I am introducing the loggers into my project and I would like to ban the print statement usage in it. My intent is to force any future developers to use the loggers and to make sure I replaced all print invocations in project.
So far I managed to restrict print('foo') and print 'foo' like invocations with:
from __future__ import print_function
def print(*args, **kwargs):
raise SyntaxError("Don't use print! Use logger instead.")
But it is still possible to use print without arguments with intent of adding newline but it won't do anything.
Is it possible to do it without interpreter modifications?
EDIT:
I wasn't clear enough I guess from the comments. I just wanted to know if I can prevent the print function for being aliased
print("foo") # raises exception
print "foo" # doesn't work either
print # doesn't raise any exception, but I want it to
foo = print # this shouldn't work either like the one above, but it does
No, you can't prevent print statements from being used in code that doesn't use from __future__ import print_function. print statements are not hooked, they are compiled directly to a set of opcodes and the implementation of those opcodes just write directly to stdout or other file object (when using the >> notation).
You could go the drastic route of requiring a custom codec, but that's no better than requiring that from __future__ import print_function is used.
By the same token, if all code does use from __future__ import print_function, while you can assign a new print function to the __builtin__ module, you can't prevent someone from building their own version (named print or something else) that writes to sys.stdout, or from executing reload(__builtin__). Python is highly dynamic and flexible, I'd not try to lock this down.
The normal path to enforce coding standards is to use a linter, code review and tests. You can install hooks on most version control systems that prevent code from being checked in that doesn't pass a linter, and both pylint and flake8 support custom plugins. You can run a test that configures the logging module to direct all output to a file then raise an exception if anything is written to stdout, etc.
This is the path that Facebook uses (and it is not alone in this approach), where Python code must pass the Facebook flake8 configuration, which includes the flake8-bugbear extension, and code is autoformatted using Black to make it easy for developers to meet those requirements.
Related
I'm a bit experienced without other languages but, novice with Python. I have come across made codes in jupyter notebooks where sys is imported.
I can't see the further use of the sys module in the code. Can someone help me to understand what is the purpose of importing sys?
I do know about the module and it's uses though but can't find a concise reason of why is it used in many code blocks without any further use.
If nothing declared within sys is actually used, then there's no benefit to importing it. There's not a significant amount of cost either.
Sys module is a rather useful module as it allows you to work with your System and those things. Eg:
You can access any command line arguments using sys.argv[1:]
You can see the Path to files.
Version of your Python Interpreter using sys.version
Exit the running code with sys.exit
Mostly you will use it for accessing the Command Line arguments.
I'm a new pythonista bro, I learned to import it whenever I want to exit the program with a nice exit text in red
import sys
name = input("What's your name? ")
if name == "Vedant":
print(f"Hello There {name}.")
else:
sys.exit(f"You're not {name}!")
The sys includes "functions + variable " to help you control and change the python environment #runtime.
Some examples of this control includes:
1- using other sources data as input via using:
sys.stdin
2- using data in the other resources via using:
sys.stdout
3- writing errors when an exception happens, automatically in :
sys.stderr
4- exit from the program by printing a message like:
sys.exit("Finish with the calculations.")
5- The built-in variable to list the directories which the interpreter will looking for functions in them:
sys.pasth
6- Use a function to realize the number of bytes in anonymous datatype via:
sys.getsizeof(1)
sys.getsizeof(3.8)
I'm trying to test a Python script (2.7) where I work with the standar input (readed with raw_input() and writed with a simple print) but I don't find how do this and I'm sure that this issue is very simple.
This is a very very very resume code of my script:
def example():
number = raw_input()
print number
if __name__ == '__main__':
example()
I want to write a unittest test to check this, but I don't find how. I've trying with StringIO and other things but I don't find the solution to do this really simple.
Somebody have a idea?
PD: Of course in the real script I use data blocks with several lines and other kind of data.
Thank you so much.
EDIT:
Thank you so much for the first really specific answer, it works perfectly, only I've had a little problem importing StringIO, because I was doing import StringIO and I needed to import like from StringIO import StringIO (I don't understand really why), but be that as It may, it works.
But I I've found another problem using this way, in my project I need test a scripts with this way (that work perfectly thanks to your support) but I want do this:
I have a file with a lot of test to pass over a script, so I open the file and read blocks of info with their result blocks and I would like to do that the code will be able to process a block checking their result and do the same with other and another...
