Bash script with jq wont get date difference from strings, and runs quite slowly on i7 16GB RAM - json

Need to find the difference between TradeCloseTime and TradeOpenTime time in dd:hh:mm format for the Exposure column in the following script.
Also the script runs super slow (~4 mins for 800 rows of json, on Core i7 16gb RAM machine)
#!/bin/bash
echo "TradeNo, TradeOpenType, TradeCloseType, TradeOpenSource, TradeCloseSource, TradeOpenTime, TradeCloseTime, PNL, Exposure" > tradelist.csv
tradecount=$(jq -r '.performance.numberOfTrades|tonumber' D.json)
for ((i=0; i<$tradecount; i++))
do
tradeNo=$(jq -r '.trades['$i']|[.tradeNo][]|tonumber' D.json)
entrySide=$(jq -r '.trades['$i'].orders[0]|[.side][]' D.json)
exitSide=$(jq -r '.trades['$i'].orders[1]|[.side][]' D.json)
entrySource=$(jq -r '.trades['$i'].orders[0]|[.source][]' D.json)
exitSource=$(jq -r '.trades['$i'].orders[1]|[.source][]' D.json)
tradeEntryTime=$(jq -r '.trades['$i'].orders[0]|[.placedTime][]' D.json | tr -d 'Z' | tr -s 'T' ' ')
tradeExitTime=$(jq -r '.trades['$i'].orders[1]|[.placedTime][]' D.json | tr -d 'Z' | tr -s 'T' ' ')
profitPercentage=$(jq -r '(.trades['$i']|[.profitPercentage][0]|tonumber)*(100)' D.json)
echo $tradeNo","$entrySide","$exitSide","$entrySource","$exitSource","$tradeEntryTime","$tradeExitTime","$profitPercentage | tr -d '"' >> tradelist.csv
done
json file looks like this
{"market":{"exchange":"BINANCE_FUTURES","coinPair":"BTC_USDT"},"strategy":{"name":"","type":"BACKTEST","candleSize":15,"lookbackDays":6,"leverageLong":1.00000000,"leverageShort":1.00000000,"strategyName":"ABC","strategyVersion":35,"runNo":"002","source":"Personal"},"strategyParameters":[{"name":"DurationInput","value":"87.0"}],"openPositionStrategy":{"actionTime":"CANDLE_CLOSE","maxPerSignal":1.00000000},"closePositionStrategy":{"actionTime":"CANDLE_CLOSE","minProfit":"NaN","stopLossValue":0.07000000,"stopLossTrailing":true,"takeProfit":0.01290000,"takeProfitDeviation":"NaN"},"performance":{"startTime":"2019-01-01T00:00:00Z","endTime":"2021-11-24T00:00:00Z","startAllocation":1000.00000000,"endAllocation":3478.58904150,"absoluteProfit":2478.58904150,"profitPerc":2.47858904,"buyHoldRatio":0.62426630,"buyHoldReturn":4.57228387,"numberOfTrades":744,"profitableTrades":0.67833109,"maxDrawdown":-0.20924885,"avgMonthlyProfit":0.05242718,"profitableMonths":0.70370370,"avgWinMonth":0.09889897,"avgLoseMonth":-0.05275563,"startPrice":null,"endPrice":57623.08000000},"trades":[{"tradeNo":0,"profit":-5.48836165,"profitPercentage":-0.00549085,"accumulatedBalance":994.51163835,"compoundProfitPerc":-0.00548836,"orders":[{"side":"Long","placedTime":"2019-09-16T21:15:00Z","placedAmount":0.09700000,"filledTime":"2019-09-16T21:15:00Z","filledAmount":0.09700000,"filledPrice":10300.49000000,"commissionPaid":0.39965901,"source":"SIGNAL"},{"side":"CloseLong","placedTime":"2019-09-17T19:15:00Z","placedAmount":0.09700000,"filledTime":"2019-09-17T19:15:00Z","filledAmount":0.09700000,"filledPrice":10252.13000000,"commissionPaid":0.39778264,"source":"SIGNAL"}]},{"tradeNo":1,"profit":-3.52735800,"profitPercentage":-0.00356403,"accumulatedBalance":990.98428035,"compoundProfitPerc":-0.00901572,"orders":[{"side":"Long","placedTime":"2019-09-19T06:00:00Z","placedAmount":0.10000000,"filledTime":"2019-09-19T06:00:00Z","filledAmount":0.10000000,"filledPrice":9893.16000000,"commissionPaid":0.39572640,"source":"SIGNAL"},{"side":"CloseLong","placedTime":"2019-09-19T06:15:00Z","placedAmount":0.10000000,"filledTime":"2019-09-19T06:15:00Z","filledAmount":0.10000000,"filledPrice":9865.79000000,"commissionPaid":0.39463160,"source":"SIGNAL"}]},{"tradeNo":2,"profit":-5.04965308,"profitPercentage":-0.00511770,"accumulatedBalance":985.93462727,"compoundProfitPerc":-0.01406537,"orders":[{"side":"Long","placedTime":"2019-09-25T10:15:00Z","placedAmount":0.11700000,"filledTime":"2019-09-25T10:15:00Z","filledAmount":0.11700000,"filledPrice":8430.00000000,"commissionPaid":0.39452400,"source":"SIGNAL"},{"side":"CloseLong","placedTime":"2019-09-25T10:30:00Z","placedAmount":0.11700000,"filledTime":"2019-09-25T10:30:00Z","filledAmount":0.11700000,"filledPrice":8393.57000000,"commissionPaid":0.39281908,"source":"SIGNAL"}]}

