This application is developed using Python 2.7
- beautifulsoup4
- bs4
- certifi
- chardet
- idna
- json2html
- nose
- python-dateutil
- requests
- six
- soupsieve
- tabulate
- urllib3
git clone https://github.com/kapsali29/StackStatsAPI.git
cd StackStatsAPI/
pip install .
Use the following command to see the command line arguments
stats --help
The output is:
usage: stats [-h] [--since SINCE] [--until UNTIL]
[--output_format OUTPUT_FORMAT]
Instructs stackstats package to manage date/time range and results output
format
optional arguments:
-h, --help show this help message and exit
--since SINCE Start date
--until UNTIL End date
--output_format OUTPUT_FORMAT
return the calculated statistics in tabular/html/json
Examples:
the package command returns the results by default in json format But you can define the the command to return the results in tabular or htmk format
Get the results in json format from 2018-12-03 10:00:00 until 2018-12-03 12:00:00
stats --since '2018-12-03 12:00:00' --until '2018-12-03 10:00:00'
{"average_answers_per_question": 0.6666666666666666, "accepted_answers_average_score": 0.0, "total_accepted_answers": 1, "top_ten_answers_comment_count": {"54169541": 10, "54172039": 0, "54172037": 0, "54151440": 0, "54172084": 0, "54172088": 0, "54172026": 0, "54172092": 0, "54172093": 0, "54172090": 0}}Get the results in tabular format
stats --since '2018-12-04 13:00:00' --until '2018-12-04 14:00:00' --output_format tabular
Actions Results
------------------------------ -----------------------------------------------------------------------------------------------------------------------------------
accepted_answers_average_score 0
average_answers_per_question 0.466666666667
top_ten_answers_comment_count {54172096: 0, 54171937: 4, 54172100: 0, 54169541: 10, 54172103: 0, 54172110: 0, 54172084: 1, 54172026: 0, 54171197: 0, 54172101: 0}
total_accepted_answers 0Get the results in html format
stats --since '2018-12-05 09:00:00' --until '2018-12-05 11:00:00' --output_format html
<table border="1"><tr><th>average_answers_per_question</th><td>0.7</td></tr><tr><th>accepted_answers_average_score</th><td>0</td></tr><tr><th>total_accepted_answers</th><td>0</td></tr><tr><th>top_ten_answers_comment_count</th><td><table border="1"><tr><th>54171937</th><td>4</td></tr><tr><th>54172132</th><td>0</td></tr><tr><th>54172069</th><td>0</td></tr><tr><th>54172136</th><td>0</td></tr><tr><th>54172137</th><td>0</td></tr><tr><th>54172133</th><td>0</td></tr><tr><th>54172047</th><td>1</td></tr><tr><th>54172117</th><td>2</td></tr><tr><th>54172090</th><td>0</td></tr><tr><th>54171717</th><td>6</td></tr></table></td></tr></table>import stackstats
api = stackstats.StackExchangeApi(since='2018-12-05 09:00:00', until='2018-12-05 11:00:00')
# Get all the answers since 2018-12-05 09:00:00 until 2018-12-05 11:00:00
answers = api.answers()
# Get all the accepted answers since 2018-12-05 09:00:00 until 2018-12-05 11:00:00
accepted_answers = api.accepted_answers(answers)
# Get the number of all accepted answers
total_accepted_answers = api.get_num_of_accepted_answers(accepted_answers)
# Get average score for all accepted answers since 2018-12-05 09:00:00 until 2018-12-05 11:00:00
accepted_answers_average_score = api.average_accepted_score(accepted_answers)
# Get the average answer count per question
average_answers_per_question = api.avg_count_question()
# Get the number of comments for given answer
num_of_comments = api.get_answer_comments(answer_id="54153375")
# Get the 10 answers ids with the highest score
top_ten_answers_ids = api.get_top_answers(answers)
# Get the comment count for each of the 10 answers with the highest score
number_of_comments_per_answer = api.get_top_answers_comments(top_ten_answers_ids)
# Get all statistics and return them in html/tabular/json format
statistics = api.results(format="json")To test the application you can simply do
python2 setup.py test