Browsing tables
A file node with display="table" shows its target as an interactive,
read-only table instead of a link or a block of text — a CSV, a TSV, a Parquet
file, JSON lines, anything the duckdb command-line tool
can read (also compressed: .csv.gz). The file is never loaded into the page:
meshfox asks duckdb for the rows on screen, so a file with millions of rows
opens as quickly as one with twenty.
Needs the duckdb executable. meshfox never installs it for you: put it
on PATH, or set duckdb_path under [tables] in .meshfox/config.toml (or
the MESHFOX_DUCKDB environment variable). Without it a table node says so
instead of showing a table.
What you can do with a table, in the browser and — full screen, with Enter —
in the terminal viewer (meshfox tui):
- Sort — click a column header (none → ascending → descending), Shift-click
to add a second key;
s/Sin the terminal. - Filter a column — type into the box under its header (
fin the terminal): plain text contains it (numbers: equals);>10,>=10,<10,=x,!=x;^start,$end,~anywhere;null,!null. - Search every column at once.
- Look at one cell — click it to read the whole value (
Enterin the terminal),y/Cmd-C copies it.
The table is read-only: edit the file with any editor and the node notices the
change and reloads. meshfox static and meshfox pdf print the first 100 rows
as a plain grid — and fail if a table can't be read (no duckdb, no file),
rather than quietly leaving it out.
A small CSV
Twenty-four products, committed next to this canvas. Try filtering price
with >=50, category with kitchen, or note with !null. Empty cells are
NULL.
24 rows × 6 cols
| # | skuvarchar | namevarchar | categoryvarchar | pricedouble | stockbigint | notevarchar |
|---|---|---|---|---|---|---|
| 1 | A-1001 | Desk lamp, brass | lighting | 39.9 | 120 | NULL |
| 2 | A-1002 | Floor lamp | lighting | 89.0 | 35 | ships in 2 boxes |
| 3 | A-1003 | LED bulb 4-pack | lighting | 12.5 | 980 | NULL |
| 4 | B-2001 | Oak shelf 80 cm | furniture | 59.0 | 44 | NULL |
| 5 | B-2002 | Oak shelf 120 cm | furniture | 79.0 | 18 | NULL |
| 6 | B-2003 | Writing desk | furniture | 249.0 | 7 | assembly required |
| 7 | B-2004 | Office chair | furniture | 189.0 | 0 | back in stock in March |
| 8 | C-3001 | Ceramic mug | kitchen | 8.9 | 640 | NULL |
| 9 | C-3002 | Mug set, 6 pcs | kitchen | 44.0 | 90 | NULL |
| 10 | C-3003 | Cast-iron pan 26 cm | kitchen | 64.0 | 52 | NULL |
| 11 | C-3004 | Chef's knife | kitchen | 72.5 | 31 | hand wash only |
| 12 | C-3005 | Cutting board | kitchen | 23.0 | 210 | NULL |
| 13 | D-4001 | Wool blanket | textiles | 69.0 | 60 | NULL |
| 14 | D-4002 | Linen cushion | textiles | 28.0 | 150 | NULL |
| 15 | D-4003 | Cotton towel | textiles | 14.0 | 420 | NULL |
| 16 | D-4004 | Curtain, 140x250 | textiles | 52.0 | 26 | NULL |
| 17 | E-5001 | Notebook A5 | stationery | 4.5 | 1500 | NULL |
| 18 | E-5002 | Fountain pen | stationery | 34.0 | 75 | blue ink included |
| 19 | E-5003 | Ink refill | stationery | 6.0 | 0 | NULL |
| 20 | E-5004 | Desk organiser | stationery | 19.0 | 88 | NULL |
| 21 | F-6001 | Plant pot 20 cm | garden | 11.0 | 330 | NULL |
| 22 | F-6002 | Watering can | garden | 17.5 | 95 | NULL |
| 23 | F-6003 | Garden shears | garden | 26.0 | 40 | NULL |
| 24 | F-6004 | Seed mix | garden | 3.8 | 1200 | sow in spring |
A million rows, generated
The big files below don't live in the repository — this block makes one.
