This tutorial is about developing bcc tools and programs using the Python interface. There are two parts: observability then networking. Snippets are taken from various programs in bcc: see their files for licences.
Also see the bcc developer's reference_guide.md, and a tutorial for end-users of tools: tutorial.md. There is also a lua interface for bcc.
This observability tutorial contains 17 lessons, and 46 enumerated things to learn.
Start by running examples/hello_world.py, while running some commands (eg, "ls") in another session. It should print "Hello, World!" for new processes. If not, start by fixing bcc: see INSTALL.md.
# ./examples/hello_world.py
bash-13364 [002] d... 24573433.052937: : Hello, World!
bash-13364 [003] d... 24573436.642808: : Hello, World!
[...]
Here's the code for hello_world.py:
from bcc import BPF
BPF(text='int kprobe__sys_clone(void *ctx) { bpf_trace_printk("Hello, World!\\n"); return 0; }').trace_print()There are six things to learn from this:
-
text='...': This defines a BPF program inline. The program is written in C. -
kprobe__sys_clone(): This is a short-cut for kernel dynamic tracing via kprobes. If the C function begins withkprobe__, the rest is treated as a kernel function name to instrument, in this case,sys_clone(). -
void *ctx: ctx has arguments, but since we aren't using them here, we'll just cast it tovoid *. -
bpf_trace_printk(): A simple kernel facility for printf() to the common trace_pipe (/sys/kernel/debug/tracing/trace_pipe). This is ok for some quick examples, but has limitations: 3 args max, 1 %s only, and trace_pipe is globally shared, so concurrent programs will have clashing output. A better interface is via BPF_PERF_OUTPUT(), covered later. -
return 0;: Necessary formality (if you want to know why, see #139). -
.trace_print(): A bcc routine that reads trace_pipe and prints the output.
Write a program that traces the sys_sync() kernel function. Print "sys_sync() called" when it runs. Test by running sync in another session while tracing. The hello_world.py program has everything you need for this.
Improve it by printing "Tracing sys_sync()... Ctrl-C to end." when the program first starts. Hint: it's just Python.
This program is in examples/tracing/hello_fields.py. Sample output (run commands in another session):
# ./examples/tracing/hello_fields.py
TIME(s) COMM PID MESSAGE
24585001.174885999 sshd 1432 Hello, World!
24585001.195710000 sshd 15780 Hello, World!
24585001.991976000 systemd-udevd 484 Hello, World!
24585002.276147000 bash 15787 Hello, World!
Code:
from bcc import BPF
# define BPF program
prog = """
int hello(void *ctx) {
bpf_trace_printk("Hello, World!\\n");
return 0;
}
"""
# load BPF program
b = BPF(text=prog)
b.attach_kprobe(event=b.get_syscall_fnname("clone"), fn_name="hello")
# header
print("%-18s %-16s %-6s %s" % ("TIME(s)", "COMM", "PID", "MESSAGE"))
# format output
while 1:
try:
(task, pid, cpu, flags, ts, msg) = b.trace_fields()
except ValueError:
continue
print("%-18.9f %-16s %-6d %s" % (ts, task, pid, msg))This is similar to hello_world.py, and traces new processes via sys_clone() again, but has a few more things to learn:
-
prog =: This time we declare the C program as a variable, and later refer to it. This is useful if you want to add some string substitutions based on command line arguments. -
hello(): Now we're just declaring a C function, instead of thekprobe__shortcut. We'll refer to this later. All C functions declared in the BPF program are expected to be executed on a probe, hence they all need to take apt_reg* ctxas first argument. If you need to define some helper function that will not be executed on a probe, they need to be defined asstatic inlinein order to be inlined by the compiler. Sometimes you would also need to add_always_inlinefunction attribute to it. -
b.attach_kprobe(event=b.get_syscall_fnname("clone"), fn_name="hello"): Creates a kprobe for the kernel clone system call function, which will execute our defined hello() function. You can call attach_kprobe() more than once, and attach your C function to multiple kernel functions. -
b.trace_fields(): Returns a fixed set of fields from trace_pipe. Similar to trace_print(), this is handy for hacking, but for real tooling we should switch to BPF_PERF_OUTPUT().
Remember the days of sysadmins typing sync three times on a slow console before reboot, to give the first asynchronous sync time to complete? Then someone thought sync;sync;sync was clever, to run them all on one line, which became industry practice despite defeating the original purpose! And then sync became synchronous, so more reasons it was silly. Anyway.
