PyCon US 2015 took place in Montréal, Canada (just like last year). The videos are being uploaded to pyvideo.org. I think we need some more weeks till all the videos get uploaded but at the moment of writing this post there are already 134 videos available.
Here is a nice script of mine (
pyvideo_popularity.py) that orders presentations by popularity.
I just found this Python podcast: http://www.talkpythontome.com/. In the latest episode you can find an interview with “Jesse Davis from MongoDB. Jesse is the maintainer for a number of popular open-source projects including the Python MongoDB driver known as PyMongo and Mongo C (for C/C++ developers, yes you read right! C developers). Jesse discusses how interesting it is to write both Python and C code and how it reawakens part of the brain.” (source)
From a MongoDB collection, you want to get a random document.
import random def get_random_doc(): # coll refers to your collection count = coll.count() return coll.find()[random.randrange(count)]
Pymongo documentation on cursors: here.
I have a project where the input JSON file is almost 7 MB. I keep this project in my Dropbox folder, so that 7 MB text file seems to be a waste. Any way to reduce its size?
I zipped it up with gzip: “
gzip -9 input.json“. This command produced a 1.3 MB “input.json.gz” file and deleted the original. Good. But how to open it in Python?
Normal way (without gzip):
import json with open("input.json") as f: d = json.load(f)
Compressed way (with gzip):
import json import gzip with gzip.open("input.json.gz", "rb") as f: d = json.loads(f.read().decode("ascii"))
I didn’t notice any performance penalty. The application that first reads this json file starts as fast as before.
For creating virtual environmets, I’ve used
virtualenvwrapper so far. However, Python 3.4 contains the command
pyvenv that does the same thing. Since it also installs
pip in the virt. env., it can replace
I like to store my virtual environments in a dedicated folder, separated from the project directory. virtualenvwrapper, by default, stores the virt. env.’s in the
~/.virtualenvs folder. Since I got used to this folder, I will continue to keep my virt. env.’s in this folder.
Say we have our project folder here:
~/python/webapps/flasky_project. Create a virt. env. for this the following way:
It will create a Python 3 virt. env.
virtualenv / virtualenvwrapper
For the sake of completeness, I also write here how to create virt. env.’s with virtualenv and virtualenvwrapper:
# blog post: http://goo.gl/oEdtT3 # virtualenvwrapper for Python 3 or Python 2 mkvirtualenv -p `which python3` myenv3 mkvirtualenv -p `which python2` myenv2 # virtualenv for Python 3 or Python 2 virtualenv -p python3 myproject3 virtualenv -p python2 myproject2 # When the env. is created, activate it # and launch the command python within. # Verify if it's the correct version.
If you use Python 3.4+ and you need a virt. env., use the command “
The WordPress.com stats helper monkeys prepared a 2014 annual report for this blog.
Here's an excerpt:
The Louvre Museum has 8.5 million visitors per year. This blog was viewed about 190,000 times in 2014. If it were an exhibit at the Louvre Museum, it would take about 8 days for that many people to see it.