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25
.drone.yml
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25
.drone.yml
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kind: pipeline
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type: docker
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name: default
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steps:
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- name: kaniko
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image: banzaicloud/drone-kaniko
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settings:
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registry: registry.kmlabz.com
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repo: birbnetes/${DRONE_REPO_NAME}
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username:
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from_secret: DOCKER_USERNAME
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password:
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from_secret: DOCKER_PASSWORD
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tags:
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- latest
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- ${DRONE_BUILD_NUMBER}
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- name: ms-teams
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image: kuperiu/drone-teams
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settings:
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webhook:
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from_secret: TEAMS_WEBHOOK
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when:
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status: [ failure ]
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2
.gitignore
vendored
2
.gitignore
vendored
@ -128,4 +128,4 @@ dmypy.json
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# Pyre type checker
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.pyre/
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.idea/
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19
Dockerfile
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19
Dockerfile
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FROM python:3
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WORKDIR /app
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VOLUME /data
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VOLUME /chart
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VOLUME /text
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ENV SEARCHDIR /data
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ENV CHARTDIR /chart
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ENV TEXTDIR /text
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COPY requirements.txt .
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RUN pip3 install --no-cache-dir -r requirements.txt && rm requirements.txt
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COPY make_graphs.py .
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CMD ["python3", "make_graphs.py"]
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ENTRYPOINT ["python3", "make_graphs.py"]
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230
make_graphs.py
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make_graphs.py
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#!/usr/bin/env python3
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"""
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Python module to automatically analyze benchmark results
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"""
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import csv
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import os
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import abc
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import multiprocessing
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import matplotlib.pyplot as pplot
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import sentry_sdk
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sentry_sdk.init("https://c1a84042595b448b94681750523dcc34@sentry.kmlabz.com/20")
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def average(lst: list) -> float:
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"""
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Agerage of list
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:param lst:
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:return:
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"""
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return sum(lst) / len(lst)
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def keychars(x):
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"""
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Return hey partnumber
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:param x:
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:return:
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"""
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return int(x.split('.')[1])
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class Analyzer(abc.ABC):
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"""
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Very abstract analyzer
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"""
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def __init__(self, typeof='.csv'):
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self.type = typeof
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def getfiles(self, directory: str = '.') -> list:
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"""
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Returns a list of csv files in directory
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:param directory:
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:return:
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"""
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return [(directory + '/' + filename) for filename in os.listdir(directory) if filename.endswith(self.type)]
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def processfile(
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self,
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fname: str,
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shouldprint: bool = False) -> None:
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pass
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def processallfiles(self, directory: str = '.') -> None:
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"""
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Process all files in a directory
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:param directory:
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:return:
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"""
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files = sorted(self.getfiles(directory), key=keychars)
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for f in files:
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self.processfile(f, False)
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class CsvAnalyzer(Analyzer):
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"""
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Abstract CSV analyzer
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"""
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def __init__(self):
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"""
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Init object
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"""
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super().__init__()
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self.responsespersec = []
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self.latencypersec = []
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def walkresponsepersec(
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self,
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responsepersec: dict,
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shouldprint: bool) -> None:
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"""
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Walks through reponsepersec dict
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:param responsepersec:
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:param shouldprint:
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:return:
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"""
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for sec in responsepersec:
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if len(responsepersec[sec]) != 0:
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self.responsespersec.append(len(responsepersec[sec]))
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self.latencypersec.append(average(responsepersec[sec]))
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if shouldprint:
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print(len(responsepersec[sec]))
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print(average(responsepersec[sec]))
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class HeyAnalyzer(CsvAnalyzer):
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"""
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Analyze hey benchmark output.
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"""
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def __init__(self):
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"""
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Init object
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"""
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super().__init__()
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def processfile(
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self,
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fname,
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shouldprint: bool = False):
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"""
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Process a single file.
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:param fname:
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:param shouldprint:
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:return:
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"""
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with open(fname, 'r') as f:
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data = csv.reader(f)
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fields = next(data)
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responsepersec = {}
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for row in data:
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items = zip(fields, row)
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item = {}
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for (name, value) in items:
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item[name] = value.strip()
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sec = int(item['offset'].split('.')[0])
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if sec not in responsepersec:
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responsepersec[sec] = []
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else:
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responsepersec[sec].append(float(item['response-time']))
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self.walkresponsepersec(responsepersec, shouldprint)
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class ChartCreator:
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"""
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Create charts automagically
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"""
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@staticmethod
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def savetxtplot(csvfile: CsvAnalyzer, directory) -> None:
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"""
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Save raw data to txt
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:param directory:
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:param csvfile:
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:return:
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"""
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with open(os.getenv('TEXTDIR', default='.') + '/' + directory + "-rps.txt", 'w') as f:
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for item in csvfile.responsespersec:
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f.write("%s\n" % item)
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with open(os.getenv('TEXTDIR', default='.') + '/' + directory + "-latency.txt", 'w') as f:
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for item in csvfile.latencypersec:
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f.write("%s\n" % item)
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@staticmethod
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def savecsvplot(csvfile: CsvAnalyzer, directory) -> None:
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"""
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Save plot of csv file
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:param csvfile:
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:param directory:
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:return:
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"""
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pplot.plot(csvfile.responsespersec)
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pplot.title(directory)
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pplot.xlabel("Time (seconds)")
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pplot.ylabel("Response/sec")
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pplot.savefig(
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os.getenv(
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'CHARTDIR',
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default='.') +
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'/' +
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directory +
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"-rps.png")
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pplot.clf()
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pplot.plot(csvfile.latencypersec)
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pplot.title(directory)
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pplot.xlabel("Time (seconds)")
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pplot.ylabel("Response time (milliseconds)")
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pplot.savefig(
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os.getenv(
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'CHARTDIR',
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default='.') +
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'/' +
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directory +
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"-latency.png")
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pplot.clf()
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print("latency min, max, avg")
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print(min(csvfile.latencypersec))
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print(max(csvfile.latencypersec))
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print(average(csvfile.latencypersec))
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print("Charted " + directory)
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@staticmethod
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def analyze_hey(abs_directory, directory):
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"""
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Analyze hey output
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:param abs_directory:
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:param directory:
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:return:
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"""
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hey = HeyAnalyzer()
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hey.processallfiles(abs_directory)
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ChartCreator.savecsvplot(hey, directory)
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ChartCreator.savetxtplot(hey, directory)
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def doallruns(self):
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"""
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Process all directories in repo
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:return:
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"""
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dirs = next(os.walk(os.getenv('SEARCHDIR', default='.')))[1]
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jobs = []
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for directory in dirs:
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abs_directory = os.getenv(
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'SEARCHDIR', default='.') + '/' + directory
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print(abs_directory)
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process = multiprocessing.Process(
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target=ChartCreator.analyze_hey, args=(
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abs_directory, directory,))
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if __name__ == "__main__":
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"""
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Entry point
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"""
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chartcreator = ChartCreator()
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chartcreator.doallruns()
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2
requirements.txt
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2
requirements.txt
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matplotlib
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sentry_sdk
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