Jira python 计算时间

Question

我正在尝试计算从问题产生到解决的时间。使用这些字段：

creation_time = issue.fields.created
resolved_time = issue.fields.resolutiondate

打印输出：

Creation: 2016-06-09T14:37:05.000+0200 Resolved: 2016-06-10T10:53:12.000+0200

我是否可以用创建日期和时间减去解决日期和时间来找出在一个问题上花费了多少时间？

Answer 1

将 date/time 字符串解析为合适的日期时间对象，然后您可以使用它们进行计算。

This post explains how to parse a date/time string or you can just take a look at the documentation for the strptime() method.

计算，this post and there's detailed documentation here里有例子。

举个例子，这样的事情应该接近解决方案：

from datetime import datetime
from datetime import timedelta

createdTime = datetime.strptime('2016-06-09T14:37:05.000+0200', '%Y-%m-%dT%H:%M:%S.%f')
resolvedTime = datetime.strptime('2016-06-10T10:53:12.000+0200', '%Y-%m-%dT%H:%M:%S.%f')

duration = resolvedTime - createdTime

duration 将是一个 timedelta 对象，您可以访问 duration.days , duration.seconds 和 duration.microseconds 来获取它的信息。

strptime 确实有一个缺点，即它不支持解析时区，因此您必须先删除那部分输入。或者，参见 this post.

Answer 2

我编写了一个函数来计算以天为单位的响应时间的均值、中值和方差。希望有所帮助；

import datetime as d
import numpy as np

ymd_create = []
ymd_resdate = []
delta_t = []

class calculate:
    def __init__(self):
        self.result = 0

    def meantime(self, issueobject):
        for i in range(0, len(issueobject)):
            ymd_create.append(d.datetime(int(issueobject[i].raw[u'fields'][u'created'].split('T')[0].split('-')[0]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[0].split('-')[1]), int(issueobject[i].raw[u'fields']
                                                                                                                                                                                                     [u'created'].split('T')[0].split('-')[2]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[1].split(':')[0]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[1].split(':')[1])))
            ymd_resdate.append(d.datetime(int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[0].split('-')[0]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[0].split('-')[1]), int(issueobject[i].raw[u'fields']
                                                                                                                                                                                                                    [u'resolutiondate'].split('T')[0].split('-')[2]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[1].split(':')[0]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[1].split(':')[1])))
            delta_t.append((ymd_resdate[i] - ymd_create[i]).days)

        self.result = np.mean(np.array(delta_t))
        return self.result

    def mediantime(self, issueobject):
        for i in range(0, len(issueobject)):
            ymd_create.append(d.datetime(int(issueobject[i].raw[u'fields'][u'created'].split('T')[0].split('-')[0]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[0].split('-')[1]), int(issueobject[i].raw[u'fields']
                                                                                                                                                                                                     [u'created'].split('T')[0].split('-')[2]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[1].split(':')[0]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[1].split(':')[1])))
            ymd_resdate.append(d.datetime(int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[0].split('-')[0]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[0].split('-')[1]), int(issueobject[i].raw[u'fields']
                                                                                                                                                                                                                    [u'resolutiondate'].split('T')[0].split('-')[2]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[1].split(':')[0]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[1].split(':')[1])))
            delta_t.append((ymd_resdate[i] - ymd_create[i]).days)

        self.result = np.median(np.array(delta_t))
        return self.result

    def variancetime(self, issueobject):
        for i in range(0, len(issueobject)):
            ymd_create.append(d.datetime(int(issueobject[i].raw[u'fields'][u'created'].split('T')[0].split('-')[0]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[0].split('-')[1]), int(issueobject[i].raw[u'fields']
                                                                                                                                                                                                     [u'created'].split('T')[0].split('-')[2]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[1].split(':')[0]), int(issueobject[i].raw[u'fields'][u'created'].split('T')[1].split(':')[1])))
            ymd_resdate.append(d.datetime(int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[0].split('-')[0]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[0].split('-')[1]), int(issueobject[i].raw[u'fields']
                                                                                                                                                                                                                    [u'resolutiondate'].split('T')[0].split('-')[2]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[1].split(':')[0]), int(issueobject[i].raw[u'fields'][u'resolutiondate'].split('T')[1].split(':')[1])))
            delta_t.append((ymd_resdate[i] - ymd_create[i]).days)

        self.result = np.var(np.array(delta_t))
        return self.result

Answer 3

strptime 不支持解析时区。此代码对我有用

from datetime import datetime
createdTime = datetime.strptime(issue.fields.created.split(".")[0], '%Y-%m-%dT%H:%M:%S')
resolvedTime = datetime.strptime(issue.fields.resolutiondate.split(".")[0], '%Y-%m-%dT%H:%M:%S')
duration = resolvedTime - createdTime

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