Profile CSP Code

The csp.profiler library allows users to time cycle/node executions during a graph run. There are two available utilities.

One can use these metrics to identify bottlenecks/inefficiencies in their graphs.

Table of Contents

• Table of Contents
• Profiling a real-time csp.graph
• Saving raw profiling data to a file
• graph_info: build-time information

Profiling a real-time csp.graph

The csp.profiler library provides a GUI for profiling real-time CSP graphs. One can access this GUI by adding a http_port argument to their profiler call.

with profiler.Profiler(http_port=8888) as p:
    results = csp.run(graph, starttime=st, endtime=et) # run the graph normally

This will open up the GUI on localhost:8888 (as http_port=8888) which will display real-time node timing, cycle timing and memory snapshots. Profiling stats will be calculated whenever you refresh the page or call a GET request. Additionally, you can add the format=jsonargument (localhost:8888?format=json) to your request to receive the ProfilerInfo as a JSON object rather than the HTML display.

Users can add the display_graphs=True flag to include bar/pie charts of node execution times in the web UI. The matplotlib package is required to use the flag.

with profiler.Profiler(http_port=8888, display_graphs=True) as p:
    ...

Saving raw profiling data to a file

Users can save individual node execution times and individual cycle execution times to a .csv file if they desire. This is useful if you want to apply your own analysis e.g. calculate percentiles. To do this, simply add the flags node_file=<filename.csv> or cycle_file=<filename.csv>

with profiler.Profiler(cycle_file="cycle_data.csv", node_file="node_data.csv") as p:
    ...

After the graph is run, the file node_data.csv contains:

Node Type,Execution Time
count,1.9814e-05
cast_int_to_float,1.2791e-05
_time_window_updates,4.759e-06
...

After the graph is run, the file cycle_data.csv contains:

Execution Time
9.4757e-05
4.5205e-05
2.2873e-05
...

graph_info: build-time information

Users can also extract build-time information about the graph without running it by calling profiler.graph_info.

The code snippet below shows how to call graph_info.

from csp import profiler

info = profiler.graph_info(graph)