README.md

git: https://github.com/wesleyshu/GAELogReporter

# to install packages
sudo apt-get install python-numpy python-scipy python-matplotlib

# download log*:
1) goto /google_appengine/google/appengine/tools 
2) python appcfg.py --append --num_days=30 --include_all request_logs ~/specless/ ~/specless/source/server/sp_log/logs/ ‘yourdate’.log
* download to ~/specless/source/server/sp_log/logs/ as ‘yourdate’.log

# to run generate the report (for now)
1) direct to directory: your_app_location/source/server/sp_log
2) run: python log_generator.py

# naming scheme:
/sp_log has three folders, /logs, /data, and /reports
download log as ‘yourdate’.log to /logs
run generator
find report ‘yourdate’.pdf in folder /report
a intermediate file ‘yourdate’.csv is generated in /data, contains: date,call,ms,cpu_ms,cpm_usd,cost

TODO:
automation probably with unix scheduler
os.system to auto-download log
upload to drive ?

Result in report:
page 1:
weekly performance for daily total, see legend for each bar
page 2 - (-3):
daily performance regarding each call
summary for top 5 cost / avg cost / cpu_ms / avg cpu_ms
from old to new
page -2*
ms prediction for next week 
report of how many hours/ minutes consumed for total usage for next week
page -1*
cpu_ms prediction for next week 
report of how many hours/ minutes needed to buy for next week

* note: x-axis is day, y-axis is time in ms scale. prediction were based on 30 day historical data.s