We've been using pipenv for dependency management for a while, and using micropipenv's protected functionality to check lock freshness - the idea here being that micropipenv is lightweight, so this is a cheap and cheerful way of ensuring that our dependencies haven't drifted during CI or during a docker build.
Alas, micropipenv has no such feature for poetry (it skips the hash check completely), and I am therefore left to "reverse-engineer" the feature on my own. Ostensibly this should be super easy - I've assembled the code posted later from what I traced through the poetry and poetry-core repos (Locker, Factory, core.Factory, and PyProjectTOML, primarily). This absolutely does not do the trick, and I'm at a loss as to why.
_relevant_keys = ["dependencies", "group", "source", "extras"]
def _get_content_hash(pyproject):
content = pyproject["tool"]["poetry"]
print(content)
relevant_content = {}
for key in _relevant_keys:
relevant_content[key] = content.get(key)
print(json.dumps(relevant_content, sort_keys=True).encode())
content_hash = sha256(
json.dumps(relevant_content, sort_keys=True).encode()
).hexdigest()
print(f"Calculated: {content_hash}")
return content_hash
def is_fresh(lockfile, pyproject):
metadata = lockfile.get("metadata", {})
print(f"From file: {lockfile['metadata']['content-hash']}")
if "content-hash" in metadata:
return _get_content_hash(pyproject) == lockfile["metadata"]["content-hash"]
return False
Would love to figure out what exactly the heck I'm missing here - i'm guessing that the poetry locker _local_config gets changed at some point and I've failed to notice it.
References:
Locker: https://github.com/python-poetry/poetry/blob/a1a5bce96d85bdc0fdc60b8abf644615647f969e/poetry/packages/locker.py#L454
core.Factory: https://github.com/python-poetry/poetry-core/blob/afaa6903f654b695d9411fb548ad10630287c19f/poetry/core/factory.py#L24
Naturally, this ended up being a PEBKAC error. I was using the hash generation function from the master branch but using an earlier version of poetry on the command line. Once I used the function from the correct code version, everything was hunky dory.
I think this functionality actually exists in micropipenv now anyways lol
I'm trying to make a simple speech recognition program in Python using Sphinx. I installed it using pip in CMD, then I installed PocketSphinx in the same way. The tutorial I'm following says I need to include the model directories for PocketSphinx, but I don't know where the directory is. How do I find it, and am I doing something wrong?
If you are using pocketsphinx-python installed via pip, and following some example code similar to that provided by the package's github page, you may find there are a few code changes needed.
Here's what's currently in the README (as of March 11, 2018):
from pocketsphinx.pocketsphinx import *
from sphinxbase.sphinxbase import *
MODELDIR = "pocketsphinx/model"
DATADIR = "pocketsphinx/test/data"
# Create a decoder with certain model
config = Decoder.default_config()
config.set_string('-hmm', path.join(MODELDIR, 'en-us/en-us'))
config.set_string('-lm', path.join(MODELDIR, 'en-us/en-us.lm.bin'))
config.set_string('-dict', path.join(MODELDIR, 'en-us/cmudict-en-us.dict'))
This not-yet-accepted pull request describes some changes which may help for those of us using pip and working on our python code outside the downloaded module's directory (at least in a *nix/Mac environment, I haven't tested on Windows). Here's a diff snippet; the key idea is to use path.dirname(pocketsphinx.__file__) to get the base directory in which to look for the model directory:
-MODELDIR = "pocketsphinx/model"
-DATADIR = "pocketsphinx/test/data"
+import pocketsphinx;
+POCKETSPHINXDIR = path.dirname(pocketsphinx.__file__)
+MODELDIR = path.join(POCKETSPHINXDIR, "model")
+DATADIR = path.join(POCKETSPHINXDIR, "data")
(Small note: I took liberty to fix a small typo in the spelling of POCKETSPHINXDIR, so this code isn't exactly the same as the pull request)
Go the location where your python is installed look for the following location inside that (this location is according to windows installation)
Lib\site-packages\speech_recognition\pocketsphinx-data
default model is en-US however there are few other language models that one can download from here
https://sourceforge.net/projects/cmusphinx/files/Acoustic%20and%20Language%20Models/
It may be late to answer now, but for newcomers, Python module has some convenience methods:
from pocketsphinx import get_model_path, get_data_path
print(get_model_path())
print(get_data_path())
I'm trying to add cross-references to external API into my documentation but I'm facing three different behaviors.