Run it (r in the terminal, the run button in the browser), then watch
events.csv in the next node fill in: a million rows, sorted, filtered and
searched in a fraction of a second after the first, one-time import
(which meshfox keeps in .meshfox/tables/, capped by [tables] cache_max_bytes, 4 GiB by default).
mkdir -p tables-data
awk 'BEGIN {
srand(42)
n = split("EU US APAC LATAM MEA", regions, " ")
print "id,ts,region,amount,note"
for (i = 1; i <= 1000000; i++) {
printf "%d,2026-%02d-%02d %02d:%02d,%s,%.2f,%s\n", i, int(rand()*12)+1, \
int(rand()*28)+1, int(rand()*24), int(rand()*60), \
regions[int(rand()*n)+1], rand()*1000, (i % 7 == 0 ? "" : "order " i)
}
}' > tables-data/events.csv
echo "wrote $(wc -l < tables-data/events.csv) lines"
events.csv
Until generate has run this says the file is missing; afterwards, sort
amount descending, filter region with APAC and ts with 2026-06, or
scroll to the very last row with G in the terminal. A column's type
(bigint, varchar, double, ...) is detected from the data and shown under
its name; numbers are right-aligned.
1,000,000 rows × 5 cols · first 100 shown
| # | idbigint | tstimestamp | regionvarchar | amountdouble | notevarchar |
|---|---|---|---|---|---|
| 1 | 1 | 2026-01-01 17:02:00 | APAC | 927.11 | order 1 |
| 2 | 2 | 2026-08-21 11:24:00 | LATAM | 479.97 | order 2 |
| 3 | 3 | 2026-01-09 05:17:00 | EU | 119.8 | order 3 |
| 4 | 4 | 2026-04-09 10:23:00 | APAC | 158.64 | order 4 |
| 5 | 5 | 2026-11-21 03:04:00 | EU | 42.1 | order 5 |
| 6 | 6 | 2026-03-21 17:43:00 | APAC | 551.66 | order 6 |
| 7 | 7 | 2026-06-20 16:37:00 | US | 219.67 | NULL |
| 8 | 8 | 2026-08-24 12:54:00 | EU | 314.91 | order 8 |
| 9 | 9 | 2026-04-03 10:33:00 | MEA | 688.91 | order 9 |
| 10 | 10 | 2026-04-20 19:32:00 | MEA | 706.41 | order 10 |
| 11 | 11 | 2026-01-05 00:18:00 | LATAM | 852.9 | order 11 |
| 12 | 12 | 2026-06-01 10:40:00 | APAC | 118.86 | order 12 |
| 13 | 13 | 2026-02-21 12:07:00 | EU | 157.41 | order 13 |
| 14 | 14 | 2026-08-18 20:59:00 | EU | 992.06 | NULL |
| 15 | 15 | 2026-01-16 14:27:00 | US | 602.42 | order 15 |
| 16 | 16 | 2026-10-28 07:25:00 | APAC | 408.81 | order 16 |
| 17 | 17 | 2026-10-24 14:56:00 | LATAM | 542.12 | order 17 |
| 18 | 18 | 2026-04-20 00:21:00 | LATAM | 553.21 | order 18 |
| 19 | 19 | 2026-05-12 07:37:00 | EU | 687.69 | order 19 |
| 20 | 20 | 2026-08-19 08:05:00 | LATAM | 584.9 | order 20 |
| 21 | 21 | 2026-06-19 05:49:00 | LATAM | 374.52 | NULL |
| 22 | 22 | 2026-03-19 05:00:00 | US | 344.75 | order 22 |
| 23 | 23 | 2026-11-18 05:22:00 | MEA | 526.33 | order 23 |
| 24 | 24 | 2026-09-03 20:27:00 | APAC | 654.97 | order 24 |
| 25 | 25 | 2026-09-10 08:06:00 | APAC | 44.2 | order 25 |
| 26 | 26 | 2026-08-01 18:02:00 | MEA | 524.6 | order 26 |
