improving speed of Python module import

you could build a simple server/client, the server running continuously making and updating the plot, and the client just communicating the next file to process.

I wrote a simple server/client example based on the basic example from the socket module docs: http://docs.python.org/2/library/socket.html#example

here is server.py:

# expensive imports
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import scipy.ndimage
import scipy.signal
import sys
import os

# Echo server program
import socket

HOST = ''                 # Symbolic name meaning all available interfaces
PORT = 50007              # Arbitrary non-privileged port
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind((HOST, PORT))
s.listen(1)
while 1:
    conn, addr = s.accept()
    print 'Connected by', addr
    data = conn.recv(1024)
    if not data: break
    conn.sendall("PLOTTING:" + data)
    # update plot
    conn.close()

and client.py:

# Echo client program
import socket
import sys

HOST = ''    # The remote host
PORT = 50007              # The same port as used by the server
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((HOST, PORT))
s.sendall(sys.argv[1])
data = s.recv(1024)
s.close()
print 'Received', repr(data)

you just run the server:

python server.py

which does the imports, then the client just sends via the socket the filename of the new file to plot:

python client.py mytextfile.txt

then the server updates the plot.

On my machine running your imports take 0.6 seconds, while running client.py 0.03 seconds.

Not an actual answer to the question, but a hint on how to profile the import speed with Python 3.7 and tuna (a small project of mine):

python3 -X importtime -c "import scipy" 2> scipy.log
tuna scipy.log