The following example times how quickly the do_sync function is called, and prints output if it has been called more recently than one second ago. A sync;sync;sync will print output for the 2nd and 3rd sync's:
# ./examples/tracing/sync_timing.py
Tracing for quick sync's... Ctrl-C to end
At time 0.00 s: multiple syncs detected, last 95 ms ago
At time 0.10 s: multiple syncs detected, last 96 ms ago
This program is examples/tracing/sync_timing.py:
from __future__ import print_function
from bcc import BPF
# load BPF program
b = BPF(text="""
#include <uapi/linux/ptrace.h>
BPF_HASH(last);
int do_trace(struct pt_regs *ctx) {
u64 ts, *tsp, delta, key = 0;
// attempt to read stored timestamp
tsp = last.lookup(&key);
if (tsp != 0) {
delta = bpf_ktime_get_ns() - *tsp;
if (delta < 1000000000) {
// output if time is less than 1 second
bpf_trace_printk("%d\\n", delta / 1000000);
}
last.delete(&key);
}
// update stored timestamp
ts = bpf_ktime_get_ns();
last.update(&key, &ts);
return 0;
}
""")
b.attach_kprobe(event=b.get_syscall_fnname("sync"), fn_name="do_trace")
print("Tracing for quick sync's... Ctrl-C to end")
# format output
start = 0
while 1:
(task, pid, cpu, flags, ts, ms) = b.trace_fields()
if start == 0:
start = ts
ts = ts - start
print("At time %.2f s: multiple syncs detected, last %s ms ago" % (ts, ms))Things to learn:
bpf_ktime_get_ns(): Returns the time as nanoseconds.BPF_HASH(last): Creates a BPF map object that is a hash (associative array), called "last". We didn't specify any further arguments, so it defaults to key and value types of u64.key = 0: We'll only store one key/value pair in this hash, where the key is hardwired to zero.last.lookup(&key): Lookup the key in the hash, and return a pointer to its value if it exists, else NULL. We pass the key in as an address to a pointer.last.delete(&key): Delete the key from the hash. This is currently required because of a kernel bug in.update().last.update(&key, &ts): Associate the value in the 2nd argument to the key, overwriting any previous value. This records the timestamp.
Modify the sync_timing.py program (prior lesson) to store the count of all kernel sync system calls (both fast and slow), and print it with the output. This count can be recorded in the BPF program by adding a new key index to the existing hash.
Browse the examples/tracing/disksnoop.py program to see what is new. Here is some sample output:
# ./disksnoop.py
TIME(s) T BYTES LAT(ms)
16458043.436012 W 4096 3.13
16458043.437326 W 4096 4.44
16458044.126545 R 4096 42.82
16458044.129872 R 4096 3.24
[...]
And a code snippet:
[...]
REQ_WRITE = 1 # from include/linux/blk_types.h
# load BPF program
b = BPF(text="""
#include <uapi/linux/ptrace.h>
#include <linux/blkdev.h>
BPF_HASH(start, struct request *);
void trace_start(struct pt_regs *ctx, struct request *req) {
// stash start timestamp by request ptr
u64 ts = bpf_ktime_get_ns();
start.update(&req, &ts);
}
void trace_completion(struct pt_regs *ctx, struct request *req) {
u64 *tsp, delta;
tsp = start.lookup(&req);
if (tsp != 0) {
delta = bpf_ktime_get_ns() - *tsp;
bpf_trace_printk("%d %x %d\\n", req->__data_len,
req->cmd_flags, delta / 1000);
start.delete(&req);
}
}
""")
b.attach_kprobe(event="blk_start_request", fn_name="trace_start")
b.attach_kprobe(event="blk_mq_start_request", fn_name="trace_start")
b.attach_kprobe(event="blk_account_io_completion", fn_name="trace_completion")
[...]Things to learn:
REQ_WRITE: We're defining a kernel constant in the Python program because we'll use it there later. If we were using REQ_WRITE in the BPF program, it should just work (without needing to be defined) with the appropriate #includes.trace_start(struct pt_regs *ctx, struct request *req): This function will later be attached to kprobes. The arguments to kprobe functions arestruct pt_regs *ctx, for registers and BPF context, and then the actual arguments to the function. We'll attach this to blk_start_request(), where the first argument isstruct request *.start.update(&req, &ts): We're using the pointer to the request struct as a key in our hash. What? This is commonplace in tracing. Pointers to structs turn out to be great keys, as they are unique: two structs can't have the same pointer address. (Just be careful about when it gets free'd and reused.) So what we're really doing is tagging the request struct, which describes the disk I/O, with our own timestamp, so that we can time it. There's two common keys used for storing timestamps: pointers to structs, and, thread IDs (for timing function entry to return).req->__data_len: We're dereferencing members ofstruct request. See its definition in the kernel source for what members are there. bcc actually rewrites these expressions to be a series ofbpf_probe_read()calls. Sometimes bcc can't handle a complex dereference, and you need to callbpf_probe_read()directly.