| 27 | 27 | 2026-08-17 13:58:00 | US | 85.99 | order 27 |
| 28 | 28 | 2026-02-18 23:12:00 | APAC | 798.64 | NULL |
| 29 | 29 | 2026-10-18 07:21:00 | US | 529.19 | order 29 |
| 30 | 30 | 2026-07-16 07:24:00 | LATAM | 308.25 | order 30 |
| 31 | 31 | 2026-11-26 22:18:00 | MEA | 330.35 | order 31 |
| 32 | 32 | 2026-10-06 16:59:00 | LATAM | 709.31 | order 32 |
| 33 | 33 | 2026-06-16 09:50:00 | MEA | 107.05 | order 33 |
| 34 | 34 | 2026-02-18 12:28:00 | EU | 305.49 | order 34 |
| 35 | 35 | 2026-02-17 07:23:00 | LATAM | 526.44 | NULL |
| 36 | 36 | 2026-09-12 23:02:00 | LATAM | 337.21 | order 36 |
| 37 | 37 | 2026-09-06 08:54:00 | APAC | 917.01 | order 37 |
| 38 | 38 | 2026-12-09 08:13:00 | US | 284.02 | order 38 |
| 39 | 39 | 2026-08-23 02:23:00 | APAC | 970.46 | order 39 |
| 40 | 40 | 2026-01-26 06:50:00 | US | 303.29 | order 40 |
| 41 | 41 | 2026-01-09 01:35:00 | LATAM | 372.8 | order 41 |
| 42 | 42 | 2026-09-16 09:27:00 | APAC | 175.31 | NULL |
| 43 | 43 | 2026-04-15 07:55:00 | APAC | 234.81 | order 43 |
| 44 | 44 | 2026-04-27 04:08:00 | EU | 122.07 | order 44 |
| 45 | 45 | 2026-05-20 04:16:00 | LATAM | 458.64 | order 45 |
| 46 | 46 | 2026-04-26 14:06:00 | APAC | 483.62 | order 46 |
| 47 | 47 | 2026-10-09 00:18:00 | APAC | 439.14 | order 47 |
| 48 | 48 | 2026-12-07 21:20:00 | EU | 320.82 | order 48 |
| 49 | 49 | 2026-06-26 06:40:00 | EU | 238.76 | NULL |
| 50 | 50 | 2026-02-03 04:00:00 | US | 128.31 | order 50 |
| 51 | 51 | 2026-06-09 23:21:00 | EU | 110.91 | order 51 |
| 52 | 52 | 2026-08-22 03:23:00 | LATAM | 815.8 | order 52 |
| 53 | 53 | 2026-04-24 17:21:00 | MEA | 872.34 | order 53 |
| 54 | 54 | 2026-05-08 07:14:00 | EU | 137.67 | order 54 |
| 55 | 55 | 2026-02-22 00:40:00 | MEA | 524.28 | order 55 |
| 56 | 56 | 2026-11-10 04:17:00 | APAC | 776.46 | NULL |
| 57 | 57 | 2026-06-03 08:22:00 | EU | 103.79 | order 57 |
| 58 | 58 | 2026-12-10 09:26:00 | MEA | 979.93 | order 58 |
| 59 | 59 | 2026-10-06 19:16:00 | LATAM | 532.92 | order 59 |
| 60 | 60 | 2026-10-19 04:06:00 | EU | 669.93 | order 60 |
| 61 | 61 | 2026-01-04 13:50:00 | US | 951.65 | order 61 |
| 62 | 62 | 2026-12-04 13:09:00 | MEA | 144.89 | order 62 |
| 63 | 63 | 2026-04-16 12:57:00 | MEA | 390.37 | NULL |
| 64 | 64 | 2026-02-20 22:54:00 | EU | 4.54 | order 64 |
| 65 | 65 | 2026-02-27 15:04:00 | US | 170.61 | order 65 |
| 66 | 66 | 2026-02-19 06:13:00 | US | 39.05 | order 66 |
| 67 | 67 | 2026-11-28 20:55:00 | MEA | 404.27 | order 67 |
| 68 | 68 | 2026-02-06 23:36:00 | US | 977.78 | order 68 |
| 69 | 69 | 2026-02-27 12:27:00 | LATAM | 381.12 | order 69 |
| 70 | 70 | 2026-05-12 07:52:00 | LATAM | 960.97 | NULL |
| 71 | 71 | 2026-07-28 04:54:00 | APAC | 224.52 | order 71 |
| 72 | 72 | 2026-11-05 20:54:00 | LATAM | 31.71 | order 72 |
