Finding audio "tics" in stereo wav files using python I have thousands of audio files that I want to "batch" process searching for audio tics.  This is easily done using a DAW but that requires opening each file independently, searching for the tic (visually looking at the waveform or listening to the file play), and then cleaning the tic with signal processing tools within the DAW.  However, this approach is extremely time consuming.  

I'd like to write a program using python to process all of the files and provide candidate files that contain tics in the audio.  I've been researching the web and found tons of references for plotting frequencies using fft after reading in the wav file but I don't want to plot the data I want to examine it in the program to determine if there is an audio tic (or potential tic) present.

Any help or ideas would be deeply appreciated.
I don’t know what DAW you use, but I’m pretty sure Waves and probably some other companies have plug ins for this kind of application.
After reviewing your images it seems that the tics are high frequency and high amplitude so there are some simple things you could try.
You could check each sample and compare the absolute value to some threshold, such that if it is higher, you have a tic.
Second, you could high pass filter the signal to isolate the tic, then do the previous step.
Third, you could calculate the RMS of the signal, then compare the absolute value (peak) of each sample to the RMS, such that a tic occurs whenever the ratio or difference exceeds a given threshold.
Lastly, you could do frequency magnitude analysis.  For this you would set up a window size N and step size M.  Every M samples you take N samples and apply a window function, then calculate the frequency transform magnitude of the N samples.  One idea would be to look at the rate of change of individual frequency components such that if it exceeds a threshold you have a tic.  This is probably the most CPU intensive and complex implementation.