improving speed of Python module import

Solution 1:

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

Solution 2:

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.