On my local machine, I run a python script which contains this line
bashCommand = "cwm --rdf test.rdf --ntriples > test.nt"
os.system(bashCommand)
This works fine.
Then I run the same code on a server and I get the following error message
'import site' failed; use -v for traceback
Traceback (most recent call last):
File "/usr/bin/cwm", line 48, in <module>
from swap import diag
ImportError: No module named swap
So what I did then is I inserted a print bashCommand which prints me than the command in the terminal before it runs it with os.system().
Of course, I get again the error (caused by os.system(bashCommand)) but before that error it prints the command in the terminal. Then I just copied that output and did a copy paste into the terminal and hit enter and it works...
Does anyone have a clue what's going on?
Don't use os.system. It has been deprecated in favor of subprocess. From the docs: "This module intends to replace several older modules and functions: os.system, os.spawn".
Like in your case:
import subprocess
bashCommand = "cwm --rdf test.rdf --ntriples > test.nt"
process = subprocess.Popen(bashCommand.split(), stdout=subprocess.PIPE)
output, error = process.communicate()
To somewhat expand on the earlier answers here, there are a number of details which are commonly overlooked.
Prefer subprocess.run() over subprocess.check_call() and friends over subprocess.call() over subprocess.Popen() over os.system() over os.popen()
Understand and probably use text=True, aka universal_newlines=True.
Understand the meaning of shell=True or shell=False and how it changes quoting and the availability of shell conveniences.
Understand differences between sh and Bash
Understand how a subprocess is separate from its parent, and generally cannot change the parent.
Avoid running the Python interpreter as a subprocess of Python.
These topics are covered in some more detail below.
Prefer subprocess.run() or subprocess.check_call()
The subprocess.Popen() function is a low-level workhorse but it is tricky to use correctly and you end up copy/pasting multiple lines of code ... which conveniently already exist in the standard library as a set of higher-level wrapper functions for various purposes, which are presented in more detail in the following.
Here's a paragraph from the documentation:
The recommended approach to invoking subprocesses is to use the run() function for all use cases it can handle. For more advanced use cases, the underlying Popen interface can be used directly.
Unfortunately, the availability of these wrapper functions differs between Python versions.
subprocess.run() was officially introduced in Python 3.5. It is meant to replace all of the following.
subprocess.check_output() was introduced in Python 2.7 / 3.1. It is basically equivalent to subprocess.run(..., check=True, stdout=subprocess.PIPE).stdout
subprocess.check_call() was introduced in Python 2.5. It is basically equivalent to subprocess.run(..., check=True)
subprocess.call() was introduced in Python 2.4 in the original subprocess module (PEP-324). It is basically equivalent to subprocess.run(...).returncode
High-level API vs subprocess.Popen()
The refactored and extended subprocess.run() is more logical and more versatile than the older legacy functions it replaces. It returns a CompletedProcess object which has various methods which allow you to retrieve the exit status, the standard output, and a few other results and status indicators from the finished subprocess.
subprocess.run() is the way to go if you simply need a program to run and return control to Python. For more involved scenarios (background processes, perhaps with interactive I/O with the Python parent program) you still need to use subprocess.Popen() and take care of all the plumbing yourself. This requires a fairly intricate understanding of all the moving parts and should not be undertaken lightly. The simpler Popen object represents the (possibly still-running) process which needs to be managed from your code for the remainder of the lifetime of the subprocess.
It should perhaps be emphasized that just subprocess.Popen() merely creates a process. If you leave it at that, you have a subprocess running concurrently alongside with Python, so a "background" process. If it doesn't need to do input or output or otherwise coordinate with you, it can do useful work in parallel with your Python program.
Avoid os.system() and os.popen()
Since time eternal (well, since Python 2.5) the os module documentation has contained the recommendation to prefer subprocess over os.system():
The subprocess module provides more powerful facilities for spawning new processes and retrieving their results; using that module is preferable to using this function.
The problems with system() are that it's obviously system-dependent and doesn't offer ways to interact with the subprocess. It simply runs, with standard output and standard error outside of Python's reach. The only information Python receives back is the exit status of the command (zero means success, though the meaning of non-zero values is also somewhat system-dependent).
