Python - 循环遍历列表中的一组项目

Question

I have the below query that extract some data from JIRA and have that saved to a csv. I am however trying to loop in through a series of projects. I see that the latest project gets saved and not all projects passed in the loop.

Given below is what I am trying to perform :

projects = ['project_a','project_b']

for project in projects:
    issues = jira.search_issues('project= ' + project)

    result = []
    for value in issues:
        value = value
        timeSpentSeconds = i.timeSpentSeconds
        timeSpent = i.timeSpent
        updated = i.updated
        started = i.started
        author = i.author
        dict_ = {'value': value,
                     'timeSpent': timeSpent,
                     'updated': updated,
                     'started': started,
                     'author': author}

        result.append(dict_)

        df = pd.DataFrame(result)


        df.to_csv('/Desktop/file.csv')

Answer 1

You're overwriting the data frame at each loop df.to_csv('/Desktop/file.csv') . Everytime, you write the new project in the file and erase the old one.

You should define result before starting to iterate over the projects. Otherwise, you can create one csv file per project.

Also it would be more efficient to create and save the dataframe at the end of the top level loop.

Answer 2

df.to_csv('/Desktop/file.csv', mode='a')

Default mode of .to_csv is write. You have to change it to append. If you want to do it that way.

Better solution would be to make whole dataframe then saving it to wanted file

projects = ['project_a','project_b']

result = []

for project in projects:
    issues = jira.search_issues('project= ' + project, maxResults=False, fields="worklog")   
    for value in issues:
        for i in value.fields.worklog.worklogs:
            value = value
            timeSpentSeconds = i.timeSpentSeconds
            timeSpent = i.timeSpent
            updated = i.updated
            started = i.started
            author = i.author
            dict_ = {'value': value,
                     'timeSpent': timeSpent,
                     'updated': updated,
                     'started': started,
                     'author': author}

            result.append(dict_)

df = pd.DataFrame(result)
df.to_csv('/Desktop/file.csv')