This is a pretty interesting program, and if you can understand all the code, you'll understand many important basics. We're still using the bpf_trace_printk() hack, so let's fix that next.
Let's finally stop using bpf_trace_printk() and use the proper BPF_PERF_OUTPUT() interface. This will also mean we stop getting the free trace_field() members like PID and timestamp, and will need to fetch them directly. Sample output while commands are run in another session:
# ./hello_perf_output.py
TIME(s) COMM PID MESSAGE
0.000000000 bash 22986 Hello, perf_output!
0.021080275 systemd-udevd 484 Hello, perf_output!
0.021359520 systemd-udevd 484 Hello, perf_output!
0.021590610 systemd-udevd 484 Hello, perf_output!
[...]
Code is examples/tracing/hello_perf_output.py:
from bcc import BPF
import ctypes as ct
# define BPF program
prog = """
#include <linux/sched.h>
// define output data structure in C
struct data_t {
u32 pid;
u64 ts;
char comm[TASK_COMM_LEN];
};
BPF_PERF_OUTPUT(events);
int hello(struct pt_regs *ctx) {
struct data_t data = {};
data.pid = bpf_get_current_pid_tgid();
data.ts = bpf_ktime_get_ns();
bpf_get_current_comm(&data.comm, sizeof(data.comm));
events.perf_submit(ctx, &data, sizeof(data));
return 0;
}
"""
# load BPF program
b = BPF(text=prog)
b.attach_kprobe(event=b.get_syscall_fnname("clone"), fn_name="hello")
# define output data structure in Python
TASK_COMM_LEN = 16 # linux/sched.h
class Data(ct.Structure):
_fields_ = [("pid", ct.c_uint),
("ts", ct.c_ulonglong),
("comm", ct.c_char * TASK_COMM_LEN)]
# header
print("%-18s %-16s %-6s %s" % ("TIME(s)", "COMM", "PID", "MESSAGE"))
# process event
start = 0
def print_event(cpu, data, size):
global start
event = ct.cast(data, ct.POINTER(Data)).contents
if start == 0:
start = event.ts
time_s = (float(event.ts - start)) / 1000000000
print("%-18.9f %-16s %-6d %s" % (time_s, event.comm, event.pid,
"Hello, perf_output!"))
# loop with callback to print_event
b["events"].open_perf_buffer(print_event)
while 1:
b.perf_buffer_poll()Things to learn:
struct data_t: This defines the C struct we'll use to pass data from kernel to user space.BPF_PERF_OUTPUT(events): This names our output channel "events".struct data_t data = {};: Create an empty data_t struct that we'll then populate.bpf_get_current_pid_tgid(): Returns the process ID in the lower 32 bits (kernel's view of the PID, which in user space is usually presented as the thread ID), and the thread group ID in the upper 32 bits (what user space often thinks of as the PID). By directly setting this to a u32, we discard the upper 32 bits. Should you be presenting the PID or the TGID? For a multi-threaded app, the TGID will be the same, so you need the PID to differentiate them, if that's what you want. It's also a question of expectations for the end user.bpf_get_current_comm(): Populates the first argument address with the current process name.events.perf_submit(): Submit the event for user space to read via a perf ring buffer.class Data(ct.Structure): Now define the Python version of the C data structure.def print_event(): Define a Python function that will handle reading events from theeventsstream.b["events"].open_perf_buffer(print_event): Associate the Pythonprint_eventfunction with theeventsstream.while 1: b.perf_buffer_poll(): Block waiting for events.
This may be improved in future bcc versions. Eg, the Python data struct could be auto-generated from the C code.
Rewrite sync_timing.py, from a prior lesson, to use BPF_PERF_OUTPUT.
