform for that.

This part deserves better docs, but here's a reference example you can use to search by month or year:

q('transactions')
  .filter({ date: { $transform: '$month', $eq: '2021-01' } })
  .select('*');

This would return all transactions in the month of 2021-01. We've applied the $month function to the date field and applied the condition of equaling 2021-01.

You can substitute $year to do the same thing for year.

Total Amount per Payee between 6 Apr 2020 and 5 Apr 2021​

(
  await $query(
    $q('transactions')
      .filter({
        $and: [
          { date: { $gte: '2020-04-06' } },
          { date: { $lte: '2021-04-05' } },
        ],
      })
      .groupBy('payee.name')
      .orderBy('payee.name')
      .select(['payee.name', { amount: { $sum: '$amount' } }]),
  )
).data.map(row => {
  console.log(`${row['payee.name']}: ${row.amount / 100}`);
});

Total Amount of all transactions with Note containing #interest (P) between 6 Apr 2020 and 5 Apr 2021​

(
  await $query(
    $q('transactions')
      .filter({
        $and: [
          { date: { $gte: '2020-04-06' } },
          { date: { $lte: '2021-04-05' } },
          { notes: { $like: '%#interest (P)%' } },
        ],
      })
      .calculate({ $sum: '$amount' }),
  )
).data / 100;

or

(
  await $query(
    $q('transactions')
      .filter({
        $and: [
          { date: { $gte: '2020-04-06' } },
          { date: { $lte: '2021-04-05' } },
          { notes: { $like: '%#interest (P)%' } },
        ],
      })
      .select({ total: { $sum: '$amount' } }),
  )
).data[0].total / 100;

Total Amount per Category between 6 Apr 2020 and 5 Apr 2021​

(
  await $query(
    $q('transactions')
      .filter({
        $and: [
          { date: { $gte: '2020-04-06' } },
          { date: { $lte: '2021-04-05' } },
        ],
      })
      .groupBy('category.name')
      .orderBy(['category.group.sort_order', 'category.sort_order'])
      .select([
        'category.group.name',
        'category.name',
        { amount: { $sum: '$amount' } },
      ]),
  )
).data.map(row => {
  console.log(
    `${row['category.group.name']}/${row['category.name']}: ${
      row.amount / 100
    }`,
  );
});