PEP-324 (which was already mentioned above) contains a more detailed rationale for why os.system is problematic and how subprocess attempts to solve those issues.
os.popen() used to be even more strongly discouraged:
Deprecated since version 2.6: This function is obsolete. Use the subprocess module.
However, since sometime in Python 3, it has been reimplemented to simply use subprocess, and redirects to the subprocess.Popen() documentation for details.
Understand and usually use check=True
You'll also notice that subprocess.call() has many of the same limitations as os.system(). In regular use, you should generally check whether the process finished successfully, which subprocess.check_call() and subprocess.check_output() do (where the latter also returns the standard output of the finished subprocess). Similarly, you should usually use check=True with subprocess.run() unless you specifically need to allow the subprocess to return an error status.
In practice, with check=True or subprocess.check_*, Python will throw a CalledProcessError exception if the subprocess returns a nonzero exit status.
A common error with subprocess.run() is to omit check=True and be surprised when downstream code fails if the subprocess failed.
On the other hand, a common problem with check_call() and check_output() was that users who blindly used these functions were surprised when the exception was raised e.g. when grep did not find a match. (You should probably replace grep with native Python code anyway, as outlined below.)
All things counted, you need to understand how shell commands return an exit code, and under what conditions they will return a non-zero (error) exit code, and make a conscious decision how exactly it should be handled.
Understand and probably use text=True aka universal_newlines=True
Since Python 3, strings internal to Python are Unicode strings. But there is no guarantee that a subprocess generates Unicode output, or strings at all.
(If the differences are not immediately obvious, Ned Batchelder's Pragmatic Unicode is recommended, if not outright obligatory, reading. There is a 36-minute video presentation behind the link if you prefer, though reading the page yourself will probably take significantly less time.)
Deep down, Python has to fetch a bytes buffer and interpret it somehow. If it contains a blob of binary data, it shouldn't be decoded into a Unicode string, because that's error-prone and bug-inducing behavior - precisely the sort of pesky behavior which riddled many Python 2 scripts, before there was a way to properly distinguish between encoded text and binary data.
With text=True, you tell Python that you, in fact, expect back textual data in the system's default encoding, and that it should be decoded into a Python (Unicode) string to the best of Python's ability (usually UTF-8 on any moderately up to date system, except perhaps Windows?)
If that's not what you request back, Python will just give you bytes strings in the stdout and stderr strings. Maybe at some later point you do know that they were text strings after all, and you know their encoding. Then, you can decode them.
normal = subprocess.run([external, arg],
stdout=subprocess.PIPE, stderr=subprocess.PIPE,
check=True,
text=True)
print(normal.stdout)
convoluted = subprocess.run([external, arg],
stdout=subprocess.PIPE, stderr=subprocess.PIPE,
check=True)
# You have to know (or guess) the encoding
print(convoluted.stdout.decode('utf-8'))
Python 3.7 introduced the shorter and more descriptive and understandable alias text for the keyword argument which was previously somewhat misleadingly called universal_newlines.
Understand shell=True vs shell=False
With shell=True you pass a single string to your shell, and the shell takes it from there.
With shell=False you pass a list of arguments to the OS, bypassing the shell.
When you don't have a shell, you save a process and get rid of a fairly substantial amount of hidden complexity, which may or may not harbor bugs or even security problems.
On the other hand, when you don't have a shell, you don't have redirection, wildcard expansion, job control, and a large number of other shell features.
A common mistake is to use shell=True and then still pass Python a list of tokens, or vice versa. This happens to work in some cases, but is really ill-defined and could break in interesting ways.
# XXX AVOID THIS BUG
buggy = subprocess.run('dig +short stackoverflow.com')
# XXX AVOID THIS BUG TOO
broken = subprocess.run(['dig', '+short', 'stackoverflow.com'],
shell=True)
# XXX DEFINITELY AVOID THIS
pathological = subprocess.run(['dig +short stackoverflow.com'],
shell=True)
correct = subprocess.run(['dig', '+short', 'stackoverflow.com'],
# Probably don't forget these, too
check=True, text=True)
# XXX Probably better avoid shell=True
# but this is nominally correct
fixed_but_fugly = subprocess.run('dig +short stackoverflow.com',
shell=True,
# Probably don't forget these, too
check=True, text=True)
The common retort "but it works for me" is not a useful rebuttal unless you understand exactly under what circumstances it could stop working.
