I have a argparse function containing a mix of internal and user specify settings. I want to use a json as configuration file to store user-specified parameters so that the json will be parsed back to this argparse function.
I also have a mix of data types in the parameters, they are defined in argparse but not in the json.
My argparse function looks like this
def parse_opt():
parser = argparse.ArgumentParser()
parser.add_argument('--name', nargs='+', type=str, default='experiment', help='project name') #specify by users
parser.add_argument('--visualise', action='store_true', help='output contains graphs') #specify by users
parser.add_argument('--imgsize', '--img', '--img-size', nargs='+', type=int, default=[640], help='image size h,w') #let users specify
parser.add_argument('--data', type=str, default=ROOT / 'data/coco128.yaml', help='(optional) dataset.yaml path') #internal default setting
parser.add_argument('--thres', type=float, default=0.3, help='threshold') #internal default setting
opt = parser.parse_args()
return opt
My json configuration config.json looks like this, and it allows users to specify their parameters
d = {"name": "trial_001",
"visualise": true,
"imgsize": 1280}
I tried the following to pass new configurations using the script below, and ran into error TypeError: 'bool' object is not subscriptable . In the main() function, I want all default settings parsed as opt , then the three use user-defined parameters defined in config.json will override opt.name, opt.visualise and opt.imgsize. Then detect(**vars(opt)) reads all users and default parameters and apply detect() function to them (note: my detect() function isn't added in this post as it is quite long). Appreciate any pointers here. thanks.
import argparse
import json
def main(opt):
opt = parse_opt()
with open('config.json') as config_file:
d = json.loads(config_file.read())
for item in d.items():
args.extend(item)
detect(**vars(opt)) #detect() is a function that reads all variables from opt
if __name__ == "__main__":
main(opt)
EDIT: this is the full error message I encountered.
for item in d.items():
args.extend(item)
parser.parse_args(args)
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3326, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-26-53a113868d66>", line 1, in <module>
parser.parse_args(args)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/argparse.py", line 1749, in parse_args
args, argv = self.parse_known_args(args, namespace)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/argparse.py", line 1781, in parse_known_args
namespace, args = self._parse_known_args(args, namespace)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/argparse.py", line 1822, in _parse_known_args
option_tuple = self._parse_optional(arg_string)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/argparse.py", line 2108, in _parse_optional
if not arg_string[0] in self.prefix_chars:
TypeError: 'bool' object is not subscriptable
In Python, how can we find out the command line arguments that were provided for a script, and process them?
For some more specific examples, see Implementing a "[command] [action] [parameter]" style command-line interfaces? and How do I format positional argument help using Python's optparse?.
import sys
print("\n".join(sys.argv))
sys.argv is a list that contains all the arguments passed to the script on the command line. sys.argv[0] is the script name.
Basically,
import sys
print(sys.argv[1:])
The canonical solution in the standard library is argparse (docs):
Here is an example:
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument("-f", "--file", dest="filename",
help="write report to FILE", metavar="FILE")
parser.add_argument("-q", "--quiet",
action="store_false", dest="verbose", default=True,
help="don't print status messages to stdout")
args = parser.parse_args()
argparse supports (among other things):
Multiple options in any order.
Short and long options.
Default values.
Generation of a usage help message.
Just going around evangelizing for argparse which is better for these reasons.. essentially:
(copied from the link)
argparse module can handle positional
and optional arguments, while
optparse can handle only optional
arguments
argparse isn’t dogmatic about
what your command line interface
should look like - options like -file
or /file are supported, as are
required options. Optparse refuses to
support these features, preferring
purity over practicality
argparse produces more
informative usage messages, including
command-line usage determined from
your arguments, and help messages for
both positional and optional
arguments. The optparse module
requires you to write your own usage
string, and has no way to display
help for positional arguments.
