I have the following code where I have a list of usernames and I try and check if the users are in a specific Windows Usergroup using net user domain | find somegroup
.
The problem is that I run that command for about 8 usergroups per username and it is slow. I would like to send off these calls using futures and even separate threads (if it makes it quicker).
I just have to wait at the end before i do anything else. How do I go about doing it in Python?
for one_username in user_list: response = requests.get(somecontent) bs_parsed = BeautifulSoup(response.content, 'html.parser') find_all2 = bs_parsed.find("div", {"class": "QuickLinks"}) name = re.sub("ss+", ' ', find_all2.find("td", text="Name").find_next_sibling("td").text) find_all = bs_parsed.find_all("div", {"class": "visible"}) all_perms = "" d.setdefault(one_username + " (" + name + ")", []) for value in find_all: test = value.find("a", {"onmouseover": True}) if test is not None: if "MyAppID" in test.text: d[one_username + " (" + name + ")"].append(test.text) for group in groups: try: d[one_username + " (" + name + ")"].append(check_output("net user /domain " + one_username + "| find "" + group + """, shell=True, stderr=subprocess.STDOUT).strip().decode("utf-8")) except Exception: pass
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Answer
(This answer currently ignores HTML parsing your code does … you can queue that into a pool identically to how this approach queues the net user
calls)
First, lets define a function that takes a tuple
of (user, group)
and returns the desired information.
# a function that calls net user to find info on a (user, group) def get_group_info(usr_grp): # unpack the arguments usr, grp = usr_grp try: return (usr, grp, check_output( "net user /domain " + usr + "| find "" + grp + """, shell=True, stderr=subprocess.STDOUT ).strip().decode("utf-8"))) except Exception: return (usr, grp, None)
Now, we can run this in a thread pool using multiprocessing.dummy.Pool
from multiprocessing.dummy import Pool import itertools # create a pool with four worker threads pool = Pool(4) # run get_group_info for every user, group async_result = pool.map_async(get_group_info, itertools.product(user_list, groups)) # now do some other work we care about ... # and then wait on our results results = async_result.get()
The results
are a list of (user, group, data)
tuples and can be processed as you desire.
Note: This code is currently untested due to a difference in platforms