| 73 | 73 | 2026-06-06 06:20:00 | APAC | 539.13 | order 73 |
| 74 | 74 | 2026-11-18 01:41:00 | US | 366.22 | order 74 |
| 75 | 75 | 2026-12-13 23:51:00 | MEA | 686.86 | order 75 |
| 76 | 76 | 2026-09-02 10:57:00 | EU | 491.02 | order 76 |
| 77 | 77 | 2026-09-08 19:52:00 | APAC | 458.42 | NULL |
| 78 | 78 | 2026-01-26 10:25:00 | LATAM | 961.21 | order 78 |
| 79 | 79 | 2026-06-20 20:50:00 | APAC | 917.5 | order 79 |
| 80 | 80 | 2026-05-18 05:34:00 | MEA | 479.26 | order 80 |
| 81 | 81 | 2026-04-05 12:49:00 | US | 216.17 | order 81 |
| 82 | 82 | 2026-02-19 21:24:00 | US | 481.58 | order 82 |
| 83 | 83 | 2026-10-27 11:53:00 | EU | 140.92 | order 83 |
| 84 | 84 | 2026-03-12 21:12:00 | US | 66.71 | NULL |
| 85 | 85 | 2026-12-01 10:10:00 | LATAM | 400.53 | order 85 |
| 86 | 86 | 2026-03-26 23:54:00 | APAC | 696.72 | order 86 |
| 87 | 87 | 2026-12-26 19:11:00 | US | 173.96 | order 87 |
| 88 | 88 | 2026-05-02 15:00:00 | MEA | 315.46 | order 88 |
| 89 | 89 | 2026-08-16 02:33:00 | EU | 778.54 | order 89 |
| 90 | 90 | 2026-08-23 13:36:00 | US | 267.05 | order 90 |
| 91 | 91 | 2026-05-16 06:43:00 | EU | 388.23 | NULL |
| 92 | 92 | 2026-12-03 13:02:00 | US | 901.39 | order 92 |
| 93 | 93 | 2026-06-04 14:10:00 | LATAM | 591.3 | order 93 |
| 94 | 94 | 2026-12-03 04:07:00 | LATAM | 989.06 | order 94 |
| 95 | 95 | 2026-08-22 07:12:00 | EU | 893.4 | order 95 |
| 96 | 96 | 2026-02-06 15:59:00 | EU | 888.43 | order 96 |
| 97 | 97 | 2026-03-14 01:00:00 | LATAM | 86.62 | order 97 |
| 98 | 98 | 2026-12-18 13:25:00 | US | 120.41 | NULL |
| 99 | 99 | 2026-03-16 15:04:00 | EU | 389.16 | order 99 |
| 100 | 100 | 2026-06-22 17:29:00 | EU | 367.37 | order 100 |
The same data as Parquet
Parquet needs no import at all — meshfox reads it in place — so it's the
cheapest format for really big data. This block turns the CSV into one with
duckdb itself (the same tool the table view uses):
duckdb -c "COPY (SELECT * FROM 'tables-data/events.csv') TO 'tables-data/events.parquet' (FORMAT parquet)"
events.parquet
Same rows, a fraction of the disk space — compare the file size in the status bar tooltip with the CSV's.
1,000,000 rows × 5 cols · first 100 shown
| # | idbigint | tstimestamp | regionvarchar | amountdouble | notevarchar |
|---|---|---|---|---|---|
| 1 | 1 | 2026-01-01 17:02:00 | APAC | 927.11 | order 1 |
| 2 | 2 | 2026-08-21 11:24:00 | LATAM | 479.97 | order 2 |
| 3 | 3 | 2026-01-09 05:17:00 | EU | 119.8 | order 3 |
| 4 | 4 | 2026-04-09 10:23:00 | APAC | 158.64 | order 4 |
| 5 | 5 | 2026-11-21 03:04:00 | EU | 42.1 | order 5 |
| 6 | 6 | 2026-03-21 17:43:00 | APAC | 551.66 | order 6 |
| 7 | 7 | 2026-06-20 16:37:00 | US | 219.67 | NULL |
| 8 | 8 | 2026-08-24 12:54:00 | EU | 314.91 | order 8 |