Something like this:
class Test(unittest.TestCase):
...
#open file and process saving data like datablocks and results
...
allTest = True
for test in tests:
stub_stdin(self, test.dataBlock)
stub_stdouts(self)
runScrip()
if sys.stdout.getvalue() != test.expectResult:
allTest = False
self.assertEqual(allTest, True)
I know that maybe unittest doesn't has sense now, but you can do a idea about I want. So, this way fails and I don't know why.
Typical techniques involve mocking the standard sys.stdin and sys.stdout with your desired items. If you do not care for Python 3 compatibility you can just use the StringIO module, however if you want forward thinking and is willing to restrict to Python 2.7 and 3.3+, supporting for this both Python 2 and 3 in this way becomes possible without too much work through the io module (but requires a bit of modification, but put this thought on hold for now).
Assuming you already have a unittest.TestCase going, you can create a utility function (or method in the same class) that will replace sys.stdin/sys.stdout as outlined. First the imports:
import sys
import io
import unittest
In one of my recent projects I've done this for stdin, where it take a str for the inputs that the user (or another program through pipes) will enter into yours as stdin:
def stub_stdin(testcase_inst, inputs):
stdin = sys.stdin
def cleanup():
sys.stdin = stdin
testcase_inst.addCleanup(cleanup)
sys.stdin = StringIO(inputs)
As for stdout and stderr:
def stub_stdouts(testcase_inst):
stderr = sys.stderr
stdout = sys.stdout
def cleanup():
sys.stderr = stderr
sys.stdout = stdout
testcase_inst.addCleanup(cleanup)
sys.stderr = StringIO()
sys.stdout = StringIO()
Note that in both cases, it accepts a testcase instance, and calls its addCleanup method that adds the cleanup function call that will reset them back to where they were when the duration of a test method is concluded. The effect is that for the duration from when this was invoked in the test case until the end, sys.stdout and friends will be replaced with the io.StringIO version, meaning you can check its value easily, and don't have to worry about leaving a mess behind.
Better to show this as an example. To use this, you can simply create a test case like so:
class ExampleTestCase(unittest.TestCase):
def test_example(self):
stub_stdin(self, '42')
stub_stdouts(self)
example()
self.assertEqual(sys.stdout.getvalue(), '42\n')
Now, in Python 2, this test will only pass if the StringIO class is from the StringIO module, and in Python 3 no such module exists. What you can do is use the version from the io module with a modification that makes it slightly more lenient in terms of what input it accepts, so that the unicode encoding/decoding will be done automatically rather than triggering an exception (such as print statements in Python 2 will not work nicely without the following). I typically do this for cross compatibility between Python 2 and 3:
class StringIO(io.StringIO):
"""
A "safely" wrapped version
"""
def __init__(self, value=''):
value = value.encode('utf8', 'backslashreplace').decode('utf8')
io.StringIO.__init__(self, value)
def write(self, msg):
io.StringIO.write(self, msg.encode(
'utf8', 'backslashreplace').decode('utf8'))
Now plug your example function plus every code fragment in this answer into one file, you will get your self contained unittest that works in both Python 2 and 3 (although you need to call print as a function in Python 3) for doing testing against stdio.
One more note: you can always put the stub_ function calls in the setUp method of the TestCase if every single test method requires that.
Of course, if you want to use various mocks related libraries out there to stub out stdin/stdout, you are free to do so, but this way relies on no external dependencies if this is your goal.
