# Piefiller Graphical profiler for Love2D >= 0.9.2 Originally by devfirefly, heavily modified by Guard13007. Note that a lot of functionality is undocumented right now, and that some functionality doesn't work as originally intended (such as setting the position and scale of the profiler). The default settings should get you going pretty easily, the key thing to maybe change is calling the constructor with a table with its own `scale` value. # Usage 1) Require the file: ```lua local Piefiller = require("piefiller") ``` 2) Make a new instance of piefiller: ```lua local pie = Piefiller() ``` 3) Attach the piefiller to the part of your application that you want to monitor (love.update and love.draw typically are good places): ```lua function love.update() pie:attach() -- do something pie:detach() end ``` 4) Draw the output and pass key events to your piefiller: ```lua function love.draw() pie:draw() end function love.keypressed(key) pie:keypressed(key) end ``` 5) With sufficient output, press the `E` key to output to file. Example output: ``` -----drawRectangles----- source:@main.lua:20 current line: 22 time: 548.325 percentage: 98 % ---------------- ``` # Keys p = shows/hides the profiler r = resets the pie up = decreases depth down = increases depth \- = decreases step size = = increases step size s = shortens the names displayed h = shows/hides hidden processes e = saves to file called "Profile.txt" and opens directory for you ## To redefine these: Commands available: ```lua reset increase_depth decrease_depth increase_step_size decrease_step_size shorten_names show_hidden save_to_file show_profiler ``` To redefine only one of the keys: ```lua pie:setKey(command, key) ``` example: ```lua pie:setKey("increase_depth","up") ``` To redefine all of the keys: ```lua table = { "increase_depth" = "up" } pie:setKey(table) ``` # For your own interpretation If you wish to interpret the data on your own use `pie:unpack()`. Output is a table as such: ```lua data = { items = { { name, line_defined, current_line, source, time_taken, percentage, caller, } }, about = { depth, step, totalTime, }, } ``` # Additional notes The best depth to search in is usually 2 and sometimes 3. When used in large applications the output may be too much to read, however you most likely will only be wanting to optimize the most expensive items. (And you can always output the data to review later.)