pympler | Development tool to measure , monitor | Machine Learning library
kandi X-RAY | pympler Summary
kandi X-RAY | pympler Summary
Before installing Pympler, try it with your Python version:. If any errors are reported, check whether your Python version is supported. Pympler is written entirely in Python, with no dependencies other than standard Python modules and libraries. Pympler works with Python 2.7, 3.5, 3.6, 3.7, 3.8 and 3.9.
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Top functions reviewed by kandi - BETA
- Start the application .
- Runs the script .
- Return a typedef object .
- Calculate the usage of a function .
- Cast response to response .
- Generate a static file .
- Add a new rule .
- Size a typedef .
- Print the class details .
- Sort the statistics .
pympler Key Features
pympler Examples and Code Snippets
Lines of Code : 6License : Strong Copyleft (CC BY-SA 4.0)
Copyfrom cllist import dllist
class DllistQueue(queue.Queue):
def _init(self, maxsize):
self.queue = dllist()
python -m pip install pympler
from pympler import asizeof
from cachetools import LRUCache
@LRUCache(MAX_BYTES, getsizeof=asizeof.asizeof)
def foo():
pass
from PyQt5 import QtCore, QtWidgets
class MainWindow(QtWidgets.QMainWindow):
def __init__(self, parent=None):
super().__init__(parent)
self.counter = 0
self.timer = QtCore.QTimer()
self.timer.timeout.from pympler import asizeof
import gc
from keras.models import Sequential
from keras.layers import Dense
model_1 = Sequential([
Dense(1, activation='relu', input_shape=(10,)),
])
gc.collect()
print('Model 1 size = ', asizeof.basicsize{
3: set(of all 9-tuples that should be prefixed by 3)
5: set(of all 9-tuples that should be prefixed by 3)
9: set(of all 9-tuples that should be prefixed by 3)
}
{
(3,7): set(of all 8-tuples that shoupip uninstall tb-nightly tensorboard tensorflow-estimator tensorflow-gpu tf-estimator-nightly
pip install tensorflow # or `tensorflow-gpu`, or `tf-nightly`, ...
import pkg_resources
for entry_point in pkg_resourtemp_df['rel_contribution'] = 0.0
temp_df['rel_contribution'] = temp_df['overlay_area']/sum(temp_df.area)
temp_df = merged_df[merged_df['seed_index'] == row['seed_index']]
# Merge datafarmepip install -r requirements.txt
conda install --yes --file requirements.txt
while read requirement; do conda install --yes $requirement; done < requirements.txt
for obj in locals().values():
print(asizeof.asizeof(obj) / 1024)
for name, obj in locals().items():
if name != 'asizeof':
print(asizeof.asizeof(obj) / 1024)
del var
del data
Community Discussions
Trending Discussions on pympler
QUESTION
I use the following code to produce what looks like a memory leak after emptying a queue with the get() method.
...ANSWER
Answered 2021-Apr-23 at 13:44If anyone looking for solution, the reason for the leak seem to be the stock python deque used in the Queue implementation. I've changed the deque implementation from the stock one found here:
https://github.com/kata198/python-cllist
Then redefined the Queue class follows:
QUESTION
I am working on this problem for several hours and can't find a solution. I am running a loop and do some calculations on a relatively big DataFrame. But with every loop, the virtual memory usage increases, until I am running out of memory. I tried manual garbage collection, setting the default thresholds of gc and libraries like pympler and objgraph to find the cause of this behaviour, but haven't been successful.
I created a minimal code example which runs out of memory in a couple of seconds on 8gb of RAM and ~7gb of paging file in a few iterations:
...ANSWER
Answered 2021-Mar-11 at 09:28Using the most up-to-date Pandas version resolved this issue. It even halved memory allocation!
QUESTION
Looking for a way to decrease the use of memory in python, I created this code
...ANSWER
Answered 2020-Dec-17 at 21:04In a normal class, __dict__ is a descriptor that provides access to an instance's attributes:
QUESTION
I'm trying to classify texts into categories. I've developed the code which does this, but kfold sample sizes differ on Spyder and Pycharm, even though the code is exactly the same.
This is the code:
...ANSWER
Answered 2020-Nov-18 at 09:00Ok, I found the problem. As I mentioned in my post, the so-called problem arises based on the versions of the libraries. And it seems, Keras now displays the batch number instead of sample count. Here are the similar posts:
QUESTION
I'm trying to build a pytorch project on an IterableDataset with zarr as storage backend.
ANSWER
Answered 2020-Sep-11 at 11:01Turns out that I had an issue in my validation routine:
QUESTION
Title is self explanatory, the toy code is shown below:
...ANSWER
Answered 2020-May-11 at 08:15In the documentation https://pympler.readthedocs.io/en/latest/library/asizeof.html it says,
If all is True and if no positional arguments are supplied. size all current gc objects, including module, global and stack frame objects.
Maybe what you're looking for is basicsize.
QUESTION
I have a "seed" GeoDataFrame (GDF)(RED) which contains a 0.5 arc minutes global grid ((180*2)*(360*2) = 259200). Each cell contains an absolute population estimate. In addition, I have a "leech" GDF (GREEN) with roughly 8250 adjoining non-regular shapes of various sizes (watersheds).
I wrote a script to allocate the population estimates to the geometries in the leech GDF based on the overlapping area between grid cells (seed GDF) and the geometries in the leech GDF. The script works perfectly fine for my sample data (see below). However, once I run it on my actual data, it is very slow. I ran it overnight and the next morning only 27% of the calculations had been performed. I will have to run this script many times and waiting for two days each time, is simply not an option.
After doing a bit of literature research, I already replaced (?) for loops with for index i in df.iterrows() (or is this the same as "conventional" python for loops) but it didn't bring about the performance imporvement I had hoped for.
Any suggestion son how I can speed up my code? In twelve hours, my script only processed only ~30000 rows out of ~200000.
My expected output is the column leech_df['leeched_values'].
ANSWER
Answered 2020-Feb-27 at 18:33It might be worthy to profile your code in details to get precise insights of what is your bottleneck.
Bellow some advises to already improve your script performance:
- Avoid
list.append(1)to count occurrences, usecollection.Counterinstead; - Avoid
pandas.DataFrame.iterrows, usepandas.DataFrame.itertuplesinstead; - Avoid extra assignation that are not needed, use
pandas.DataFrame.fillnainstead:
Eg. this line:
QUESTION
I have some code that I am running from my own package and the program is using a lot more memory (60GB) than it should be. How can I print the size of all objects (in bytes) in the current namespace in order to attempt to work out where this memory is being used?
I attempted something like
...ANSWER
Answered 2017-Oct-03 at 10:27dir() returns only the names present in the local scope. Use the locals() function to get the local scope as a dictionary:
QUESTION
I am using pympler's muppy module to retrieve information about the memory.
What I would like to do is to be able to filter down the results by object type, like so:
ANSWER
Answered 2019-Dec-16 at 10:29Try using:
QUESTION
I uninstalled my old version of spyder and installed spyder 4.0 using anaconda navigator. When I try to run spyder I get the following error message. What do I need to do to install spyder 4.0 correctly?
...ANSWER
Answered 2019-Dec-10 at 14:09Try to update numpy using the following command:
conda install -f numpy
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