argparse supports action that
consume a variable number of
command-line args, while optparse
requires that the exact number of
arguments (e.g. 1, 2, or 3) be known
in advance
argparse supports parsers that
dispatch to sub-commands, while
optparse requires setting
allow_interspersed_args and doing the
parser dispatch manually
And my personal favorite:
argparse allows the type and
action parameters to add_argument()
to be specified with simple
callables, while optparse requires
hacking class attributes like
STORE_ACTIONS or CHECK_METHODS to get
proper argument checking
There is also argparse stdlib module (an "impovement" on stdlib's optparse module). Example from the introduction to argparse:
# script.py
import argparse
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'integers', metavar='int', type=int, choices=range(10),
nargs='+', help='an integer in the range 0..9')
parser.add_argument(
'--sum', dest='accumulate', action='store_const', const=sum,
default=max, help='sum the integers (default: find the max)')
args = parser.parse_args()
print(args.accumulate(args.integers))
Usage:
$ script.py 1 2 3 4
4
$ script.py --sum 1 2 3 4
10
If you need something fast and not very flexible
main.py:
import sys
first_name = sys.argv[1]
last_name = sys.argv[2]
print("Hello " + first_name + " " + last_name)
Then run python main.py James Smith
to produce the following output:
Hello James Smith
The docopt library is really slick. It builds an argument dict from the usage string for your app.
Eg from the docopt readme:
"""Naval Fate.
Usage:
naval_fate.py ship new <name>...
naval_fate.py ship <name> move <x> <y> [--speed=<kn>]
naval_fate.py ship shoot <x> <y>
naval_fate.py mine (set|remove) <x> <y> [--moored | --drifting]
naval_fate.py (-h | --help)
naval_fate.py --version
Options:
-h --help Show this screen.
--version Show version.
--speed=<kn> Speed in knots [default: 10].
--moored Moored (anchored) mine.
--drifting Drifting mine.
"""
from docopt import docopt
if __name__ == '__main__':
arguments = docopt(__doc__, version='Naval Fate 2.0')
print(arguments)
One way to do it is using sys.argv. This will print the script name as the first argument and all the other parameters that you pass to it.
import sys
for arg in sys.argv:
print arg
#set default args as -h , if no args:
if len(sys.argv) == 1: sys.argv[1:] = ["-h"]
I use optparse myself, but really like the direction Simon Willison is taking with his recently introduced optfunc library. It works by:
"introspecting a function
definition (including its arguments
and their default values) and using
that to construct a command line
argument parser."
So, for example, this function definition:
def geocode(s, api_key='', geocoder='google', list_geocoders=False):
is turned into this optparse help text:
Options:
-h, --help show this help message and exit
-l, --list-geocoders
-a API_KEY, --api-key=API_KEY
-g GEOCODER, --geocoder=GEOCODER
I like getopt from stdlib, eg:
try:
opts, args = getopt.getopt(sys.argv[1:], 'h', ['help'])
except getopt.GetoptError, err:
usage(err)
for opt, arg in opts:
if opt in ('-h', '--help'):
usage()
if len(args) != 1:
usage("specify thing...")
Lately I have been wrapping something similiar to this to make things less verbose (eg; making "-h" implicit).
As you can see optparse "The optparse module is deprecated with and will not be developed further; development will continue with the argparse module."
Pocoo's click is more intuitive, requires less boilerplate, and is at least as powerful as argparse.
The only weakness I've encountered so far is that you can't do much customization to help pages, but that usually isn't a requirement and docopt seems like the clear choice when it is.
import argparse
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('integers', metavar='N', type=int, nargs='+',
help='an integer for the accumulator')
parser.add_argument('--sum', dest='accumulate', action='store_const',
const=sum, default=max,
help='sum the integers (default: find the max)')
args = parser.parse_args()
print(args.accumulate(args.integers))
Assuming the Python code above is saved into a file called prog.py
$ python prog.py -h
Ref-link: https://docs.python.org/3.3/library/argparse.html
You may be interested in a little Python module I wrote to make handling of command line arguments even easier (open source and free to use) - Commando
Yet another option is argh. It builds on argparse, and lets you write things like:
import argh
# declaring:
def echo(text):
"Returns given word as is."
return text
def greet(name, greeting='Hello'):
"Greets the user with given name. The greeting is customizable."
return greeting + ', ' + name
# assembling:
parser = argh.ArghParser()
parser.add_commands([echo, greet])
# dispatching:
if __name__ == '__main__':
parser.dispatch()
It will automatically generate help and so on, and you can use decorators to provide extra guidance on how the arg-parsing should work.