You can do it all (extracts, conversions and formatting) with one jq call:
#!/bin/sh
echo 'TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure'
query='
.trades[]
| [
.tradeNo,
.orders[0].side,
.orders[1].side,
.orders[0].source,
.orders[1].source,
(.orders[0].placedTime | fromdate | strftime("%Y-%m-%d %H:%M:%S")),
(.orders[1].placedTime | fromdate | strftime("%Y-%m-%d %H:%M:%S")),
.profitPercentage * 100,
(
(.orders[1].placedTime | fromdate) - (.orders[0].placedTime | fromdate)
| (. / 86400 | floor | tostring) + (. % 86400 | strftime(":%H:%M"))
)
]
|#csv
'
jq -r "$query" < D.json > tradelist.csv
example of JSON (cleaned of all irrelevant keys):
{
"trades": [
{
"tradeNo": 0,
"profitPercentage": -0.00549085,
"orders": [
{
"side": "Long",
"placedTime": "2018-12-16T21:34:46Z",
"source": "SIGNAL"
},
{
"side": "CloseLong",
"placedTime": "2019-09-17T19:15:00Z",
"source": "SIGNAL"
}
]
}
]
}
output:
TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure
0,"Long","CloseLong","SIGNAL","SIGNAL","2018-12-16 21:34:46","2019-09-17 20:15:00",-0.549085,"274:22:40"
If you want to get rid of the double quotes that jq adds when generating a CSV (which are completely valid, but you need a real parser to read the CSV) then you can replace #csv with #tsv and post-process the output with tr '\t' ',', like this:
query='
...
|#tsv
'
jq -r "$query" < D.json | tr '\t' ',' > tradelist.csv
and you'll get:
TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure
0,Long,CloseLong,SIGNAL,SIGNAL,2018-12-16 21:34:46,2019-09-17 20:15:00,-0.549085,274:22:40
note: This method of getting rid of the " in the CSV is only accurate when there is no \n \t \r \ , or " characters in the input data.

Regarding the main question (regarding computing time differences), you're in luck as jq provides the built-in function fromdateiso8601 for converting ISO times to "the
number of seconds since the Unix epoch (1970-01-01T00:00:00Z)".
With your JSON sample,
.trades[]
| [ .orders[1].placedTime, .orders[0].placedTime]
| map(fromdateiso8601)
| .[0] - .[1]
produces the three differences:
79200
900
900
And here's a function for converting seconds to "hh:mm:ss" format:
def hhmmss:
def l: tostring | if length < 2 then "0\(.)" else . end;
(. % 60) as $ss
| ((. / 60) | floor) as $mm
| (($mm / 60) | floor) as $hh
| ($mm % 60) as $mm
| [$hh, $mm, $ss] | map(l) | join(":");