I am using sphinx(1.3.1) with Python(2.7.3) and my intersphinx mapping is configured as:
{
'python': ('https://docs.python.org/2.7', None),
'numpy': ('http://docs.scipy.org/doc/numpy/', None),
'cv2' : ('http://docs.opencv.org/2.4/', None),
'h5py' : ('http://docs.h5py.org/en/latest/', None)
}
I have no trouble writing a cross-reference to numpy API with :class:`numpy.ndarray` or :func:`numpy.array` which gives me, as expected, something like numpy.ndarray.
However, with h5py, the only way I can have a link generated is if I omit the module name. For example, :class:`Group` (or :class:`h5py:Group`) gives me Group but :class:`h5py.Group` fails to generate a link.
Finally, I cannot find a way to write a working cross-reference to OpenCV API, none of these seems to work:
:func:`cv2.convertScaleAbs`
:func:`cv2:cv2.convertScaleAbs`
:func:`cv2:convertScaleAbs`
:func:`convertScaleAbs`
How to properly write cross-references to external API, or configure intersphinx, to have a generated link as in the numpy case?
In addition to the detailed answer from #gall, I've discovered that intersphinx can also be run as a module:
python -m sphinx.ext.intersphinx 'http://python-eve.org/objects.inv'
This outputs nicely formatted info. For reference: https://github.com/sphinx-doc/sphinx/blob/master/sphinx/ext/intersphinx.py#L390
I gave another try on trying to understand the content of an objects.inv file and hopefully this time I inspected numpy and h5py instead of only OpenCV's one.
How to read an intersphinx inventory file
Despite the fact that I couldn't find anything useful about reading the content of an object.inv file, it is actually very simple with the intersphinx module.
from sphinx.ext import intersphinx
import warnings
def fetch_inventory(uri):
"""Read a Sphinx inventory file into a dictionary."""
class MockConfig(object):
intersphinx_timeout = None # type: int
tls_verify = False
class MockApp(object):
srcdir = ''
config = MockConfig()
def warn(self, msg):
warnings.warn(msg)
return intersphinx.fetch_inventory(MockApp(), '', uri)
uri = 'http://docs.python.org/2.7/objects.inv'
# Read inventory into a dictionary
inv = fetch_inventory(uri)
# Or just print it
intersphinx.debug(['', uri])
File structure (numpy)
After inspecting numpy's one, you can see that keys are domains:
[u'np-c:function',
u'std:label',
u'c:member',
u'np:classmethod',
u'np:data',
u'py:class',
u'np-c:member',
u'c:var',
u'np:class',
u'np:function',
u'py:module',
u'np-c:macro',
u'np:exception',
u'py:method',
u'np:method',
u'np-c:var',
u'py:exception',
u'np:staticmethod',
u'py:staticmethod',
u'c:type',
u'np-c:type',
u'c:macro',
u'c:function',
u'np:module',
u'py:data',
u'np:attribute',
u'std:term',
u'py:function',
u'py:classmethod',
u'py:attribute']
You can see how you can write your cross-reference when you look at the content of a specific domain. For example, py:class:
{u'numpy.DataSource': (u'NumPy',
u'1.9',
u'http://docs.scipy.org/doc/numpy/reference/generated/numpy.DataSource.html#numpy.DataSource',
u'-'),
u'numpy.MachAr': (u'NumPy',
u'1.9',
u'http://docs.scipy.org/doc/numpy/reference/generated/numpy.MachAr.html#numpy.MachAr',
u'-'),
u'numpy.broadcast': (u'NumPy',
u'1.9',
u'http://docs.scipy.org/doc/numpy/reference/generated/numpy.broadcast.html#numpy.broadcast',
u'-'),
...}
So here, :class:`numpy.DataSource` will work as expected.
h5py
In the case of h5py, the domains are:
[u'py:attribute', u'std:label', u'py:method', u'py:function', u'py:class']
and if you look at the py:class domain:
{u'AttributeManager': (u'h5py',
u'2.5',
u'http://docs.h5py.org/en/latest/high/attr.html#AttributeManager',
u'-'),
u'Dataset': (u'h5py',
u'2.5',
u'http://docs.h5py.org/en/latest/high/dataset.html#Dataset',
u'-'),
u'ExternalLink': (u'h5py',
u'2.5',
u'http://docs.h5py.org/en/latest/high/group.html#ExternalLink',
u'-'),
...}
That's why I couldn't make it work as numpy references. So a good way to format them would be :class:`h5py:Dataset`.
