python_pinger.git

1) # python_pinger
2) 
3) These are different approaches to how one might implement a daemon to
4) repeatedly ping multiple hosts to see if the network is up.
5) 
6) ## Single Threaded
7) 
8) This is the most naive implementation. For each ping host, the main
9) process thread pings them one at a time, and prints any changes.
10) 

11) ![Single Threaded Pings](http://dlma.com/images/python_pinger/ping_single_threaded.png)
12) 

13) The code for such a loop might look like this:
14) 

15)     # "results" is a dict of ip_address -> last ping result

16)     for address in results.keys():
17)         result = ping(address)
18)         if result != results[address]:
19)             log(f'{time.strftime("%Y-%m-%d %H:%M:%S", now)} {address} {result}')
20)             results[address] = result
21)     time.sleep(delay)
22) 
23) Logs go to a logfile, and example output looks like this:
24) 
25)     2019-07-06 11:23:20 192.168.1.1 UP
26)     2019-07-06 11:23:20 192.168.1.12 UP
27)     2019-07-06 11:23:29 192.168.1.12 DOWN
28)     2019-07-06 11:23:39 192.168.1.12 UP

29) 
30) ### Upsides
31) 
32) Really simple code.
33) 
34) ### Downsides
35) 
36) Since the pings are serialized, one long timeout from one host could
37) affect detecting a problem at another host.
38) 

39) ## Long Lived Workers Consuming from a Queue

40) 
41) Raymond Hettinger's [PyBay 2018 Keynote](https://pybay.com/site_media/slides/raymond2017-keynote/threading.html)

42) uses the queue module to send data between threads, so I thought I'd make a
43) version of the pinger that did the same.

44) 

45) ![Long Lived Queue Workers](http://dlma.com/images/python_pinger/ping_long_lived_queue_workers.png)

46) 

47) The main thread sends an address to a queue that the worker threads wait upon.
48) 

49) See the source: **[long\_lived\_worker\_queue.py](http://git.dlma.com/python_pinger.git/blob/master/long_lived_worker_queue.py)**

50) 
51) ### Upsides
52) 
53) Multi-threaded ping calls won't block each other.
54) 
55) ### Downsides
56) 

57) The ping tasks read from, and write to a shared dictionary. (Reading and
58) updating the last status.)

59) 
60) ## Short Lived Workers
61) 

62) How about we don't keep the workers around, and only spawn them when

63) there's something to do? That way, we won't waste memory when there's

64) nothing going on. The main thread passes the address to the workers when
65) they're constructed.

66) 
67) ![Short Lived Workers](http://dlma.com/images/python_pinger/ping_short_lived_workers.png)

68) 

69) See the source: **[short\_lived\_workers.py](http://git.dlma.com/python_pinger.git/blob/master/short_lived_workers.py)**

70) 
71) ### Upsides
72) 
73) The worker tasks aren't in memory if they're not doing anything. So usually a smaller memory profile.
74) 
75) ### Downsides
76) 
77) The ping tasks still read from, and write to a shared dictionary. (Reading and updating the last status.)
78) 
79) ## Long Lived Looping Workers
80) 

81) I saved the best for last. The only thing the main thread does is bring the
82) workers and the print manager to life. The workers each independently do their own loop:
83) ping, compare, print, and wait.
84) 

85) Since the process thread doesn't have anything to do after spawning the workers,
86) it can be one of the workers.
87) 

88) ![Long Lived Looping Workers](http://dlma.com/images/python_pinger/ping_long_lived_looping_workers.png)

89) 

90) See the source: **[long\_lived\_looping\_workers.py](http://git.dlma.com/python_pinger.git/blob/master/long_lived_looping_workers.py)**

91) 
92) ### Upsides
93) 
94) No more race conditions! The worker threads mind their own business.
95) 
96) ### Downsides
97) 
98) The worker threads remain in memory.
99) 

100) ## Long Lived Looping Locked Workers
101) 
102) That was fun using only the synchronized queue class and no locks. But now that
103) we've got the long lived looping workers that don't need their own queue, let's
104) replace the print manager with a threading lock.
105) 
106) ![Long Lived Looping Locked Workers](http://dlma.com/images/python_pinger/ping_long_lived_looping_locked_workers.png)
107) 
108) See the source: **[long\_lived\_looping\_locked\_workers.py](http://git.dlma.com/python_pinger.git/blob/master/long_lived_looping_locked_workers.py)**
109) 
110) ### Upsides
111) 
112) Got rid of the entire printer thread.
113) 
114) ### Downsides
115) 
116) Uses a lock, which in more complex applications with multiple locks becomes difficult to reason about.
117)