To briefly recap, correct usage looks like
subprocess.run("string for 'the shell' to parse", shell=True)
# or
subprocess.run(["list", "of", "tokenized strings"]) # shell=False
If you want to avoid the shell but are too lazy or unsure of how to parse a string into a list of tokens, notice that shlex.split() can do this for you.
subprocess.run(shlex.split("no string for 'the shell' to parse")) # shell=False
# equivalent to
# subprocess.run(["no", "string", "for", "the shell", "to", "parse"])
The regular split() will not work here, because it doesn't preserve quoting. In the example above, notice how "the shell" is a single string.
Refactoring Example
Very often, the features of the shell can be replaced with native Python code. Simple Awk or sed scripts should probably just be translated to Python instead.
To partially illustrate this, here is a typical but slightly silly example which involves many shell features.
cmd = '''while read -r x;
do ping -c 3 "$x" | grep 'min/avg/max'
done <hosts.txt'''
# Trivial but horrible
results = subprocess.run(
cmd, shell=True, universal_newlines=True, check=True)
print(results.stdout)
# Reimplement with shell=False
with open('hosts.txt') as hosts:
for host in hosts:
host = host.rstrip('\n') # drop newline
ping = subprocess.run(
['ping', '-c', '3', host],
text=True,
stdout=subprocess.PIPE,
check=True)
for line in ping.stdout.split('\n'):
if 'min/avg/max' in line:
print('{}: {}'.format(host, line))
Some things to note here:
With shell=False you don't need the quoting that the shell requires around strings. Putting quotes anyway is probably an error.
It often makes sense to run as little code as possible in a subprocess. This gives you more control over execution from within your Python code.
Having said that, complex shell pipelines are tedious and sometimes challenging to reimplement in Python.
The refactored code also illustrates just how much the shell really does for you with a very terse syntax -- for better or for worse. Python says explicit is better than implicit but the Python code is rather verbose and arguably looks more complex than this really is. On the other hand, it offers a number of points where you can grab control in the middle of something else, as trivially exemplified by the enhancement that we can easily include the host name along with the shell command output. (This is by no means challenging to do in the shell, either, but at the expense of yet another diversion and perhaps another process.)
Common Shell Constructs
For completeness, here are brief explanations of some of these shell features, and some notes on how they can perhaps be replaced with native Python facilities.
Globbing aka wildcard expansion can be replaced with glob.glob() or very often with simple Python string comparisons like for file in os.listdir('.'): if not file.endswith('.png'): continue. Bash has various other expansion facilities like .{png,jpg} brace expansion and {1..100} as well as tilde expansion (~ expands to your home directory, and more generally ~account to the home directory of another user)
Shell variables like $SHELL or $my_exported_var can sometimes simply be replaced with Python variables. Exported shell variables are available as e.g. os.environ['SHELL'] (the meaning of export is to make the variable available to subprocesses -- a variable which is not available to subprocesses will obviously not be available to Python running as a subprocess of the shell, or vice versa. The env= keyword argument to subprocess methods allows you to define the environment of the subprocess as a dictionary, so that's one way to make a Python variable visible to a subprocess). With shell=False you will need to understand how to remove any quotes; for example, cd "$HOME" is equivalent to os.chdir(os.environ['HOME']) without quotes around the directory name. (Very often cd is not useful or necessary anyway, and many beginners omit the double quotes around the variable and get away with it until one day ...)
Redirection allows you to read from a file as your standard input, and write your standard output to a file. grep 'foo' <inputfile >outputfile opens outputfile for writing and inputfile for reading, and passes its contents as standard input to grep, whose standard output then lands in outputfile. This is not generally hard to replace with native Python code.
Pipelines are a form of redirection. echo foo | nl runs two subprocesses, where the standard output of echo is the standard input of nl (on the OS level, in Unix-like systems, this is a single file handle). If you cannot replace one or both ends of the pipeline with native Python code, perhaps think about using a shell after all, especially if the pipeline has more than two or three processes (though look at the pipes module in the Python standard library or a number of more modern and versatile third-party competitors).