The following tool records a histogram of disk I/O sizes. Sample output:
# ./bitehist.py
Tracing... Hit Ctrl-C to end.
^C
kbytes : count distribution
0 -> 1 : 3 | |
2 -> 3 : 0 | |
4 -> 7 : 211 |********** |
8 -> 15 : 0 | |
16 -> 31 : 0 | |
32 -> 63 : 0 | |
64 -> 127 : 1 | |
128 -> 255 : 800 |**************************************|
Code is examples/tracing/bitehist.py:
from __future__ import print_function
from bcc import BPF
from time import sleep
# load BPF program
b = BPF(text="""
#include <uapi/linux/ptrace.h>
#include <linux/blkdev.h>
BPF_HISTOGRAM(dist);
int kprobe__blk_account_io_completion(struct pt_regs *ctx, struct request *req)
{
dist.increment(bpf_log2l(req->__data_len / 1024));
return 0;
}
""")
# header
print("Tracing... Hit Ctrl-C to end.")
# trace until Ctrl-C
try:
sleep(99999999)
except KeyboardInterrupt:
print()
# output
b["dist"].print_log2_hist("kbytes")A recap from earlier lessons:
kprobe__: This prefix means the rest will be treated as a kernel function name that will be instrumented using kprobe.struct pt_regs *ctx, struct request *req: Arguments to kprobe. Thectxis registers and BPF context, thereqis the first argument to the instrumented function:blk_account_io_completion().req->__data_len: Dereferencing that member.
New things to learn:
BPF_HISTOGRAM(dist): Defines a BPF map object that is a histogram, and names it "dist".dist.increment(): Increments the histogram bucket index provided as first argument by one by default. Optionally, custom increments can be passed as the second argument.bpf_log2l(): Returns the log-2 of the provided value. This becomes the index of our histogram, so that we're constructing a power-of-2 histogram.b["dist"].print_log2_hist("kbytes"): Prints the "dist" histogram as power-of-2, with a column header of "kbytes". The only data transferred from kernel to user space is the bucket counts, making this efficient.
Write a program that times disk I/O, and prints a histogram of their latency. Disk I/O instrumentation and timing can be found in the disksnoop.py program from a prior lesson, and histogram code can be found in bitehist.py from a prior lesson.
This example is split into separate Python and C files. Example output:
# ./vfsreadlat.py 1
Tracing... Hit Ctrl-C to end.
usecs : count distribution
0 -> 1 : 0 | |
2 -> 3 : 2 |*********** |
4 -> 7 : 7 |****************************************|
8 -> 15 : 4 |********************** |
usecs : count distribution
0 -> 1 : 29 |****************************************|
2 -> 3 : 28 |************************************** |
4 -> 7 : 4 |***** |
8 -> 15 : 8 |*********** |
16 -> 31 : 0 | |
32 -> 63 : 0 | |
64 -> 127 : 0 | |
128 -> 255 : 0 | |
256 -> 511 : 2 |** |
512 -> 1023 : 0 | |
1024 -> 2047 : 0 | |
2048 -> 4095 : 0 | |
4096 -> 8191 : 4 |***** |
8192 -> 16383 : 6 |******** |
16384 -> 32767 : 9 |************ |
32768 -> 65535 : 6 |******** |
65536 -> 131071 : 2 |** |
usecs : count distribution
0 -> 1 : 11 |****************************************|
2 -> 3 : 2 |******* |
4 -> 7 : 10 |************************************ |
8 -> 15 : 8 |***************************** |
16 -> 31 : 1 |*** |
32 -> 63 : 2 |******* |
[...]
Browse the code in examples/tracing/vfsreadlat.py and examples/tracing/vfsreadlat.c. Things to learn:
b = BPF(src_file = "vfsreadlat.c"): Read the BPF C program from a separate source file.b.attach_kretprobe(event="vfs_read", fn_name="do_return"): Attaches the BPF C functiondo_return()to the return of the kernel functionvfs_read(). This is a kretprobe: instrumenting the return from a function, rather than its entry.b["dist"].clear(): Clears the histogram.
Tracing while a dd if=/dev/urandom of=/dev/null bs=8k count=5 is run:
# ./urandomread.py
TIME(s) COMM PID GOTBITS
24652832.956994001 smtp 24690 384
24652837.726500999 dd 24692 65536
24652837.727111001 dd 24692 65536
24652837.727703001 dd 24692 65536
24652837.728294998 dd 24692 65536
24652837.728888001 dd 24692 65536
Hah! I caught smtp by accident. Code is examples/tracing/urandomread.py:
from __future__ import print_function
from bcc import BPF
# load BPF program
b = BPF(text="""
TRACEPOINT_PROBE(random, urandom_read) {
// args is from /sys/kernel/debug/tracing/events/random/urandom_read/format
bpf_trace_printk("%d\\n", args->got_bits);
return 0;
}
""")
# header
print("%-18s %-16s %-6s %s" % ("TIME(s)", "COMM", "PID", "GOTBITS"))
# format output
while 1:
try:
(task, pid, cpu, flags, ts, msg) = b.trace_fields()
except ValueError:
continue
print("%-18.9f %-16s %-6d %s" % (ts, task, pid, msg))Things to learn:
TRACEPOINT_PROBE(random, urandom_read): Instrument the kernel tracepointrandom:urandom_read. These have a stable API, and thus are recommend to use instead of kprobes, wherever possible. You can runperf listfor a list of tracepoints. Linux >= 4.7 is required to attach BPF programs to tracepoints.args->got_bits:argsis auto-populated to be a structure of the tracepoint arguments. The comment above says where you can see that structure. Eg:
# cat /sys/kernel/debug/tracing/events/random/urandom_read/format
name: urandom_read
ID: 972
format:
field:unsigned short common_type; offset:0; size:2; signed:0;
field:unsigned char common_flags; offset:2; size:1; signed:0;
field:unsigned char common_preempt_count; offset:3; size:1; signed:0;
field:int common_pid; offset:4; size:4; signed:1;
field:int got_bits; offset:8; size:4; signed:1;
field:int pool_left; offset:12; size:4; signed:1;
field:int input_left; offset:16; size:4; signed:1;
print fmt: "got_bits %d nonblocking_pool_entropy_left %d input_entropy_left %d", REC->got_bits, REC->pool_left, REC->input_left
In this case, we were printing the got_bits member.
Convert disksnoop.py from a previous lesson to use the block:block_rq_issue and block:block_rq_complete tracepoints.
This program instruments a user-level function, the strlen() library function, and frequency counts its string argument. Example output:
# ./strlen_count.py
Tracing strlen()... Hit Ctrl-C to end.
^C COUNT STRING
1 " "
1 "/bin/ls"
1 "."
1 "cpudist.py.1"
1 ".bashrc"
1 "ls --color=auto"
1 "key_t"
[...]
10 "a7:~# "
10 "/root"
12 "LC_ALL"
12 "en_US.UTF-8"
13 "en_US.UTF-8"
20 "~"
70 "#%^,~:-=?+/}"
340 "\x01\x1b]0;root@bgregg-test: ~\x07\x02root@bgregg-test:~# "
These are various strings that are being processed by this library function while tracing, along with their frequency counts. strlen() was called on "LC_ALL" 12 times, for example.
Code is examples/tracing/strlen_count.py:
from __future__ import print_function
from bcc import BPF
from time import sleep
# load BPF program
b = BPF(text="""
#include <uapi/linux/ptrace.h>
struct key_t {
char c[80];
};
BPF_HASH(counts, struct key_t);
int count(struct pt_regs *ctx) {
if (!PT_REGS_PARM1(ctx))
return 0;
struct key_t key = {};
u64 zero = 0, *val;
bpf_probe_read(&key.c, sizeof(key.c), (void *)PT_REGS_PARM1(ctx));
// could also use `counts.increment(key)`
val = counts.lookup_or_init(&key, &zero);
(*val)++;
return 0;
};
""")
b.attach_uprobe(name="c", sym="strlen", fn_name="count")
# header
print("Tracing strlen()... Hit Ctrl-C to end.")
# sleep until Ctrl-C
try:
sleep(99999999)
except KeyboardInterrupt:
pass
# print output
print("%10s %s" % ("COUNT", "STRING"))
counts = b.get_table("counts")
for k, v in sorted(counts.items(), key=lambda counts: counts[1].value):
print("%10d \"%s\"" % (v.value, k.c.encode('string-escape')))Things to learn:
PT_REGS_PARM1(ctx): This fetches the first argument tostrlen(), which is the string.b.attach_uprobe(name="c", sym="strlen", fn_name="count"): Attach to library "c" (if this is the main program, use its pathname), instrument the user-level functionstrlen(), and on execution call our C functioncount().
