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Apparently, it’s configurable beyond the default limits of tornado (100mb) and is already set to ~.5Gb in the default values. But by setting “max_body_size” and “max_buffer_size” in the tornado_settings dict I should be able to go past this. (Git thread: #650).
# Disable the autosave to stop chunking of the payload%autosave10000000000000#import the modulesimportnumpyasnpimportmatplotlib.cmascmimportmatplotlib.pyplotaspltimportmatplotlibasmplmpl.rcParams['figure.dpi']=800defprint_big():
''' Running this generates an image of ~26mb'''rand_array=np.random.rand(10000,10000) #create your arrayplt.imshow(rand_array,cmap=cm.bone) #show your array with the selected colourplt.show() #show the image
Then run 'print_big()' in 4 separate cells. This generates a payload of ~108mb and you get the warning: Malformed HTTP message from ::1: Content-Length too long
The text was updated successfully, but these errors were encountered:
Apparently, it’s configurable beyond the default limits of tornado (100mb) and is already set to ~.5Gb in the default values. But by setting “max_body_size” and “max_buffer_size” in the tornado_settings dict I should be able to go past this. (Git thread: #650).
To reproduce:
My Environment:
Running Mac OSX
Browser: Chrome Version 67.0.3396.99
matplotlib==2.2.2
numpy==1.15.0
Setup the server:
To generate a sufficiently large payload:
Then run 'print_big()' in 4 separate cells. This generates a payload of ~108mb and you get the warning:
Malformed HTTP message from ::1: Content-Length too long
The text was updated successfully, but these errors were encountered: