numpyencoder | Custom Python JSON encoder for handling Numpy data types | JSON Processing library
kandi X-RAY | numpyencoder Summary
kandi X-RAY | numpyencoder Summary
Custom Python JSON encoder for handling Numpy data types.
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Top functions reviewed by kandi - BETA
- Convert NumPy arrays to JSON .
numpyencoder Key Features
numpyencoder Examples and Code Snippets
Lines of Code : 106License : Strong Copyleft (CC BY-SA 4.0)
Copy# A very simplified abstraction of the actual app.
def simulate_intervals(data):
for t in range(data.n_intervals):
state = interval(data) # returns a JAX NumPy array
yield state
def simulate(data):
for key in range(data.n_triwith open(os.path.join(logs_dir, 'config.json'), 'w') as file:
json.dump(Config.__dict__.copy(), file, cls = NumpyEncoder)
import numpy as np
import json
from numpyencoder import NumpyEncoder
numpy_data = np.array([0, 1, 2, 3])
print(json.dumps(numpy_data, cls=NumpyEncoder))
print ("", flush = True)
python -m pip install --user "git+https://github.com/javadba/mpld3@display_fix"
def _convert_numpy_objects(self, dict_to_convert : Dict) -> Dict:
new = {}
for k, v in dict_to_convert.items():
if isinstance(v, dict):
new[k] = self._convert_numpy_objects(v)
else:
if isidef default(self, obj):
if isinstance(obj, (numpy.int_, numpy.intc, numpy.intp, numpy.int8,
numpy.int16, numpy.int32, numpy.int64, numpy.uint8,
numpy.uint16,numpy.uint32, numpy.uint64)):
return int(obj)
elifclass NumpyEncoder(json.JSONEncoder):
""" Special json encoder for numpy types """
-
def default(self, obj):
if isinstance(obj, (numpy.int_, numpy.intc, numpy.intp, numpy.int8,
numpy.int16, numpy.int32,Community Discussions
Trending Discussions on numpyencoder
QUESTION
I want to create a network where you can hover over each label to read it interactively.
I am using jupyter lab, specs are: Selected Jupyter core packages...
...ANSWER
Answered 2021-Oct-23 at 21:18The problem seems to be that G.nodes() isn't a list of labels. You can get the node numbers or labels via converting it to a list (list(G.nodes())).
An updated version could look like:
QUESTION
I have a computationally heavy process that takes several minutes to complete in the server. So I want to send the results of every iteration to the client via websockets.
The overall application works but my problem is that all the messages are arriving at the client in one big chunk after the entire simulation finishes. I must be missing something here as I expect the await websocket.send_json() to send the message during the process and not all of them at the end.
ANSWER
Answered 2021-Aug-25 at 18:17I was not able to make it work as posted in my question, still interested in hearing from anyone who understands why it is not possible to send multiple async messages without them getting blocked.
For anyone interested, here is my current solution:
Ping pong messages from client and serverI changed the logic so the server and client are constantly sending each other messages and not trying to stream the data in a single request from the client.
This actually works much better than my original attempt because I can detect when a sockets gets disconnected and stop processing in the server. Basically, if the client disconnects, no new requests for data are sent from that client and the server never continues the heavy computation.
ServerQUESTION
Hey so i wrote a Python script to stream a webcam to a other device via UDP. But when i start the stream only the first few lines of the Image get displayed. Also even through i used the same Variable for writing the File to disk and displaying it i get diffrent results. Because in the saved image the colours are normal but in the live picture the colours are(i think) inverted. What i already tried:
- using a lan connection between the devices
- searching on google for others with the same problem
Server code:
...ANSWER
Answered 2021-Apr-07 at 21:24The frame returned value from cap.read() is just one single image from the stream, it is a matrix of size (height, width, channels), so when you do frame[0] you are getting only the first line of this matrix. Secondly, your encoding is inefficient, if you want to send one image (frame) at a time you could just dump the image file into the socket.
Here is my implementation, beware that as the receiver is single-threaded, it may loose several packets if it starts to do slow operations (such as writing to disk, computer vision). In that case you should create another thread that only to listens to that port and writes to a queue.
receive.py
QUESTION
I wish to serialize an entire class to json. However, most of the variables I need are static variables (not defined within __init__()). Is there a Pythonic way to do that, other then the naive solution, i.e., calling all variables by name?
So far, I tried to call json.dump() with an encoder to handle numpy arrays:
ANSWER
Answered 2020-Sep-14 at 16:05So, I did some research and found a solution, just in case someone get here via Google. The way to save all the class variables, even the static ones, is to call json.dump() with the class name, and not the instance name, like so:
QUESTION
I am working on a web server with a Python flask and passing data to the post method.
Let's say your Python flask web server is A, and B is a python file that sends data to server A as a post.
I planned to create a pod through deployment of A and pod as a job.
When testing on a local computer, it ran without problems and replaced only the ip address with the Kubernetes service name (to use the dns service).
But the problem is A 500 error.
I don't know what's wrong ... Please help me.
...ANSWER
Answered 2020-Jan-14 at 07:54Putting flush in the print output in the python code worked surprisingly. I don't know what the principle is.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install numpyencoder
You can use numpyencoder like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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