For your second issue, test cases have to be written in a certain way, where they must be encapsulated within a method and not at the class level, your original example will fail. However you might want to do something like this:
class Test(unittest.TestCase):
def helper(self, data, answer, runner):
stub_stdin(self, data)
stub_stdouts(self)
runner()
self.assertEqual(sys.stdout.getvalue(), answer)
self.doCleanups() # optional, see comments below
def test_various_inputs(self):
data_and_answers = [
('hello', 'HELLOhello'),
('goodbye', 'GOODBYEgoodbye'),
]
runScript = upperlower # the function I want to test
for data, answer in data_and_answers:
self.helper(data, answer, runScript)
The reason why you might want to call doCleanups is to prevent the cleanup stack from getting as deep as all the data_and_answers pairs are there, but that will pop everything off the cleanup stack so if you had any other things that need to be cleaned up at the end this might end up being problematic - you are free to leave that there as all of the stdio related objects will be restored at the end in the same order, so the real one will always be there. Now the function I wanted to test:
def upperlower():
raw = raw_input()
print (raw.upper() + raw),
So yes, a bit of explanation for what I did might help: remember within a TestCase class, the framework relies strictly on the instance's assertEqual and friends for it to function. So to ensure testing being done at the right level you really want to call those asserts all the time so that helpful error messages will be shown at the moment the error occurred with the inputs/answers that didn't quite show up right, rather than until the very end like what you did with the for loop (that will tell you something was wrong, but not exactly where out of the hundreds and now you are mad). Also the helper method - you can call it anything you want, as long as it doesn't start with test because then the framework will try to run it as one and it will fail terribly. So just follow this convention and you can basically have templates within your test case to run your test with - you can then use it in a loop with a bunch of inputs/outputs like what I did.
As for your other question:
only I've had a little problem importing StringIO, because I was doing import StringIO and I needed to import like from StringIO import StringIO (I don't understand really why), but be that as It may, it works.
Well, if you look at my original code I did show you how did import io and then overrode the io.StringIO class by defining class StringIO(io.StringIO). However it works for you because you are doing this strictly from Python 2, whereas I do try to target my answers to Python 3 whenever possible given that Python 2 will (probably definitely this time) not be supported in less than 5 years. Think of the future users that might be reading this post who had similar problem as you. Anyway, yes, the original from StringIO import StringIO works, as that's the StringIO class from the StringIO module. Though from cStringIO import StringIO should work as that imports the C version of the StringIO module. It works because they all offer close enough interfaces, and so they will basically work as intended (until of course you try to run this under Python 3).
Again, putting all this together along with my code should result in a self-contained working test script. Do remember to look at documentation and follow the form of the code, and not invent your own syntax and hoping things to work (and as for exactly why your code didn't work, because the "test" code was defined at where the class was being constructed, so all of that was executed while Python was importing your module, and since none of the things that are needed for the test to run are even available (namely the class itself doesn't even exist yet), the whole thing just dies in fits of twitching agony). Asking questions here help too, even though the issue you face is something really common, not having a quick and simple name to search for your exact problem does make it difficult to figure out where you went wrong, I supposed? :) Anyway good luck, and good on you for taking the effort to test your code.
There are other methods, but given that the other questions/answers I looked at here at SO doesn't seem to help, I hope this one this. Other ones for reference:
How to supply stdin, files and environment variable inputs to Python unit tests?
python mocking raw input in unittests
Naturally, it bares repeating that all of this can be done using unittest.mock available in Python 3.3+ or the original/rolling backport version on pypi, but given that those libraries hides some of the intricacies on what actually happens, they may end up hiding some of the details on what actually happens (or need to happen) or how the redirection actually happens. If you want, you can read up on unittest.mock.patch and go down slightly to the StringIO patching sys.stdout section.
I'm running lint as follows:
$ python -m pylint.lint m2test.py
with this code:
import M2Crypto
def f():
M2Crypto.RSA.new_pub_key("").as_pem(cipher=None).split("\n")
The lint output ends with:
Exception AttributeError: '_shutdown' in <module 'threading' from '/usr/lib/python2.7/site-packages/M2Crypto-0.21.1-py2.7-linux-x86_64.egg/M2Crypto/threading.pyc'> ignored
This code works fine when run (the above is actually a minimal test case; but the full version does work). The exception is ignored, but Bitten considers this a failure, so stops on this step.
I've tried adding 'M2Crypto.threading.init()'/'M2Crypto.threading.cleanup()' around the definition of the function, but that didn't fix the problem.
How can I prevent this problem from occurring?
I'm using M2Crypto 0.21.1, pylint 0.24 and Python 2.7 (also tried 2.7.2) on Debian Lenny x86_64.
