> I'm trying to get a sense of the rate limitations of a python frontend.

1) python is single-threaded, for ultimate performance, a MIDAS frontend (or any DAQ 
application) has to be multithreaded:
a) thread with busy loop read the data and place it into a FIFO
b) thread to read data from FIFO and send it to SYSTEM buffer shared memory or to 
mserver
c) thread to respond to begin-run, end-run, etc RPCs
d) probably a thread to recycle memory from thread (b) back to thread (a) if per-event 
malloc()/free() adds too much overhead

2) data readout. C++ AXI bus access is compiled into 1 instruction and results in 1 AXI 
bus operation. comparable for python likely has much more overhead, slows you down.

3) event bank filling. C++ for() loop is compiled into very compact machine code, 
python loop cannot because each array element can be random data type, shows you down.

bottom line, there is a reason high speed data acquisitions are written in C/C++, not 
in shell, perl, tcl/tk, or (today's favourite) python.

> The C++ frontend is about 100 times faster in both data and event rates.

This is as expected. You can probably improve python code to get closer to 10 times 
slower than C++. But consider:

a) will it be "fast enough" for the task?
b) learning C++ and optimizing python to within "2-3-10x slower than C++" may involve a 
similar amount of time and effort.

And you have not looked at the real-time properties of your frontend. You may discover 
that it's actually faster than you think, but occasionally stops for a millisecond (or 
two or hundred). some applications a notorious for running memory garbage collection 
just at the wrong time.

I am working right now on exactly this problem, I have a 1 GHz ARM CPU (Cyclone-V FPGA) 
and I need to push data out at 100 Mbytes/sec while avoiding and bad-real-time dropouts  
that cause the FPGA data FIFO to overflow. And I only have 2 CPU cores, 1 to read the 
FPGA FIFO, 1 to run the TCP/IP stack and the ethernet driver. No this can be done with 
python.

K.O.