I prefer using an intermediate structure of the "entry" and "exit" JSON. This helps with debugging the jq commands. Formatted for readability over performance:
#!/usr/bin/env bash
echo "TradeNo,TradeOpenType,TradeCloseType,TradeOpenSource,TradeCloseSource,TradeOpenTime,TradeCloseTime,PNL,Exposure" > tradelist.csv
jq -r '
.trades[]
|{tradeNo,
profitPercentage,
entry:.orders[0],
exit:.orders[1],
entryTS:.orders[0].placedTime|fromdate,
exitTS:.orders[1].placedTime|fromdate}
|[.tradeNo,
.entry.side,
.exit.side,
.entry.source,
.exit.source,
(.entry.placedTime|strptime("%Y-%m-%dT%H:%M:%SZ")|strftime("%Y-%m-%d %H:%M:%S")),
(.exit.placedTime|strptime("%Y-%m-%dT%H:%M:%SZ")|strftime("%Y-%m-%d %H:%M:%S")),
(.profitPercentage*100),
(.exitTS-.entryTS|todate|strptime("%Y-%m-%dT%H:%M:%SZ")|strftime("%d:%H:%M"))]|#csv
' D.json | tr -d '"' >> tradelist.csv
WARNING: This formatting assumes Exposure is LESS THAN 1 MONTH. Good luck with that!

Related

JSON JQ filter by date older than bash

I have a json with this format of data in a text.json file
[
{
"name": "page/page1.html",
"properties": {
"lastModified": "2021-08-10T18:00:45+00:00",
}
},
{
"name": "page/page2.html",
"properties": {
"lastModified": "2021-08-10T19:24:23+00:00",
}
},
{
"name": "page/page3.html",
"properties": {
"lastModified": "2021-08-10T20:36:21+00:00",
}
}
]
I want to make a list of all the names of files which are last modified more that 30 minutes ago. This is my query at the moment to get a list of file names as a variable which i can use later.
file_names=`cat text.json | jq -r .[].name`
How can I use jq to filter for lastModified more than 30 minutes ago based on the timestamp in the properties so I only get the relevant file names?
I'd typically calculate the target date in native bash.
#!/usr/bin/env bash
# make sure we have bash new enough for printf %(...)T time-formatting
# this makes our script work even without GNU date
case $BASH_VERSION in
''|[123].*|4.[012].*) echo "ERROR: bash 4.3+ required" >&2; exit 1;;
esac
export TZ=UTC # force all timestamps to be in UTC (+00:00 / Z)
# faster, bash-builtin now=$(date +%s)
printf -v now '%(%s)T' -1
# faster, bash-builtin start_date_iso8601=$(date +%s -d '30 minutes ago')
start_date_epoch=$((now - 60*30))
printf -v start_date_iso8601 '%(%Y-%m-%dT%H:%M:%S+00:00)T' "$start_date_epoch"
# read our resulting names into an array (not a string)
# jq -j suppresses newlines so we can use NUL delimiters
while IFS= read -r -d '' name; do
names+=( "$name" )
done < <(
jq -j --arg start_date "$start_date_iso8601" '
.[] |
select(.properties.lastModified < $start_date) |
(.name, "\u0000")
' <text.json
)
# print the content of the array we just read the names into
printf 'Matching name: %q\n' "${names[#]}"
This seems to work
date=`date +%Y-%m-%d'T'%H:%M'Z' -d "15 min ago"`
file_names=`jq -r --arg date "$date" '.[] | select(.properties.lastModified < $date) | .name' < text.json`
Let jq do all date computations:
With bash 4 and above with mapfile:
mapfile -d '' last_modified < <(
jq --join-output '(now - 1800) as $date | .[] | select((.properties.lastModified | .[:18] + "Z" | fromdate) < $date) | .name + "\u0000"' input_file.json
)
# For debug purpose
declare -p last_modified
Without mapfile, records are delimited with ASCII RS control character rather than a null byte:
IFS=$'\36' read -ra last_modified < <(jq -j '(now - 1800) as $date | .[] | select((.properties.lastModified | .[:18] + "Z" | fromdate) < $date) | .name + "\u001e"' input_file.json)
Here is the stand-alone jq script with comments:
#!/usr/bin/env -S jq -jf
# Store current timestamp minus 30 minutes (1800 seconds) as $date
(now - 1800) as $date |
.[] |
#
select(
(
# Strip the numerical timezone offset out from the timestamp
# and replace it with the Z for UTC iso8601
# to make it an iso8601 date string that jq understands
.properties.lastModified | .[:18] + "Z" | fromdate
) < $date
) |
.name + "\u0000"

How to convert json values to prometheus?