The exception that you are seeing is caused by a bug in the astng package (presumably “Abstract Syntax Tree, Next Generation”?) which is a toolkit on which pylint depends, written by the same people. I should note in passing that I always encourage people to use pyflakes instead of pylint when possible, because it is quick, simple, fast, and predictable, whereas pylint tries to do several kinds of deep magic that are not only slow but that can get it into exactly this kind of trouble. :)
Here are the two packages on PyPI:
http://pypi.python.org/pypi/pylint
http://pypi.python.org/pypi/astng
And note that this problem had to be, necessarily, a bug in pylint and not in your code, because pylint does not run your code in order to produce its report — imagine the havoc that could be wreaked if it did (since code being linted might delete files, etcetera)! Since your code does not get run, no amount of caution, like protecting your call with threading init() or cleanup() functions, could possibly have prevented this error — unless the code snippets happened, for other reasons, to alter the behavior we are about to investigate.
So, on to your actual exception.
I had never actually heard of _shutdown before! A quick search of the Python standard library showed its definition in threading.py but not a call of the function from anywhere; only by searching the Python C source code did I discover where in pythonrun.c, during interpreter shutdown, the function is actually called:
static void
wait_for_thread_shutdown(void)
{
...
PyObject *threading = PyMapping_GetItemString(tstate->interp->modules,
"threading");
if (threading == NULL) {
/* threading not imported */
PyErr_Clear();
return;
}
result = PyObject_CallMethod(threading, "_shutdown", "");
if (result == NULL) {
PyErr_WriteUnraisable(threading);
}
...
}
Apparently it is some sort of cleanup function that the threading Standard Library module requires, and they have special-cased the Python interpreter itself to make sure that it gets called.
As you can see from the code above, Python quietly and without complaint handles the case where the threading module never gets imported during a program's run. But if threading does get imported, and still exists at shutdown time, then the interpreter looks inside for a _shutdown function and goes so far as to print an error message — and then return a non-zero exit status, the cause of your problems — if it cannot call it.
So we have to discover why the threading module exists but has no _shutdown method at the moment when pylint is done examining your program and Python is exiting. Some instrumention is called for. Can we print out what the module looks like as pylint exits? We can! The pylint/lint.py module, in its last few lines, runs its “main program” by instantiating a Run class it has defined:
if __name__ == '__main__':
Run(sys.argv[1:])
So I opened lint.py in my editor — one of the magnificent things about having each little project installed in a Python Virual Environment is that I can jump in and edit third-party code for quick experiments — and added the following print statement down at the bottom of the Run class's __init__() method:
sys.path.pop(0)
print "*****", sys.modules['threading'].__file__ # added by me!
if exit:
sys.exit(self.linter.msg_status)
I re-ran the command:
python -m pylint.lint m2test.py
And out came the __file__ string of the threading module:
***** /home/brandon/venv/lib/python2.7/site-packages/M2Crypto/threading.pyc
Well, look at that.
This is the problem!
According to this path, there actually exists an M2Crypto/threading.py module that, under all normal circumstances, should just be called M2Crypto.threading, and therefore sit in the sys.modules dictionary under the name:
sys.modules['M2Crypto.threading']
But somehow that file is also getting loaded as the main Python threading module, shadowing the official threading module that sits in the Standard Library. Because of this, the Python exit logic is quite correctly complaining that the Standard Library _shutdown() function is missing.
How could this happen? Top-level modules can only appear in paths that are listed explicitly in sys.path, not in sub-directories beneath them. This leads to a new question: is there any point during the pylint run that the …/M2Crypto/ directory itself is getting put on sys.path as though it contained top-level modules? Let's see!
We need more instrumentation: we need to have Python tell us the moment that a directory with M2Crypto in the name appears in sys.path. It will really slow things down, but let's add a trace function to pylint's __init__.py — because that is the first module that gets imported when you run -m pylint.lint — that will write an output file telling us, for every line of code executed, whether sys.path has any bad values in it:
def install_tracer():
import sys
output = open('mytracer.out', 'w')
def mytracer(frame, event, arg):
broken = any(p.endswith('M2Crypto') for p in sys.path)
output.write('{} {}:{} {}\n'.format(
broken, frame.f_code.co_filename, frame.f_lineno, event))
return mytracer
sys.settrace(mytracer)
install_tracer()
del install_tracer
Note how careful I am here: I define only one name in the module's namespace, and then carefully delete it to clean up after myself before I let pylint continue loading! And all of the resources that the trace function itself needs — namely, the sys module and the output open file — are available in the install_tracer() closure so that, from the outside, pylint looks exactly the same as always. Just in case anyone tries to introspect it, like pylint might!
