Add matplotlib example

demo/pybpf4.py

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+import time
+
+from pythonbpf import bpf, map, section, bpfglobal, BPF
+from pythonbpf.helpers import pid
+from pythonbpf.maps import HashMap
+from pylibbpf import *
+from ctypes import c_void_p, c_int64, c_uint64, c_int32
+import matplotlib.pyplot as plt
+
+# This program attaches an eBPF tracepoint to sys_enter_clone,
+# counts per-PID clone syscalls, stores them in a hash map,
+# and then plots the distribution as a histogram using matplotlib.
+# It provides a quick view of process creation activity over 10 seconds.
+# Everything is done with Python only code and with the new pylibbpf library.
+# Run `sudo /path/to/python/binary/ pybpf4.py`
+
+@bpf
+@map
+def hist() -> HashMap:
+    return HashMap(key=c_int32, value=c_uint64, max_entries=4096)
+
+@bpf
+@section("tracepoint/syscalls/sys_enter_clone")
+def hello(ctx: c_void_p) -> c_int64:
+    process_id = pid()
+    one = 1
+    prev = hist().lookup(process_id)
+    if prev:
+        previous_value = prev + 1
+        print(f"count: {previous_value} with {process_id}")
+        hist().update(process_id, previous_value)
+        return c_int64(0)
+    else:
+        hist().update(process_id, one)
+    return c_int64(0)
+
+
+@bpf
+@bpfglobal
+def LICENSE() -> str:
+    return "GPL"
+
+
+b = BPF()
+b.load_and_attach()
+hist = BpfMap(b, hist)
+print("Recording")
+time.sleep(10)
+
+counts = list(hist.values())
+
+plt.hist(counts, bins=20)
+plt.xlabel("Clone calls per PID")
+plt.ylabel("Frequency")
+plt.title("Syscall clone counts")
+plt.show()