I recommend looking at docopt as a simple alternative to these others.
docopt is a new project that works by parsing your --help usage message rather than requiring you to implement everything yourself. You just have to put your usage message in the POSIX format.
Also with python3 you might find convenient to use Extended Iterable Unpacking to handle optional positional arguments without additional dependencies:
try:
_, arg1, arg2, arg3, *_ = sys.argv + [None] * 2
except ValueError:
print("Not enough arguments", file=sys.stderr) # unhandled exception traceback is meaningful enough also
exit(-1)
The above argv unpack makes arg2 and arg3 "optional" - if they are not specified in argv, they will be None, while if the first is not specified, ValueError will be thouwn:
Traceback (most recent call last):
File "test.py", line 3, in <module>
_, arg1, arg2, arg3, *_ = sys.argv + [None] * 2
ValueError: not enough values to unpack (expected at least 4, got 3)
My solution is entrypoint2. Example:
from entrypoint2 import entrypoint
#entrypoint
def add(file, quiet=True):
''' This function writes report.
:param file: write report to FILE
:param quiet: don't print status messages to stdout
'''
print file,quiet
help text:
usage: report.py [-h] [-q] [--debug] file
This function writes report.
positional arguments:
file write report to FILE
optional arguments:
-h, --help show this help message and exit
-q, --quiet don't print status messages to stdout
--debug set logging level to DEBUG
import sys
# Command line arguments are stored into sys.argv
# print(sys.argv[1:])
# I used the slice [1:] to print all the elements except the first
# This because the first element of sys.argv is the program name
# So the first argument is sys.argv[1], the second is sys.argv[2] ecc
print("File name: " + sys.argv[0])
print("Arguments:")
for i in sys.argv[1:]:
print(i)
Let's name this file command_line.py and let's run it:
C:\Users\simone> python command_line.py arg1 arg2 arg3 ecc
File name: command_line.py
Arguments:
arg1
arg2
arg3
ecc
Now let's write a simple program, sum.py:
import sys
try:
print(sum(map(float, sys.argv[1:])))
except:
print("An error has occurred")
Result:
C:\Users\simone> python sum.py 10 4 6 3
23
This handles simple switches, value switches with optional alternative flags.
import sys
# [IN] argv - array of args
# [IN] switch - switch to seek
# [IN] val - expecting value
# [IN] alt - switch alternative
# returns value or True if val not expected
def parse_cmd(argv,switch,val=None,alt=None):
for idx, x in enumerate(argv):
if x == switch or x == alt:
if val:
if len(argv) > (idx+1):
if not argv[idx+1].startswith('-'):
return argv[idx+1]
else:
return True
//expecting a value for -i
i = parse_cmd(sys.argv[1:],"-i", True, "--input")
//no value needed for -p
p = parse_cmd(sys.argv[1:],"-p")
Several of our biotechnology clients have posed these two questions recently:
How can we execute a Python script as a command?
How can we pass input values to a Python script when it is executed as a command?
I have included a Python script below which I believe answers both questions. Let's assume the following Python script is saved in the file test.py:
#
#----------------------------------------------------------------------
#
# file name: test.py
#
# input values: data - location of data to be processed
# date - date data were delivered for processing
# study - name of the study where data originated
# logs - location where log files should be written
#
# macOS usage:
#
# python3 test.py "/Users/lawrence/data" "20220518" "XYZ123" "/Users/lawrence/logs"
#
# Windows usage:
#
# python test.py "D:\data" "20220518" "XYZ123" "D:\logs"
#
#----------------------------------------------------------------------
#
# import needed modules...
#
import sys
import datetime
def main(argv):
#
# print message that process is starting...
#
print("test process starting at", datetime.datetime.now().strftime("%Y%m%d %H:%M"))
#
# set local values from input values...
#
data = sys.argv[1]
date = sys.argv[2]
study = sys.argv[3]
logs = sys.argv[4]
#
# print input arguments...
#
print("data value is", data)
print("date value is", date)
print("study value is", study)
print("logs value is", logs)
#
# print message that process is ending...
#
print("test process ending at", datetime.datetime.now().strftime("%Y%m%d %H:%M"))