This program instruments a user-defined static tracing (USDT) probe, which is the user-level version of a kernel tracepoint. Sample output:
# ./nodejs_http_server.py 24728
TIME(s) COMM PID ARGS
24653324.561322998 node 24728 path:/index.html
24653335.343401998 node 24728 path:/images/welcome.png
24653340.510164998 node 24728 path:/images/favicon.png
Relevant code from examples/tracing/nodejs_http_server.py:
from __future__ import print_function
from bcc import BPF, USDT
import sys
if len(sys.argv) < 2:
print("USAGE: nodejs_http_server PID")
exit()
pid = sys.argv[1]
debug = 0
# load BPF program
bpf_text = """
#include <uapi/linux/ptrace.h>
int do_trace(struct pt_regs *ctx) {
uint64_t addr;
char path[128]={0};
bpf_usdt_readarg(6, ctx, &addr);
bpf_probe_read(&path, sizeof(path), (void *)addr);
bpf_trace_printk("path:%s\\n", path);
return 0;
};
"""
# enable USDT probe from given PID
u = USDT(pid=int(pid))
u.enable_probe(probe="http__server__request", fn_name="do_trace")
if debug:
print(u.get_text())
print(bpf_text)
# initialize BPF
b = BPF(text=bpf_text, usdt_contexts=[u])Things to learn:
bpf_usdt_readarg(6, ctx, &addr): Read the address of argument 6 from the USDT probe intoaddr.bpf_probe_read(&path, sizeof(path), (void *)addr): Now the stringaddrpoints to into ourpathvariable.u = USDT(pid=int(pid)): Initialize USDT tracing for the given PID.u.enable_probe(probe="http__server__request", fn_name="do_trace"): Attach ourdo_trace()BPF C function to the Node.jshttp__server__requestUSDT probe.b = BPF(text=bpf_text, usdt_contexts=[u]): Need to pass in our USDT object,u, to BPF object creation.
This is an older tutorial included as a bonus lesson. Use this for recap and to reinforce what you've already learned.
This is a slightly more complex tracing example than Hello World. This program will be invoked for every task change in the kernel, and record in a BPF map the new and old pids.
The C program below introduces two new concepts.
The first is the macro BPF_TABLE. This defines a table (type="hash"), with key
type key_t and leaf type u64 (a single counter). The table name is stats,
containing 1024 entries maximum. One can lookup, lookup_or_init, update,
and delete entries from the table.
The second concept is the prev argument. This argument is treated specially by
the BCC frontend, such that accesses to this variable are read from the saved
context that is passed by the kprobe infrastructure. The prototype of the args
starting from position 1 should match the prototype of the kernel function being
kprobed. If done so, the program will have seamless access to the function
parameters.
#include <uapi/linux/ptrace.h>
#include <linux/sched.h>
struct key_t {
u32 prev_pid;
u32 curr_pid;
};
// map_type, key_type, leaf_type, table_name, num_entry
BPF_HASH(stats, struct key_t, u64, 1024);
int count_sched(struct pt_regs *ctx, struct task_struct *prev) {
struct key_t key = {};
u64 zero = 0, *val;
key.curr_pid = bpf_get_current_pid_tgid();
key.prev_pid = prev->pid;
// could also use `stats.increment(key);`
val = stats.lookup_or_init(&key, &zero);
(*val)++;
return 0;
}The userspace component loads the file shown above, and attaches it to the
finish_task_switch kernel function.
The [] operator of the BPF object gives access to each BPF_TABLE in the
program, allowing pass-through access to the values residing in the kernel. Use
the object as you would any other python dict object: read, update, and deletes
are all allowed.
from bcc import BPF
from time import sleep
b = BPF(src_file="task_switch.c")
b.attach_kprobe(event="finish_task_switch", fn_name="count_sched")
# generate many schedule events
for i in range(0, 100): sleep(0.01)
for k, v in b["stats"].items():
print("task_switch[%5d->%5d]=%u" % (k.prev_pid, k.curr_pid, v.value))These programs have now been merged, and are both in examples/tracing/task_switch.py.
For further study, see Sasha Goldshtein's linux-tracing-workshop, which contains additional labs. There are also many tools in bcc /tools to study.
Please read CONTRIBUTING-SCRIPTS.md if you wish to contrubite tools to bcc. At the bottom of the main README.md, you'll also find methods for contacting us. Good luck, and happy tracing!
To do.