I have a Flyte task function like this:
#task
def do_stuff(framework_obj):
framework_obj.get_outputs() # This calls Types.Blob.fetch(some_uri)
Trying to load a blob URI using flytekit.sdk.types.Types.Blob.fetch, but getting this error:
ERROR:flytekit: Exception when executing No temporary file system is present. Either call this method from within the context of a task or surround with a 'with LocalTestFileSystem():' block. Or specify a path when calling this function. Note: Cleanup is not automatic when a path is specified.
I can confirm I can load blobs using with LocalTestFileSystem(), in tests, but when actually trying to run a workflow, I'm not sure why I'm getting this error, as the function that calls blob-processing is decorated with #task so it's definitely a Flyte Task. I also confirmed that the task node exists on the Flyte web console.
What path is the error referencing and how do I call this function appropriately?
Using Flyte Version 0.16.2
Could you please give a bit more information about the code? This is flytekit version 0.15.x? I'm a bit confused since that version shouldn't have the #task decorator. It should only have #python_task which is an older API. If you want to use the new python native typing API you should install flytekit==0.17.0 instead.
Also, could you point to the documentation you're looking at? We've updated the docs a fair amount recently, maybe there's some confusion around that. These are the examples worth looking at. There's also two new Python classes, FlyteFile and FlyteDirectory that have replaced the Blob class in flytekit (though that remains what the IDL type is called).
(would've left this as a comment but I don't have the reputation to yet.)
Some code to help with fetching outputs and reading from a file output
#task
def task_file_reader():
client = SynchronousFlyteClient("flyteadmin.flyte.svc.cluster.local:81", insecure=True)
exec_id = WorkflowExecutionIdentifier(
domain="development",
project="flytesnacks",
name="iaok0qy6k1",
)
data = client.get_execution_data(exec_id)
lit = data.full_outputs.literals["o0"]
ctx = FlyteContext.current_context()
ff = TypeEngine.to_python_value(ctx, lv=lit,
expected_python_type=FlyteFile)
with open(ff, 'rb') as fh:
print(fh.readlines())
When using the hypothesis library and performing stateful testing, how can I see or output the Bundle "services" the library is trying on my code?
Example
import hypothesis.strategies as st
from hypothesis.strategies import integers
from hypothesis.stateful import Bundle, RuleBasedStateMachine, rule, precondition
class test_servicediscovery(RuleBasedStateMachine):
services = Bundle('services')
#rule(target=services, s=st.integers(min_value=0, max_value=2))
def add_service(self, s):
return s
The question is: how do I print / see the Bundle "services" variable, generated by the library?
In the example you've given, the services bundle isn't being tried on your code - you're adding things to it, but never using them as inputs to another rule.
If you are, running Hypothesis in verbose mode will show all inputs as they happen; or even in normal mode failing examples will print all the values used.
I am trying to generate a feature set with the Essentia MusicExtractor from a yaml profile as described in the documentation here and here via python.
My code snippet:
from essentia.standard import MusicExtractor
profile = "some_profile.yaml"
audio = "some_audio.mp3"
features, frames = MusicExtractor(profile=profile)(audio)
My yaml profile:
This produces the folling error:
RuntimeError:
Error while configuring MusicExtractor:
Pool: Cannot set/add/merge value to the pool under the name 'rhythm.stats'
because that name already exists but contains a different data type than value.
It does not really look that i am doing something wrong.
I ran into the same problem and fixed it this way:
Downloaded a sample profile from the essentia repos examples.
Ran the profile.
Commented out the conflicting lines after each run, which are just a few. Basically the stats and statsMFCC lines.
From this I could derive a working profile.
I am trying to run my own version of baselines code source of reinforcement learning on github: (https://github.com/openai/baselines/tree/master/baselines/ppo2).
Whatever I do, I keep having the same display which looks like this :
Where can I edit it ? I know I should edit the "learn" method but I don't know how
Those prints are the result of the following block of code, which can be found at this link (for the latest revision at the time of writing this at least):
if update % log_interval == 0 or update == 1:
ev = explained_variance(values, returns)
logger.logkv("serial_timesteps", update*nsteps)
logger.logkv("nupdates", update)
logger.logkv("total_timesteps", update*nbatch)
logger.logkv("fps", fps)
logger.logkv("explained_variance", float(ev))
logger.logkv('eprewmean', safemean([epinfo['r'] for epinfo in epinfobuf]))
logger.logkv('eplenmean', safemean([epinfo['l'] for epinfo in epinfobuf]))
logger.logkv('time_elapsed', tnow - tfirststart)
for (lossval, lossname) in zip(lossvals, model.loss_names):
logger.logkv(lossname, lossval)
logger.dumpkvs()
If your goal is to still print some things here, but different things (or the same things in a different format) your only option really is to modify this source file (or copy the code you need into a new file and apply your changes there, if allowed by the code's license).
If your goal is just to suppress these messages, the easiest way to do so would probably be by running the following code before running this learn() function:
from baselines import logger
logger.set_level(logger.DISABLED)
That's using this function to disable the baselines logger. It might also disable other baselines-related output though.
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.