#
# call main() to begin processing...
#
if __name__ == '__main__':
main(sys.argv)
The script can be executed on a macOS computer in a Terminal shell as shown below and the results will be printed to standard output (be sure the current directory includes the test.py file):
$ python3 test.py "/Users/lawrence/data" "20220518" "XYZ123" "/Users/lawrence/logs"
test process starting at 20220518 16:51
data value is /Users/lawrence/data
date value is 20220518
study value is XYZ123
logs value is /Users/lawrence/logs
test process ending at 20220518 16:51
The script can also be executed on a Windows computer in a Command Prompt as shown below and the results will be printed to standard output (be sure the current directory includes the test.py file):
D:\scripts>python test.py "D:\data" "20220518" "XYZ123" "D:\logs"
test process starting at 20220518 17:20
data value is D:\data
date value is 20220518
study value is XYZ123
logs value is D:\logs
test process ending at 20220518 17:20
This script answers both questions posed above and is a good starting point for developing scripts that will be executed as commands with input values.
Reason for the new answer:
Existing answers specify multiple options.
Standard option is to use argparse, a few answers provided examples from the documentation, and one answer suggested the advantage of it. But all fail to explain the answer adequately/clearly to the actual question by OP, at least for newbies.
An example of argparse:
import argparse
def load_config(conf_file):
pass
if __name__ == '__main__':
parser = argparse.ArgumentParser()
//Specifies one argument from the command line
//You can have any number of arguments like this
parser.add_argument("conf_file", help="configuration file for the application")
args = parser.parse_args()
config = load_config(args.conf_file)
Above program expects a config file as an argument. If you provide it, it will execute happily. If not, it will print the following
usage: test.py [-h] conf_file
test.py: error: the following arguments are required: conf_file
You can have the option to specify if the argument is optional.
You can specify the expected type for the argument using type key
parser.add_argument("age", type=int, help="age of the person")
You can specify default value for the arguments by specifying default key
This document will help you to understand it to an extent.
I was wondering if this was possible to iterate through a map directly in Cython code, ie, in the .pyx.
Here is my example:
import cython
cimport cython
from licpp.map import map as mapcpp
def it_through_map(dict mymap_of_int_int):
# python dict to map
cdef mapcpp[int,int] mymap_in = mymap_of_int_int
cdef mapcpp[int,int].iterator it = mymap_in.begin()
while(it != mymap.end()):
# let's pretend here I just want to print the key and the value
print(it.first) # Not working
print(it.second) # Not working
it ++ # Not working
This does not compile: Object of type 'iterator' has no attribute 'first'
I used map container in cpp before but for this code, I am trying to stick to cython/python, is it possible here?.
Resolved by DavidW
Here is an working version of the code, following DavidW answer:
import cython
cimport cython
from licpp.map import map as mapcpp
from cython.operator import dereference, postincrement
def it_through_map(dict mymap_of_int_int):
# python dict to map
cdef mapcpp[int,int] mymap_in = mymap_of_int_int
cdef mapcpp[int,int].iterator it = mymap_in.begin()
while(it != mymap.end()):
# let's pretend here I just want to print the key and the value
print(dereference(it).first) # print the key
print(dereference(it).second) # print the associated value
postincrement(it) # Increment the iterator to the net element
The map iterator doesn't have elements first and second. Instead it has a operator* which returns a pair reference. In C++ you can use it->first to do this in one go, but that syntax doesn't work in Cython (and it isn't intelligent enough to decide to use -> instead of . itself in this case).
Instead you use cython.operator.dereference:
from cython.operator cimport dereference
# ...
print(dereference(it).first)
Similarly, it++ can be done with cython.operator.postincrement
I know I should specify argtypes for my C/C++ functions since some of my calls would otherwise result in stack corruption.
myCfunc.argtypes = [ct.c_void_p, ct.POINTER(ct.c_void_p)]
myCfunc.errcheck = my_error_check
In fact, I would like to verify that I did not forget to specify function prototypes (argtypes/errcheck) for any of my about 100 function calls...
Right now I just grep through my Python files and visually compare against my file containing the prototype definitions.
Is there a better way to verify that I have defined argtypes/errcheck for all my calls?
