# install via go tools
go get github.com/muhqu/go-sparkline
go install github.com/muhqu/go-sparkline
# verify
go-sparkline --help
$ go-sparkline --help
usage: go-sparkline [<flags>] [<values>]
Flags:
--help Show help.
-s, --stream stream
--animate start animation
--lazy ignore parse errors
--char-size=7:17 Pixel size of a single character. Can also be set via env
ITERM_CHARACTER_SIZE. The default 7:17 corresponds to 12p Monaco.
--rows=3 height in number of rows
--renderer=sparks available renderers: line, sparks, vlines
Args:
[<values>] Numeric values to render. Can also be read from stdin.
go-sparkline 16 19 18 12 7 4 7 15 25 33 35 32 26 21
# or
echo 16 19 18 12 7 4 7 15 25 33 35 32 26 21 | go-sparkline
echo '[16,19,18,12,7,4,7,15,25,33,35,32,26,21]' | go-sparkline
(
echo '[16,19,18]'; sleep 1;
echo '[12,7,4]'; sleep 1;
echo '[7,15,25]'; sleep 1;
echo '[33,35,32]'; sleep 1;
echo '[26,21]';
) | go-sparkline --stream
ping -n -i 0.3 localhost \
| awk 'BEGIN{FS="time=|ms"}/time=/{printf "%d\n",$2*1000;fflush()}' \
| go-sparkline --stream
$ aws cloudwatch get-metric-statistics \
--namespace AWS/ELB \
--metric-name RequestCount \
--end-time "2015-04-15T21:15:00Z" \
--start-time "2015-04-15T17:45:00Z" \
--period 900 \
--statistics Sum \
| tee cloudwatch.json \
| go-sparkline
$ head cloudwatch.json; echo '...'; tail cloudwatch.json;
{
"Datapoints": [
{
"Timestamp": "2015-04-15T17:45:00Z",
"Sum": 37823.0,
"Unit": "Count"
},
{
"Timestamp": "2015-04-15T11:30:00Z",
"Sum": 12413.0,
...
"Unit": "Count"
},
{
"Timestamp": "2015-04-15T21:15:00Z",
"Sum": 29428.0,
"Unit": "Count"
}
],
"Label": "RequestCount"
}
A: iTerm2 supports a bunch of propritary ESC seq. The nightly build even includes one to render images directly into the terminal.
ESC ] 1337 ; File = [optional arguments] : base-64 encoded file contents ^G
© 2015 by Mathias Leppich github.com/muhqu, @muhqu |
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