Job control lets you interrupt jobs, run them in the background, return them to the foreground, etc. The basic Unix signals to stop and continue a process are of course available from Python, too. But jobs are a higher-level abstraction in the shell which involve process groups etc which you have to understand if you want to do something like this from Python.
Quoting in the shell is potentially confusing until you understand that everything is basically a string. So ls -l / is equivalent to 'ls' '-l' '/' but the quoting around literals is completely optional. Unquoted strings which contain shell metacharacters undergo parameter expansion, whitespace tokenization and wildcard expansion; double quotes prevent whitespace tokenization and wildcard expansion but allow parameter expansions (variable substitution, command substitution, and backslash processing). This is simple in theory but can get bewildering, especially when there are several layers of interpretation (a remote shell command, for example).
Understand differences between sh and Bash
subprocess runs your shell commands with /bin/sh unless you specifically request otherwise (except of course on Windows, where it uses the value of the COMSPEC variable). This means that various Bash-only features like arrays, [[ etc are not available.
If you need to use Bash-only syntax, you can
pass in the path to the shell as executable='/bin/bash' (where of course if your Bash is installed somewhere else, you need to adjust the path).
subprocess.run('''
# This for loop syntax is Bash only
for((i=1;i<=$#;i++)); do
# Arrays are Bash-only
array[i]+=123
done''',
shell=True, check=True,
executable='/bin/bash')
A subprocess is separate from its parent, and cannot change it
A somewhat common mistake is doing something like
subprocess.run('cd /tmp', shell=True)
subprocess.run('pwd', shell=True) # Oops, doesn't print /tmp
The same thing will happen if the first subprocess tries to set an environment variable, which of course will have disappeared when you run another subprocess, etc.
A child process runs completely separate from Python, and when it finishes, Python has no idea what it did (apart from the vague indicators that it can infer from the exit status and output from the child process). A child generally cannot change the parent's environment; it cannot set a variable, change the working directory, or, in so many words, communicate with its parent without cooperation from the parent.
The immediate fix in this particular case is to run both commands in a single subprocess;
subprocess.run('cd /tmp; pwd', shell=True)
though obviously this particular use case isn't very useful; instead, use the cwd keyword argument, or simply os.chdir() before running the subprocess. Similarly, for setting a variable, you can manipulate the environment of the current process (and thus also its children) via
os.environ['foo'] = 'bar'
or pass an environment setting to a child process with
subprocess.run('echo "$foo"', shell=True, env={'foo': 'bar'})
(not to mention the obvious refactoring subprocess.run(['echo', 'bar']); but echo is a poor example of something to run in a subprocess in the first place, of course).
Don't run Python from Python
This is slightly dubious advice; there are certainly situations where it does make sense or is even an absolute requirement to run the Python interpreter as a subprocess from a Python script. But very frequently, the correct approach is simply to import the other Python module into your calling script and call its functions directly.
If the other Python script is under your control, and it isn't a module, consider turning it into one. (This answer is too long already so I will not delve into details here.)
If you need parallelism, you can run Python functions in subprocesses with the multiprocessing module. There is also threading which runs multiple tasks in a single process (which is more lightweight and gives you more control, but also more constrained in that threads within a process are tightly coupled, and bound to a single GIL.)
Call it with subprocess
import subprocess
subprocess.Popen("cwm --rdf test.rdf --ntriples > test.nt")
The error you are getting seems to be because there is no swap module on the server, you should install swap on the server then run the script again
It is possible you use the bash program, with the parameter -c for execute the commands:
bashCommand = "cwm --rdf test.rdf --ntriples > test.nt"
output = subprocess.check_output(['bash','-c', bashCommand])
You can use subprocess, but I always felt that it was not a 'Pythonic' way of doing it. So I created Sultan (shameless plug) that makes it easy to run command line functions.
https://github.com/aeroxis/sultan
Also you can use 'os.popen'.
Example:
import os
command = os.popen('ls -al')
print(command.read())
print(command.close())
Output:
total 16
drwxr-xr-x 2 root root 4096 ago 13 21:53 .
drwxr-xr-x 4 root root 4096 ago 13 01:50 ..