The mention of namespaces by #eryksun made me wrap the dll in a class that only exposes the explicitly annotated functions. As long as the dll doesn't have the function names "annotate" or "_error_check" (which my didn't), the following approach seems to work for me:
import ctypes as ct
class MyWinDll:
def __init__(self, dll_filename):
self._dll = ct.WinDLL(dll_filename)
# Specify function prototypes using the annotate function
self.annotate(self._dll.myCfunc, [ct.POINTER(ct.c_void_p)], self._error_check)
self.annotate(self._dll.myCfunc2, [ct.c_void_p], self._error_check)
...
def annotate(self, function, argtypes, errcheck):
# note that "annotate" may not be used as a function name in the dll...
function.argtypes = argtypes
function.errcheck = errcheck
setattr(self, function.__name__, function)
def _error_check(self, result, func, arguments):
if result != 0:
raise Exception
if __name__ == '__main__':
dll = MyWinDll('myWinDll.dll')
handle = ct.c_void_p(None)
# Now call the dll functions using the wrapper object
dll.myCfunc(ct.byref(handle))
dll.myCfunc2(handle)
Update: Comments by #eryksun made me try to improve the code by giving the user control of the WinDLL constructor and attempting to reduce repeated code:
import ctypes as ct
DEFAULT = object()
def annotate(dll_object, function_name, argtypes, restype=DEFAULT, errcheck=DEFAULT):
function = getattr(dll_object._dll, function_name)
function.argtypes = argtypes
# restype and errcheck is optional in the function_prototypes list
if restype is DEFAULT:
restype = dll_object.default_restype
function.restype = restype
if errcheck is DEFAULT:
errcheck = dll_object.default_errcheck
function.errcheck = errcheck
setattr(dll_object, function_name, function)
class MyDll:
def __init__(self, ct_dll, **function_prototypes):
self._dll = ct_dll
for name, prototype in function_prototypes.items():
annotate(self, name, *prototype)
class OneDll(MyDll):
def __init__(self, ct_dll):
# set default values for function_prototypes
self.default_restype = ct.c_int
self.default_errcheck = self._error_check
function_prototypes = {
'myCfunc': [[ct.POINTER(ct.c_void_p)]],
'myCfunc2': [[ct.c_void_p]],
# ...
'myCgetErrTxt': [[ct.c_int, ct.c_char_p, ct.c_size_t], DEFAULT, None]
}
super().__init__(ct_dll, **function_prototypes)
# My error check function actually calls the dll, so I keep it here...
def _error_check(self, result, func, arguments):
msg = ct.create_string_buffer(255)
if result != 0:
raise Exception(self.myCgetErrTxt(result, msg, ct.sizeof(msg)))
if __name__ == '__main__':
ct_dll = ct.WinDLL('myWinDll.dll')
dll = OneDll(ct_dll)
handle = ct.c_void_p(None)
dll.myCfunc(ct.byref(handle))
dll.myCfunc2(handle)
(I don't know if original code should be deleted, I kept it for reference.)
Here's a dummy class that can replace the DLL object's function call with a simple check to see the attributes have been defined:
class DummyFuncPtr(object):
restype = False
argtypes = False
errcheck = False
def __call__(self, *args, **kwargs):
assert self.restype
assert self.argtypes
assert self.errcheck
def __init__(self, *args):
pass
def __setattr__(self, key, value):
super(DummyFuncPtr, self).__setattr__(key, True)
To use it replace your DLL object's _FuncPtr class and then call each function to run the check, e.g.:
dll = ctypes.cdll.LoadLibrary(r'path/to/dll')
# replace the DLL's function pointer
# comment out this line to disable the dummy class
dll._FuncPtr = DummyFuncPtr
some_func = dll.someFunc
some_func.restype = None
some_func.argtypes = None
some_func.errcheck = None
another_func = dll.anotherFunc
another_func.restype = None
another_func.argtypes = None
some_func() # no error
another_func() # Assertion error due to errcheck not defined
The dummy class completely prevents the function from ever being called of course, so just comment out the replacement line to switch back to normal operation.
Note that it will only check each function when that function is called, so this would best be in a unit test file somewhere where the function is guaranteed to be called.