After runing this command:
mtr -jnbz www.google.com |jq .report.hubs|jq -r 'keys_unsorted[] as $k | "\(.[$k])"'
I get this result:
{"count":"1","host":"1.1.1.1","ASN":"AS???","Loss%":0,"Snt":10,"Last":36.28,"Avg":39.43,"Best":34.77,"Wrst":62.37,"StDev":8.15}
{"count":"2","host":"2.2.2.2","ASN":"AS???","Loss%":100,"Snt":10,"Last":0,"Avg":0,"Best":0,"Wrst":0,"StDev":0}
How can I get this result(prometheus format):
mtr_loss{"count"="1","host"="1.1.1.1","ASN"="AS???"} 0
mtr_snt{"count"="1","host"="1.1.1.1","ASN"="AS???"} 10
mtr_last{"count"="1","host"="1.1.1.1","ASN"="AS???"} 36.28
mtr_avg{"count"="1","host"="1.1.1.1","ASN"="AS???"} 39.43
mtr_best{"count"="1","host"="1.1.1.1","ASN"="AS???"} 34.77
mtr_wrst{"count"="1","host"="1.1.1.1","ASN"="AS???"} 67.37
mtr_stdev{"count"="1","host"="1.1.1.1","ASN"="AS???"} 8.15
And so on for the second string
I will be grateful to you for any tips and tricks
Regards
The following is perhaps easier to follow, maintain, and reuse:
# produce the {"k"="value", ...} representation:
def kv:
. as $in
| reduce keys_unsorted[] as $k ([]; . + ["\"\($k)\"=\"\($in[$k])\""] )
| join(",")
| "{" + . + "}" ;
# downcase and remove %
def ht($s):
keys_unsorted[] as $key
| .[$key] as $value
| "mtr_\($key|ascii_downcase|gsub("%";""))\($s) \($value)";
({count,host,ASN} | kv) as $s
| {"Loss%", Snt, Last, Avg, Best, Wrst, StDev}
| ht($s)
It was quite easy :) :
mtr -jnbz www.google.com |
tr -d "%" |
jq -r '.report.hubs[]
| "mtr_loss{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.Loss)\nmtr_sent{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.Snt)\nmtr_last{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.Last)\nmtr_avg{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.Avg)\nmtr_best{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.Best)\nmtr_wrst{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.Wrst)\nmtr_stdev{count=\"\(.count)\",host=\"\(.host)\",asn=\"\(.ASN)\"} \(.StDev)" '

jq create output in many separate files

given the following json:
[
{"_id":{"$oid":"6d2"},"jlo":"ΕΙ AJSB","dd":"d5f"},
{"_id":{"$oid":"c6d3"},"jlo":"ΕΙ ALKSB","dd":"5d9"},
{"_id":{"$oid":"b0cc6d4"},"jlo":"ΕΙ AGHTSB","dd":"1b1"},
{"_id":{"$oid":"6d2"},"jlo":"ΕPOWΙ AJSB","dd":"d5f"},
{"_id":{"$oid":"c6d3"},"jlo":"ΕGTΙ ALKSB","dd":"5d9"},
{"_id":{"$oid":"b0cc6d4"},"jlo":"ΕLKΙ AGHTSB","dd":"1b1"}
]
what i need to do is have as output for each discrete value of the ll element, the unique values of ta, in a separate file, named after a one to one representation where each dd code is substituted with a human readable representation:
d5f:departmentone
5d9:departmentalt
1b1:departshort
Desired output, in a per row basis, each unique value of jlo with the count of times it was found in each dd element so we get in the end something like this:
first file named departmentone.txt:
ΕΙ AJSB 1
ΕPOWΙ AJSB 1
second file named departmentalt.txt
ΕΙ ALKSB 1
ΕGTΙ ALKSB 1
third file named departshort.txt
ΕΙ AGHTSB 2
i have tried with map and reduce, group_by, sort_by, with really poor results
Only one invocation of jq is necessary. To allocate the output to the separate files, you can combine this one invocation with a single invocation to awk, or you could use a shell loop as illustrated below.
First, here's an illustration of how the shell pipeline would look:
jq -r --rawfile dd2name dd2name.tsv -f group.jq input.json |
while IFS=$'\t' read -r f v ; do echo "$v" >> "$f" ; done
This assumes that the mapping to filenames is in a TSV file named dd2name.tsv, and that the following jq program is in group.jq:
def dict:
split("\n") | map(select(length>0) | split("\t"))
| INDEX(.[0]) | map_values(.[1]);
($dd2name | dict) as $dict
| ($dict | keys_unsorted[]) as $dd
| map(select(.dd == $dd))
| group_by(.jlo)
| map("\($dict[$dd])\t\(.[0].jlo) \(length)")[]
As the name suggests, the dict function creates a dictionary giving the mapping of .dd values to the filenames. It assumes the availability of INDEX. If your jq does not have INDEX, then now would be an excellent time to upgrade your jq; otherwise, its def can easily be copied from builtin.jq (google: builtin.jq "def INDEX"), or you could replace the last line by: | reduce .[] as $p ({}; .[$p[0]] = $p[1]);
awk-based solution
The following invocation of awk can be used instead of the while ... done command above:
awk -F\\t 'fn && (fn!=$1) {close(fn)}; {fn=$1; print $2 >> fn}'
Season to taste
If the dd2name.tsv mapping file does not contain the ".txt" suffix, it can easily be added in any of a variety of ways, according to taste.
Note also that the proposed solutions above make some assumptions, notably that the .jlo values do not contain tabs, newlines, or NULs. If any of those assumptions is violated, then some tweaking will be required.
I'd do it in three passes, filtering the array with the desired dd and grouping by jlo, then extracting the jlo of the first (guaranteed) item of the array and its length :
map(select(.dd == "d5f")) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]
You can try it here.
Full bash run :
jq --arg dd d5f --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > departmentone.txt
jq --arg dd 5d9 --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > departmentalt.txt
jq --arg dd 1b1 --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > departmentshort.txt
Supposing you have a file named "mapping.txt" with the following content :
d5f:departmentone
5d9:departmentalt
1b1:departshort
You could extract those codes and labels to generate the files :
while IFS=: read -r code label; do
jq --arg dd $code --raw-output 'map(select(.dd == $dd)) | group_by(.jlo) | map("\(.[0].jlo) \(length)") | .[]' yourJsonFile > "$label".txt
done < mapping.txt