-rw-r--r-- 1 root root 1278 ago 13 21:12 bot.py
-rw-r--r-- 1 root root 77 ago 13 21:53 test.py
None
According to the error you are missing a package named swap on the server. This /usr/bin/cwm requires it. If you're on Ubuntu/Debian, install python-swap using aptitude.
To run the command without a shell, pass the command as a list and implement the redirection in Python using [subprocess]:
#!/usr/bin/env python
import subprocess
with open('test.nt', 'wb', 0) as file:
subprocess.check_call("cwm --rdf test.rdf --ntriples".split(),
stdout=file)
Note: no > test.nt at the end. stdout=file implements the redirection.
To run the command using the shell in Python, pass the command as a string and enable shell=True:
#!/usr/bin/env python
import subprocess
subprocess.check_call("cwm --rdf test.rdf --ntriples > test.nt",
shell=True)
Here's the shell is responsible for the output redirection (> test.nt is in the command).
To run a bash command that uses bashisms, specify the bash executable explicitly e.g., to emulate bash process substitution:
#!/usr/bin/env python
import subprocess
subprocess.check_call('program <(command) <(another-command)',
shell=True, executable='/bin/bash')
copy paste this:
def run_bash_command(cmd: str) -> Any:
import subprocess
process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE)
output, error = process.communicate()
if error:
raise Exception(error)
else:
return output
subprocess.Popen() is prefered over os.system() as it offers more control and visibility. However, If you find subprocess.Popen() too verbose or complex, peasyshell is a small wrapper I wrote above it, which makes it easy to interact with bash from Python.
https://github.com/davidohana/peasyshell
The pythonic way of doing this is using subprocess.Popen
subprocess.Popen takes a list where the first element is the command to be run followed by any command line arguments.
As an example:
import subprocess
args = ['echo', 'Hello!']
subprocess.Popen(args) // same as running `echo Hello!` on cmd line
args2 = ['echo', '-v', '"Hello Again"']
subprocess.Popen(args2) // same as running 'echo -v "Hello Again!"` on cmd line
Good Day, this should be fairly straight forward, but my googling and experimenting is not working.
I have a scraping script in python that uses Selenium/geckodriver/Firefox that runs on an Ubuntu 18 server. Sometimes it does not close properly and Selenium will crash midscript but it leaves many Web Content processes open. If not closed they use up all the memory and then selenium can no longer open and the script fails.
If I run from the command line: pkill 'Web Content' it will kill those processes and free up the memory.
In my python script I use the subprocess module to try and automate this upon Selenium crashing. I've tried a number of options including:
subprocess.call("pkill 'Web Content'".split())
subprocess.call("pkill 'Web\ Content'".split())
subprocess.call("pkill Web\ Content".split())
subprocess.call("pkill -f Web\ Content".split())
And all of these throw the same error: pkill: only one pattern can be provided
Yet, if I do something like subprocess.call("pkill firefox".split()) the code is able to run without an error.
What must I do to resolve this issue? Thank you.
Manually splitting the command line yourself simplifies the entire question significantly.
subprocess.run(['pkill', 'Web Content'], check=True)
If you genuinely need Python to perform the splitting, shlex.split() implements the rules which you assumed Python's regular split function would obey. It doesn't; it simply splits on the string you supply, with no support for escaping etc.
You have 2 options:
Use subprocess.call("pkill 'Web Content'", shell=True) or
subprocess.call(shlex.split("pkill 'Web Content'"))
Option 1
From the docs:
On POSIX with shell=True, the shell defaults to /bin/sh. If args is a
string, the string specifies the command to execute through the shell.
This means that the string must be formatted exactly as it would be
when typed at the shell prompt.
split() splits Python string around spaces:
>>> "pkill 'Web Content'".split()
['pkill', "'Web", "Content'"]
So subprocess.call("pkill 'Web Content'".split()) supplies two arguments to pkill: "'Web" and "Content'" while it expects only one. That's why error pkill: only one pattern can be provided pops.
Note the subprocess.call signature which is equivalent to subprocess.Popen:
subprocess.Popen(args,..
From the docs:
args should be a sequence of program arguments or else a single string
or path-like object. By default, the program to execute is the first
item in args if args is a sequence.