This generates a file mytracer.out of about 800k lines, that each look something like this:
False /home/brandon/venv/lib/python2.7/posixpath.py:118 call
The False says that sys.path looks clean, the filename and line number are the line of code being executed, and call indicates what stage of execution the interpreter is in.
So does sys.path ever get poisoned? Let's look at just the first True or False on each line, and see how many successive lines start with each value:
$ awk '{print$1}' mytracer.out | uniq -c
607997 False
3173 True
4558 False
33217 True
4304 False
41699 True
2953 False
110503 True
52575 False
Wow! That's a problem! For runs of several thousand lines at a time, our test case is True, which means that the interpreter is running with …/M2Crypto/ — or some variant of a pathname with M2Crypto in it — on the path, where it should not be; only the directory that contains …/M2Crypto should ever be on the path. Looking for the first False to True transition in the file, I see this:
False /home/brandon/venv/lib/python2.7/site-packages/logilab/astng/builder.py:132 line
False /home/brandon/venv/lib/python2.7/posixpath.py:118 call
...
False /home/brandon/venv/lib/python2.7/posixpath.py:124 line
False /home/brandon/venv/lib/python2.7/posixpath.py:124 return
True /home/brandon/venv/lib/python2.7/site-packages/logilab/astng/builder.py:133 line
And looking at lines 132 and 133 in the builder.py file reveals our culprit:
130 # build astng representation
131 try:
132 sys.path.insert(0, dirname(path)) # XXX (syt) iirk
133 node = self.string_build(data, modname, path)
134 finally:
135 sys.path.pop(0)
Note the comment, which is part of the original code, not an addition of my own! Obviously, XXX (syt) iirk is an exclamation in this programmer's strange native language for the phrase, “put this module's parent directory on sys.path so that pylint will break mysteriously every time someone forces pylint to introspect a package with a threading sub-module.” It is, obviously, a very compact native language. :)
If you adjust the tracing module to watch sys.modules for the actual import of threading — an exercise I will leave to the reader — you will see that it happens when SocketServer, which is imported by some other Standard Library module during the analysis, in turn tries to innocently import threading.
So let us review what is happening:
pylint is dangerous magic.
As part of its magic, if it sees you import foo, then it runs off trying to find foo.py on disk, to parse it, and to predict whether you are loading valid or invalid names from its namespace.
[See my comment, below.] Because you call .split() on the return value of RSA.as_pem(), pylint tries to introspect the as_pem() method, which in turn uses the M2Crypto.BIO module, which in turn makes calls that induce pylint to import threading.
As part of loading any module foo.py, pylint throws the directory containing foo.py on sys.path, even if that directory is inside a package, and therefore gives modules in that directory the privilege of shadowing Standard Library modules of the same name during its analysis.
When Python exits, it is upset that the M2Crypto.threading library is sitting where threading belongs, because it wants to run the _shutdown() method of threading.
You should report this as a bug to the pylint / astng folks at logilab.org. Tell them I sent you.
If you decide to keep using pylint after it has done this to you, then there seem to be two solutions in this case: either don't inspect code that calls M2Crypto, or import threading during the pylint import process — by sticking import threading into the pylint/__init__.py, for example — so that the module gets the chance to grab the sys.modules['threading'] slot before pylint gets all excited and tries to let M2Crypto/threading.py grab the slot instead.
In conclusion, I think the author of astng says it best: XXX (syt) iirk. Indeed.
Many thanks to Brandon Craig Rhodes for having tracing this down and for such a detailed post.
I've removed the offending line from astng, code available from the hg repository until logilab-astng 0.23.0 is out. And I can confirm this fixes the OP's pb.