Calculate accumulated times from json with bash script

I have data in json format that logs timestamps (hh:mm in 24h format) with an event (In/Out). My goal is to add up all the time differences between an "IN" event and the next "OUT" event.
For simplification I assume that there are no inconsistencies (The first element is always an "IN" and each "IN" is followed by an "OUT"). Exception: If the last element is an "IN", the calculation has to be done between the current time and the timestamp from the last "IN" event.
This is my script so far, which calculates all the timespans, also between an OUT and an IN event. But I need only those that are inbetween an IN and OUT event.
Any tips what might be more useful here are welcome !
#!/bin/bash
JSON='{ "times": [ [ "7:43", "IN" ], [ "8:26", "OUT" ], [ "8:27", "IN" ], [ "9:12", "OUT" ], [ "9:14", "IN" ], [ "9:22", "OUT" ], [ "9:23", "IN " ], [ "12:12", "OUT" ], [ "13:12", "IN" ] ]}'
IN_TIMES=$(jq '.times | to_entries | .[] | select(.value[1]| tostring | contains("IN")) | .value[0]' <<< "$JSON")
OUT_TIMES=$(jq '.times | to_entries | .[] | select(.value[1]| tostring | contains("OUT")) | .value[0]' <<< "$JSON")
ALL_TIMES=$(jq -r '.times| to_entries | .[] | .value[0]' <<< "$JSON")
prevtime=0
count=0
for i in $(echo $ALL_TIMES | sed "s/ / /g")
do
if [[ "$count" -eq 0 ]]; then
(( count++ ))
prevtime=$i
continue
else
(( count++ ))
fi
time1=`date +%s -d ${prevtime}`
time2=`date +%s -d ${i}`
diffsec=`expr ${time2} - ${time1}`
echo From $prevtime to $i: `date +%H:%M -ud #${diffsec}`
prevtime=$i
done
Here's an only-jq solution that only calls jq once.
Please note, though, that it may need tweaking to take into account time zone considerations, error-handling, and potentially other complications:
def mins: split(":") | map(tonumber) | .[0] * 60 + .[1];
def diff: (.[1] - .[0]) | if . >= 0 then . else 24*60 + . end;
def now_mins: now | gmtime | .[3] * 60 + .[4];
def pairs:
range(0; length; 2) as $i | [.[$i], .[$i+1] ];
def sigma(s): reduce s as $s (0; . + $s);
.times
| map( .[0] |= mins )
| if .[-1][1] == "IN" then . + [ [now_mins, "OUT"] ] else . end
| sigma(pairs | map(.[0]) | diff)
Since you measure times up to the minute, it is enough to compute minutes without messing up with the command date. I have an awk solution:
awk -F: -vIRS=" " -vfmt="From %5s to %5s: %4u minutes\n" \
'{this=$1*60+$2}a{printf(fmt,at,$0,this-a);a=0;next}{a=this;at=$0}\
END{if(a){$0=strftime("%H:%M");printf(fmt,at,$0,$1*60+$2-a)}}' <<<"$ALL_TIMES"
which works by defining a colon as field separator and a space as record separator. In this way we get a separate record with two fields for each time. Then
{this=$1*60+$2} : We compute how many minutes there are in the current record and put them in the variable this.
a{printf(fmt,at,$0,this-a);a=0;next} : If the (initially empty) variable a is not null nor zero, we are reading an OUT entry, so we print what we want, set a to zero because the next field will be an IN entry, and we continue to the next record.