OpenCV
OpenCV's inventory object seems malformed. Where I would expect to find domains there is actually 902 function signatures:
[u':',
u'AdjusterAdapter::create(const',
u'AdjusterAdapter::good()',
u'AdjusterAdapter::tooFew(int',
u'AdjusterAdapter::tooMany(int',
u'Algorithm::create(const',
u'Algorithm::getList(vector<string>&',
u'Algorithm::name()',
u'Algorithm::read(const',
u'Algorithm::set(const'
...]
and if we take the first one's value:
{u'Ptr<AdjusterAdapter>': (u'OpenCV',
u'2.4',
u'http://docs.opencv.org/2.4/detectorType)',
u'ocv:function 1 modules/features2d/doc/common_interfaces_of_feature_detectors.html#$ -')}
I'm pretty sure it is then impossible to write OpenCV cross-references with this file...
Conclusion
I thought intersphinx generated the objects.inv based on the content of the documentation project in an standard way, which seems not to be the case.
As a result, it seems that the proper way to write cross-references is API dependent and one should inspect a specific inventory object to actually see what's available.
An additional way to inspect the objects.inv file is with the sphobjinv module.
You can search local or even remote inventory files (with fuzzy matching). For instance with scipy:
$ sphobjinv suggest -t 90 -u https://docs.scipy.org/doc/scipy/reference/objects.inv "signal.convolve2d"
Remote inventory found.
:py:function:`scipy.signal.convolve2d`
:std:doc:`generated/scipy.signal.convolve2d`
Note that you may need to use :py:func: and not :py:function: (I'd be happy to know why).
How to use OpenCV 2.4 (cv2) intersphinx
Inspired by #Gall's answer, I wanted to compare the contents of the OpenCV & numpy inventory files. I couldn't get sphinx.ext.intersphinx.fetch_inventory to work from ipython, but the following does work:
curl http://docs.opencv.org/2.4/objects.inv | tail -n +5 | zlib-flate -uncompress > cv2.inv
curl https://docs.scipy.org/doc/numpy/objects.inv | tail -n +5 | zlib-flate -uncompress > numpy.inv
numpy.inv has lines like this:
numpy.ndarray py:class 1 reference/generated/numpy.ndarray.html#$ -
whereas cv2.inv has lines like this:
cv2.imread ocv:pyfunction 1 modules/highgui/doc/reading_and_writing_images_and_video.html#$ -
So presumably you'd link to the OpenCV docs with :ocv:pyfunction:`cv2.imread` instead of :py:function:`cv2.imread`. Sphinx doesn't like it though:
WARNING: Unknown interpreted text role "ocv:pyfunction".
A bit of Googling revealed that the OpenCV project has its own "ocv" sphinx domain: https://github.com/opencv/opencv/blob/2.4/doc/ocv.py -- presumably because they need to document C, C++ and Python APIs all at the same time.
To use it, save ocv.py next to your Sphinx conf.py, and modify your conf.py:
sys.path.insert(0, os.path.abspath('.'))
import ocv
extensions = [
'ocv',
]
intersphinx_mapping = {
'cv2': ('http://docs.opencv.org/2.4/', None),
}
In your rst files you need to say :ocv:pyfunc:`cv2.imread` (not :ocv:pyfunction:).
Sphinx prints some warnings (unparseable C++ definition: u'cv2.imread') but the generated html documentation actually looks ok with a link to http://docs.opencv.org/2.4/modules/highgui/doc/reading_and_writing_images_and_video.html#cv2.imread. You can edit ocv.py and remove the line that prints that warning.
The accepted answer no longer works in the new version (1.5.x) ...
import requests
import posixpath
from sphinx.ext.intersphinx import read_inventory
uri = 'http://docs.python.org/2.7/'
r = requests.get(uri + 'objects.inv', stream=True)
r.raise_for_status()
inv = read_inventory(r.raw, uri, posixpath.join)
Stubborn fool that I am, I used 2to3 and the Sphinx deprecated APIs chart to revive #david-röthlisberger's ocv.py-based answer so it'll work with Sphinx 2.3 on Python 3.5.
The fixed-up version is here:
https://gist.github.com/ssokolow/a230b27b7ea4a31f7fb40621e6461f9a
...and the quick version of what I did was:
Run 2to3 -w ocv.py && rm ocv.py.bak
Cycle back and forth between running Sphinx and renaming functions to their replacements in the chart. I believe these were the only changes I had to make on this step:
Directive now has to be imported from docutils.parsers.rst
Replace calls to l_(...) with calls to _(...) and remove the l_ import.
Replace calls to env.warn with calls to log.warn where log = sphinx.util.logging.getLogger(__name__).
Then, you just pair it with this intersphinx definition and you get something still new enough to be relevant for most use cases:
'cv2': ('https://docs.opencv.org/3.0-last-rst/', None)
For convenience, I made a small extension for aliasing intersphinx cross references. This is useful as sometimes the object inventory gets confused when an object from a submodule is imported from a package's __init__.py.
See also https://github.com/sphinx-doc/sphinx/issues/5603
###
# Workaround of
# Intersphinx references to objects imported at package level can"t be mapped.
#
# See https://github.com/sphinx-doc/sphinx/issues/5603
intersphinx_aliases = {
("py:class", "click.core.Group"):
("py:class", "click.Group"),
("py:class", "click.core.Command"):
("py:class", "click.Command"),
}
def add_intersphinx_aliases_to_inv(app):
from sphinx.ext.intersphinx import InventoryAdapter
inventories = InventoryAdapter(app.builder.env)
for alias, target in app.config.intersphinx_aliases.items():
alias_domain, alias_name = alias
target_domain, target_name = target
try:
found = inventories.main_inventory[target_domain][target_name]
try:
inventories.main_inventory[alias_domain][alias_name] = found
except KeyError:
print("could not add to inv")
continue
except KeyError:
print("missed :(")
continue
def setup(app):
app.add_config_value("intersphinx_aliases", {}, "env")
app.connect("builder-inited", add_intersphinx_aliases_to_inv)
To use this, I paste the above code in my conf.py and add aliases to the intersphinx_aliases dictionary.
Edit: So apparantly my install wasn't working. This pointed me to a mailing list Here where I figured out which commands I was missing. I have the answer for the update below. Now that I think about it, it does make sense. I just wish they'd put this somewhere simple on the dev pages.
yb = yum.YumBase()
yb.conf.assumeyes = True
yb.update(name='aws-cli')
yb.buildTransaction()
yb.processTransaction()
I'm trying to perform an update using yumbase when a server first boots with my kickstart script. At the moment I have a rather crude python subprocess to do "yum update" and would like to make this better.
I'm trying to hook into Yumbase, but the documentation is quite scarce. I have had a look at both the source code and documentation on this page: http://yum.baseurl.org/wiki/5MinuteExamples
I've figured out how to list all packages but not the ones that need updating using an SO answer from 2008: Given an rpm package name, query the yum database for updates
I've also figured out it's a very simple 3-line process to install a new package:
yb = yum.YumBase()
yb.conf.assumeyes = True
yb.install(name='aws-cli')
However the following doesn't work to "update" the package:
yb = yum.YumBase()
yb.conf.assumeyes = True
yb.update(name='aws-cli')
So what I need is:
1: A way to list the packages that need updating, much like "yum check-update"
2: Install the packages above using "yum update"
From what I can see in the yum code, it doesn't seem to be written to be used as a library. The code you gave is not the right way to do it, there's much else happening behind the scenes.
Basically, as of yum-3.4.3, the process looks like this:
->yummain.__main__
<trap KeyboardInterrupt>
->yummain.user_main(sys.argv[1:], exit_code=True)
<check YUM_PROF,YUM_PDB envvars, wrap the following into debugger/profiler if set>
->yummain.main(args)
<set up locale, set up logging>
-><create a YumBaseCli (child of YumBase & YumOutput)>
<incl. fill a list field with YumCommand instances of known commands>
->cli.YumBaseCli.getOptionsConfig()
<parse args into the YumBaseCli instance, includes initializing plugins>
<obtain global yum lock>
<check write permissions for current dir>
->cli.YumBaseCli.doCommands()
<select a YumCommand from the list>
->YumCommand.needTs/needTsRemove if needed
->YumCommand.doCommand(self, self.basecmd, self.extcmds)
<handle errors & set error code if any>
'Resolving Dependencies'
->cli.YumBaseCli.buildTransaction()
<check for an unfinished transaction>
<resolve deps using the info written by the YumCommand into the object>
<honor clean_requirements_on_remove, protected_packages,
protected_multilib, perform some checks>
<handle errors & set error code if any>
'Dependencies Resolved'
->cli.YumBaseCli.doTransaction()
<download, transaction check, transaction test, transaction
using the info in the object>
<handle errors & set error code if any>
'Complete!'
<release global yum lock>
sys.exit(error_code)
As you can see, the main working sequence is embedded directly into main so you can only replicate this logic in-process by running it directly:
yummain.main(<sequence of cmdline arguments>)
Which is just the same as running a separate process minus process isolation.