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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 <code>socket</code> module docs: <a href="http://docs.python.org/2/library/socket.html#example" rel="noreferrer">http://docs.python.org/2/library/socket.html#example</a> here is server.py: <pre><code># 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() </code></pre> and client.py: <pre><code># 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) </code></pre> you just run the server: <pre><code>python server.py </code></pre> which does the imports, then the client just sends via the socket the filename of the new file to plot: <pre><code>python client.py mytextfile.txt </code></pre> then the server updates the plot. On my machine running your imports take 0.6 seconds, while running <code>client.py</code> 0.03 seconds.
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1. POimproving speed of Python module import
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1. USAndrea Zonca
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1. CObtw, for plotting, you could take a look to `chaco`: https://pypi.python.org/pypi/chaco
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2. COThanks, I think your solution is probably the way to go. I've since switched my code to PyQtGraph, because it's faster than Matplotlib at generating the dynamic plots I'm producing. Chaco is certainly worth a look too.
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