When I use --export cvs=results.csv the timestamp has very low resolution (1s), so I cant plot timeseries.
I need to convert it into arrays, but some requests have way fewer entries in scenarios, so it is hard to compare.
metric_name,timestamp,metric_value,check,error,error_code,expected_response,group,method,name,proto,scenario,service,status,subproto,tls_version,url,extra_tags,metadata
http_reqs,1672766933,1.000000,,,,true,,POST,https://XXXXXXXXX/auth/realms/buypass/protocol/openid-connect/token,HTTP/1.1,default,,200,,tls1.2,https://XXXXXXXXX/auth/realms/buypass/protocol/openid-connect/token,,
:
:
:
The first 1000+ entries have the same timestamp
>>> datetime.datetime.fromtimestamp(1672766933).strftime('%Y%m%d %H:%M%S.%f')
'20230103 18:2853.000000'
I use matplotlib and it has no problems whatosever with micro timestamps:
>>> datetime.datetime.fromtimestamp(1672766933.123456).strftime('%Y%m%d %H:%M%S.%f')
'20230103 18:2853.123456'