{a=this;at=$0} : Otherwise, we are reading an IN entry, and set a to its minutes and at to its string representation (needed we will print it, as per previous case).
END{if(a){$0=strftime("%H:%M");printf(fmt,at,$0,$1*60+$2-a)}} : at the end, if we still have some dangling IN data, we set $0 to be the properly formatted current time and print what we want.
All done.
With Xidel and a little XQuery magic this is rather simple:
#!/bin/bash
JSON='{"times": [["7:43", "IN"], ["8:26", "OUT"], ["8:27", "IN"], ["9:12", "OUT"], ["9:14", "IN"], ["9:22", "OUT"], ["9:23", "IN "], ["12:12", "OUT"], ["13:12", "IN"]]}'
xidel -s - --xquery '
let $in:=$json/(times)()[contains(.,"IN")](1) ! time(
substring(
"00:00:00",
1,
8-string-length(.)
)||.
),
$out:=$json/(times)()[contains(.,"OUT")](1) ! time(
substring(
"00:00:00",
1,
8-string-length(.)
)||.
)
for $x at $i in $out return
concat(
"From ",
$in[$i],
" to ",
$x,
": ",
$x - $in[$i] + time("00:00:00")
)
' <<< "$JSON"
$in:
00:07:43
00:08:27
00:09:14
00:09:23
00:13:12
$out:
00:08:26
00:09:12
00:09:22
00:12:12
Output:
From 00:07:43 to 00:08:26: 00:00:43
From 00:08:27 to 00:09:12: 00:00:45
From 00:09:14 to 00:09:22: 00:00:08
From 00:09:23 to 00:12:12: 00:02:49

Get count based on value bash

I have data in this format in a file:
{"field1":249449,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249448,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249447,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249443,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
{"field1":249449,"field2":116895,"field3":1,"field4":"apple","field5":42,"field6":"2019-07-01T00:00:10","metadata":"","frontend":""}
Here, each entry represents a row. I want to have a count of the rows with respect to the value in field one, like:
249449 : 2
249448 : 1
249447 : 1
249443 : 1
How can I get that?
with awk
$ awk -F'[,:]' -v OFS=' : ' '{a[$2]++} END{for(k in a) print k, a[k]}' file
You can use the jq command line tool to interpret JSON data. uniq -c counts the number of occurences.
% jq .field1 < $INPUTFILE | sort | uniq -c
1 249443
1 249447
1 249448
2 249449
(tested with jq 1.5-1-a5b5cbe on linux xubuntu 18.04 with zsh)
Here's an efficient jq-only solution:
reduce inputs.field1 as $x ({}; .[$x|tostring] += 1)
| to_entries[]
| "\(.key) : \(.value)"
Invocation: jq -nrf program.jq input.json
(Note in particular the -n option.)
Of course if an object-representation of the counts is satisfactory, then
one could simply write:
jq -n 'reduce inputs.field1 as $x ({}; .[$x|tostring] += 1)' input.json
Using datamash and some shell utils, change the non-data delimiters to squeezed tabs, count field 3, (it'd be field 2, but there's a leading tab), reverse, then pretty print as per OP spec:
tr -s '{":,}' '\t' < file | datamash -sg 3 count 3 | tac | xargs printf '%s : %s\n'
Output:
249449 : 2
249448 : 1
249447 : 1
249443 : 1