Also note security considerations while using shell=True
Option 2
If you want to supply the args sequence use shlex.split:
>>> s = "pkill 'Web Content'"
>>> import shlex
>>> args = shlex.split(s)
>>> import subprocess
>>> subprocess.call(args)
shlex.split would split the string s using shell-like syntax.
It's up to you which option to use, note relevant information in this answer:
Understand shell=True vs shell=False With shell=True you pass a single
string to your shell, and the shell takes it from there.
With shell=False you pass a list of arguments to the OS, bypassing the
shell.
When you don't have a shell, you save a process and get rid of a
fairly substantial amount of hidden complexity, which may or may not
harbor bugs or even security problems.
On the other hand, when you don't have a shell, you don't have
redirection, wildcard expansion, job control, and a large number of
other shell features.
import os
import subprocess
proc = subprocess.Popen(['ls','*.bc'], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out,err = proc.communicate()
print out
This script should print all the files with .bc suffix however it returns an empty list. If I do ls *.bc manually in the command line it works. Doing ['ls','test.bc'] inside the script works as well but for some reason the star symbol doesnt work.. Any ideas ?
You need to supply shell=True to execute the command through a shell interpreter.
If you do that however, you can no longer supply a list as the first argument, because the arguments will get quoted then. Instead, specify the raw commandline as you want it to be passed to the shell:
proc = subprocess.Popen('ls *.bc', shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
Expanding the * glob is part of the shell, but by default subprocess does not send your commands via a shell, so the command (first argument, ls) is executed, then a literal * is used as an argument.
This is a good thing, see the warning block in the "Frequently Used Arguments" section, of the subprocess docs. It mainly discusses security implications, but can also helps avoid silly programming errors (as there are no magic shell characters to worry about)
My main complaint with shell=True is it usually implies there is a better way to go about the problem - with your example, you should use the glob module:
import glob
files = glob.glob("*.bc")
print files # ['file1.bc', 'file2.bc']
This will be quicker (no process startup overhead), more reliable and cross platform (not dependent on the platform having an ls command)
Besides doing shell=True, also make sure that your path is not quoted. Otherwise it will not be expanded by shell.
If your path may have special characters, you will have to escape them manually.
I am trying to execute a command inside a Python script:
import subprocess
output_process =
subprocess.Popen("javac -cp C:\Users\MyUsername\Desktop\htmlcleaner-2.2.jar Scrapping_lastfm.java",
shell=True, stdout=subprocess.PIPE)
But I am getting an error package org.htmlcleaner does not exist.
If I run the javac command independently, it executes fine..
My current working directry is C:\Users\MyUsername.
The error is not raised by python but by the java subprocess. Most likely the java machine is not finding some libraries, and that refines the problem to a PATH configuration problem, most likely
the variable CLASSPATH has not been set in the environment. to solve :
import shlex
JAVA_COMMAND=r"javac -cp C:\\Users\\MyUsername\\Desktop\\htmlcleaner-2.2.jar Scrapping_lastfm.java"
cmdline = shlex.split(JAVA_COMMAND)
output_process = subprocess.Popen(cmdline,shell=True, stdout=subprocess.PIPE, env={'CLASSPATH':'/path/to/java/packages'})
Try
output_process = subprocess.Popen(["javac", "-cp",
"C:\Users\MyUsername\Desktop\htmlcleaner-2.2.jar", "Scrapping_lastfm.java"],
shell=True, stdout=subprocess.PIPE, env={'ENVIRONMENTAL': '/variables/here'})
with whatever java-related environmental variables you have when you run javac normally as items in the env dictionary. asgs suggests you need CLASSPATH.
You don't have to split the command up into a list I just did that to make it easier to see the whole thing.
Be aware, that you have to escape the backslash (\) in the string. Your example is fine, however if your username is not actually MyUsername but maybe „nerd“ or any other string forming a valid escape-sequence, the command will fail.
Also make sure that you don't have spaces in the filename (or use the split syntax in the other example).
So you might want to do:
output_process = subprocess.Popen(["javac", "-cp",
"C:\\Users\\MyUsername\\Desktop\\htmlcleaner-2.2.jar", "Scrapping_lastfm.java"],
shell=True, stdout=subprocess.PIPE)