| 9 | 9 | 2026-04-03 10:33:00 | MEA | 688.91 | order 9 |
| 10 | 10 | 2026-04-20 19:32:00 | MEA | 706.41 | order 10 |
| 11 | 11 | 2026-01-05 00:18:00 | LATAM | 852.9 | order 11 |
| 12 | 12 | 2026-06-01 10:40:00 | APAC | 118.86 | order 12 |
| 13 | 13 | 2026-02-21 12:07:00 | EU | 157.41 | order 13 |
| 14 | 14 | 2026-08-18 20:59:00 | EU | 992.06 | NULL |
| 15 | 15 | 2026-01-16 14:27:00 | US | 602.42 | order 15 |
| 16 | 16 | 2026-10-28 07:25:00 | APAC | 408.81 | order 16 |
| 17 | 17 | 2026-10-24 14:56:00 | LATAM | 542.12 | order 17 |
| 18 | 18 | 2026-04-20 00:21:00 | LATAM | 553.21 | order 18 |
| 19 | 19 | 2026-05-12 07:37:00 | EU | 687.69 | order 19 |
| 20 | 20 | 2026-08-19 08:05:00 | LATAM | 584.9 | order 20 |
| 21 | 21 | 2026-06-19 05:49:00 | LATAM | 374.52 | NULL |
| 22 | 22 | 2026-03-19 05:00:00 | US | 344.75 | order 22 |
| 23 | 23 | 2026-11-18 05:22:00 | MEA | 526.33 | order 23 |
| 24 | 24 | 2026-09-03 20:27:00 | APAC | 654.97 | order 24 |
| 25 | 25 | 2026-09-10 08:06:00 | APAC | 44.2 | order 25 |
| 26 | 26 | 2026-08-01 18:02:00 | MEA | 524.6 | order 26 |
| 27 | 27 | 2026-08-17 13:58:00 | US | 85.99 | order 27 |
| 28 | 28 | 2026-02-18 23:12:00 | APAC | 798.64 | NULL |
| 29 | 29 | 2026-10-18 07:21:00 | US | 529.19 | order 29 |
| 30 | 30 | 2026-07-16 07:24:00 | LATAM | 308.25 | order 30 |
| 31 | 31 | 2026-11-26 22:18:00 | MEA | 330.35 | order 31 |
| 32 | 32 | 2026-10-06 16:59:00 | LATAM | 709.31 | order 32 |
| 33 | 33 | 2026-06-16 09:50:00 | MEA | 107.05 | order 33 |
| 34 | 34 | 2026-02-18 12:28:00 | EU | 305.49 | order 34 |
| 35 | 35 | 2026-02-17 07:23:00 | LATAM | 526.44 | NULL |
| 36 | 36 | 2026-09-12 23:02:00 | LATAM | 337.21 | order 36 |
| 37 | 37 | 2026-09-06 08:54:00 | APAC | 917.01 | order 37 |
| 38 | 38 | 2026-12-09 08:13:00 | US | 284.02 | order 38 |
| 39 | 39 | 2026-08-23 02:23:00 | APAC | 970.46 | order 39 |
| 40 | 40 | 2026-01-26 06:50:00 | US | 303.29 | order 40 |
| 41 | 41 | 2026-01-09 01:35:00 | LATAM | 372.8 | order 41 |
| 42 | 42 | 2026-09-16 09:27:00 | APAC | 175.31 | NULL |
| 43 | 43 | 2026-04-15 07:55:00 | APAC | 234.81 | order 43 |
| 44 | 44 | 2026-04-27 04:08:00 | EU | 122.07 | order 44 |
| 45 | 45 | 2026-05-20 04:16:00 | LATAM | 458.64 | order 45 |
| 46 | 46 | 2026-04-26 14:06:00 | APAC | 483.62 | order 46 |
| 47 | 47 | 2026-10-09 00:18:00 | APAC | 439.14 | order 47 |
| 48 | 48 | 2026-12-07 21:20:00 | EU | 320.82 | order 48 |
| 49 | 49 | 2026-06-26 06:40:00 | EU | 238.76 | NULL |
| 50 | 50 | 2026-02-03 04:00:00 | US | 128.31 | order 50 |
| 51 | 51 | 2026-06-09 23:21:00 | EU | 110.91 | order 51 |
| 52 | 52 | 2026-08-22 03:23:00 | LATAM | 815.8 | order 52 |
| 53 | 53 | 2026-04-24 17:21:00 | MEA | 872.34 | order 53 |
| 54 | 54 | 2026-05-08 07:14:00 | EU | 137.67 | order 54 |
