Blue Gene image attribution
Hi, readers,
Some time ago I had written this post.
pyperclip, a cool Python clipboard module
The pyperclip module allows you to programmatically copy/paste text to/from the system clipboard.
Recently, I realized that pyperclip's copy and paste functionality could be used to create a sort of rudimentary IPC (Inter Process Communication) between two Python programs running on the same machine.
So I whipped up a couple of small programs, a sender and a receiver, as a proof of concept of this idea.
Here is the sender, pyperclip_ipc_sender.py:
'''
pyperclip_ipc_sender.py
Purpose: To send JSON data to the clipboard from
a Python object.
Author: Vasudev Ram
Copyright 2018 Vasudev Ram
Web site: https://vasudevram.github.io
Blog: https://jugad2.blogspot.com
Training: https://jugad2.blogspot.com/p/training.html
Product store: https://gumroad.com/vasudevram
'''
from __future__ import print_function
import pyperclip as ppc
import json
import pprint
def generate_data():
d = {"North": 1000, "South": 2000, "East": 3000, "West": 4000}
return d
def send_data(d):
ppc.copy(json.dumps(d))
def main():
print("In pyperclip_ipc_sender.py")
print("Generating data")
d = generate_data()
print("data is:")
pprint.pprint(d)
print("Copying data to clipboard as JSON")
send_data(d)
main()
And here is the receiver, pyperclip_ipc_receiver.py:'''
pyperclip_ipc_receiver.py
Purpose: To receive JSON data from the clipboard into
a Python object and print it.
Author: Vasudev Ram
Copyright 2018 Vasudev Ram
Web site: https://vasudevram.github.io
Blog: https://jugad2.blogspot.com
Training: https://jugad2.blogspot.com/p/training.html
Product store: https://gumroad.com/vasudevram
'''
from __future__ import print_function
import pyperclip as ppc
import json
import pprint
def receive_data():
d = json.loads(ppc.paste())
return d
def main():
print("In pyperclip_ipc_receiver.py")
print("Pasting data from clipboard to Python object")
data = receive_data()
print("data is:")
pprint.pprint(data)
main()
First I ran the sender in one command window:$ python pyperclip_ipc_sender.py
In pyperclip_ipc_sender.py
data is:
{'East': 3000, 'North': 1000, 'South': 2000, 'West': 4000}
Copying data to clipboard as JSON
Then I ran the receiver in another command window:$ python pyperclip_ipc_receiver.py
In pyperclip_rpc_receiver.py
Pasting data from clipboard to Python object
data is:
{u'East': 3000, u'North': 1000, u'South': 2000, u'West': 4000}
You can see that the receiver has received the same data that was sent by the sender - via the clipboard.A few points about this technique:
- If you run the receiver without running the sender, or even before running the sender, the receiver will pick up whatever data was last put into the clipboard, either by some other program, or manually by you. For example, if you selected some text in an editor and then pressed Ctrl-C (to copy the selected text to the clipboard), the receiver would get that text (if it was JSON text - see two points below). However, that is not a bug, but a feature :)
- Obviously, this is not meant for production use, due to potential security issues. It's just a toy application as a proof of concept of this idea.
- Since I convert the Python object data to JSON in the sender before copying it to the clipboard with pyperclip, the receiver also expects the data it pastes from the clipboard into a Python object to be of type JSON. So if you instead copy some non-JSON data to the clipboard and then run the receiver, you will get an error. I tried this, and got:
ValueError: No JSON object could be decoded
To handle this gracefully, you can trap the ValueError (and maybe other kinds of exceptions that Python's json library may raise), with a try-except block around the code that pastes the data from the clipboard. You can then either tell the user to try again, or print/log the error and exit, depending on whether the receiver was an interactive or a non-interactive program.
The image at the top of the post is of an IBM Blue Gene supercomputer.
From the Wikipedia article about it:
[ The project created three generations of supercomputers, Blue Gene/L, Blue Gene/P, and Blue Gene/Q. Blue Gene systems have often led the TOP500[1] and Green500[2] rankings of the most powerful and most power efficient supercomputers, respectively. Blue Gene systems have also consistently scored top positions in the Graph500 list.[3] The project was awarded the 2009 National Medal of Technology and Innovation.[4] ]
- Enjoy.
- Vasudev Ram - Online Python training and consulting
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