This looks more like a hack but I think it works. Copying the result of "as_pem()" and splitting it.
import M2Crypto
def f():
M2Crypto.RSA.new_pub_key("").as_pem(cipher=None)[:].split("\n")
I'm using Python 2.6.7, M2Crypto 0.21.1, pylint 0.23
I was unable to reproduce (pylint 0.24 and M2Crypto 0.21.1 on Ubuntu 11.04 64bit) but two suggestions:
Explicitly initialize threading:
import M2Crypto
def f():
M2Crypto.threading.init()
M2Crypto.RSA.new_pub_key("").as_pem(cipher=None).split("\n")
M2Crypto.threading.cleanup()
Or recompile without threading:
m2crypto = Extension(name = 'M2Crypto.__m2crypto',
sources = ['SWIG/_m2crypto.i'],
extra_compile_args = ['-DTHREADING'],
#extra_link_args = ['-Wl,-search_paths_first'], # Uncomment to build Universal Mac binaries
)
I have been coding a lot in Python of late. And I have been working with data that I haven't worked with before, using formulae never seen before and dealing with huge files. All this made me write a lot of print statements to verify if it's all going right and identify the points of failure. But, generally, outputting so much information is not a good practice. How do I use the print statements only when I want to debug and let them be skipped when I don't want them to be printed?
The logging module has everything you could want. It may seem excessive at first, but only use the parts you need. I'd recommend using logging.basicConfig to toggle the logging level to stderr and the simple log methods, debug, info, warning, error and critical.
import logging, sys
logging.basicConfig(stream=sys.stderr, level=logging.DEBUG)
logging.debug('A debug message!')
logging.info('We processed %d records', len(processed_records))
A simple way to do this is to call a logging function:
DEBUG = True
def log(s):
if DEBUG:
print s
log("hello world")
Then you can change the value of DEBUG and run your code with or without logging.
The standard logging module has a more elaborate mechanism for this.
Use the logging built-in library module instead of printing.
You create a Logger object (say logger), and then after that, whenever you insert a debug print, you just put:
logger.debug("Some string")
You can use logger.setLevel at the start of the program to set the output level. If you set it to DEBUG, it will print all the debugs. Set it to INFO or higher and immediately all of the debugs will disappear.
You can also use it to log more serious things, at different levels (INFO, WARNING and ERROR).
First off, I will second the nomination of python's logging framework. Be a little careful about how you use it, however. Specifically: let the logging framework expand your variables, don't do it yourself. For instance, instead of:
logging.debug("datastructure: %r" % complex_dict_structure)
make sure you do:
logging.debug("datastructure: %r", complex_dict_structure)
because while they look similar, the first version incurs the repr() cost even if it's disabled. The second version avoid this. Similarly, if you roll your own, I'd suggest something like:
def debug_stdout(sfunc):
print(sfunc())
debug = debug_stdout
called via:
debug(lambda: "datastructure: %r" % complex_dict_structure)
which will, again, avoid the overhead if you disable it by doing:
def debug_noop(*args, **kwargs):
pass
debug = debug_noop
The overhead of computing those strings probably doesn't matter unless they're either 1) expensive to compute or 2) the debug statement is in the middle of, say, an n^3 loop or something. Not that I would know anything about that.
I don't know about others, but I was used to define a "global constant" (DEBUG) and then a global function (debug(msg)) that would print msg only if DEBUG == True.
Then I write my debug statements like:
debug('My value: %d' % value)
...then I pick up unit testing and never did this again! :)
A better way to debug the code is, by using module clrprint
It prints a color full output only when pass parameter debug=True
from clrprint import *
clrprint('ERROR:', information,clr=['r','y'], debug=True)
I'm using the new print from Python 3.x and I observed that the following code does not compile due to the end=' '.
from __future__ import print_function
import sys
if sys.hexversion < 0x02060000:
raise Exception("py too old")
...
print("x",end=" ") # fails to compile with py24
How can I continue using the new syntax but make the script fails nicely? Is it mandatory to call another script and use only safe syntax in this one?
The easy method for Python 2.6 is just to add a line like:
b'You need Python 2.6 or later.'
at the start of the file. This exploits the fact that byte literals were introduced in 2.6 and so any earlier versions will raise a SyntaxError with whatever message you write given as the stack trace.
There are some suggestions in this question here, but it looks like it is not easily possible. You'll have to create a wrapper script.
One way is to write your module using python 2.x print statement, then when you want to port it into python 3, you use 2to3 script. I think there are scripts for 3to2 conversion as well, although they seems to be less mature than 2to3.
Either way, in biggers scripts, you should always separate domain logic and input/output; that way, all the print statements/functions are bunched up together in a single file. For logging, you should use the logging module.