| 55 | 55 | 2026-02-22 00:40:00 | MEA | 524.28 | order 55 |
| 56 | 56 | 2026-11-10 04:17:00 | APAC | 776.46 | NULL |
| 57 | 57 | 2026-06-03 08:22:00 | EU | 103.79 | order 57 |
| 58 | 58 | 2026-12-10 09:26:00 | MEA | 979.93 | order 58 |
| 59 | 59 | 2026-10-06 19:16:00 | LATAM | 532.92 | order 59 |
| 60 | 60 | 2026-10-19 04:06:00 | EU | 669.93 | order 60 |
| 61 | 61 | 2026-01-04 13:50:00 | US | 951.65 | order 61 |
| 62 | 62 | 2026-12-04 13:09:00 | MEA | 144.89 | order 62 |
| 63 | 63 | 2026-04-16 12:57:00 | MEA | 390.37 | NULL |
| 64 | 64 | 2026-02-20 22:54:00 | EU | 4.54 | order 64 |
| 65 | 65 | 2026-02-27 15:04:00 | US | 170.61 | order 65 |
| 66 | 66 | 2026-02-19 06:13:00 | US | 39.05 | order 66 |
| 67 | 67 | 2026-11-28 20:55:00 | MEA | 404.27 | order 67 |
| 68 | 68 | 2026-02-06 23:36:00 | US | 977.78 | order 68 |
| 69 | 69 | 2026-02-27 12:27:00 | LATAM | 381.12 | order 69 |
| 70 | 70 | 2026-05-12 07:52:00 | LATAM | 960.97 | NULL |
| 71 | 71 | 2026-07-28 04:54:00 | APAC | 224.52 | order 71 |
| 72 | 72 | 2026-11-05 20:54:00 | LATAM | 31.71 | order 72 |
| 73 | 73 | 2026-06-06 06:20:00 | APAC | 539.13 | order 73 |
| 74 | 74 | 2026-11-18 01:41:00 | US | 366.22 | order 74 |
| 75 | 75 | 2026-12-13 23:51:00 | MEA | 686.86 | order 75 |
| 76 | 76 | 2026-09-02 10:57:00 | EU | 491.02 | order 76 |
| 77 | 77 | 2026-09-08 19:52:00 | APAC | 458.42 | NULL |
| 78 | 78 | 2026-01-26 10:25:00 | LATAM | 961.21 | order 78 |
| 79 | 79 | 2026-06-20 20:50:00 | APAC | 917.5 | order 79 |
| 80 | 80 | 2026-05-18 05:34:00 | MEA | 479.26 | order 80 |
| 81 | 81 | 2026-04-05 12:49:00 | US | 216.17 | order 81 |
| 82 | 82 | 2026-02-19 21:24:00 | US | 481.58 | order 82 |
| 83 | 83 | 2026-10-27 11:53:00 | EU | 140.92 | order 83 |
| 84 | 84 | 2026-03-12 21:12:00 | US | 66.71 | NULL |
| 85 | 85 | 2026-12-01 10:10:00 | LATAM | 400.53 | order 85 |
| 86 | 86 | 2026-03-26 23:54:00 | APAC | 696.72 | order 86 |
| 87 | 87 | 2026-12-26 19:11:00 | US | 173.96 | order 87 |
| 88 | 88 | 2026-05-02 15:00:00 | MEA | 315.46 | order 88 |
| 89 | 89 | 2026-08-16 02:33:00 | EU | 778.54 | order 89 |
| 90 | 90 | 2026-08-23 13:36:00 | US | 267.05 | order 90 |
| 91 | 91 | 2026-05-16 06:43:00 | EU | 388.23 | NULL |
| 92 | 92 | 2026-12-03 13:02:00 | US | 901.39 | order 92 |
| 93 | 93 | 2026-06-04 14:10:00 | LATAM | 591.3 | order 93 |
| 94 | 94 | 2026-12-03 04:07:00 | LATAM | 989.06 | order 94 |
| 95 | 95 | 2026-08-22 07:12:00 | EU | 893.4 | order 95 |
| 96 | 96 | 2026-02-06 15:59:00 | EU | 888.43 | order 96 |
| 97 | 97 | 2026-03-14 01:00:00 | LATAM | 86.62 | order 97 |
| 98 | 98 | 2026-12-18 13:25:00 | US | 120.41 | NULL |
| 99 | 99 | 2026-03-16 15:04:00 | EU | 389.16 | order 99 |
| 100 | 100 | 2026-06-22 17:29:00 | EU | 367.37 | order 100 |