| class MultipleFieldLookupORMixin(object): | |
| """ | |
| Actual code http://www.django-rest-framework.org/api-guide/generic-views/#creating-custom-mixins | |
| Apply this mixin to any view or viewset to get multiple field filtering | |
| based on a `lookup_fields` attribute, instead of the default single field filtering. | |
| """ | |
| def get_object(self): | |
| queryset = self.get_queryset() # Get the base queryset | |
| queryset = self.filter_queryset(queryset) # Apply any filter backends | |
| filter = {} |
| #!/usr/bin/env python | |
| """ | |
| Recipe for creating and updating security groups programmatically. | |
| """ | |
| import collections | |
| import boto |
| from __future__ import with_statement | |
| from fabvenv import virtualenv | |
| from fabric.api import * | |
| from fabric.contrib.console import confirm | |
| # http://stackoverflow.com/questions/1180411/activate-a-virtualenv-via-fabric-as-deploy-user | |
| # http://stackoverflow.com/questions/30964502/python-fabric-nested-roles |
I'm going to cover a simple, but effective, utility for managing state and transitions (aka workflow). We often need to store the state (status) of a model and it should only be in one state at a time.
| # copied from kaggle microsoft malware classification problem discussion forum | |
| import sys | |
| import os | |
| from math import log, pow | |
| import numpy as np | |
| import scipy as sp | |
| from PIL import Image | |
| import matplotlib.pyplot as plt | |
| def saveimg(array,name): |
| https://unix.stackexchange.com/a/217720 | |
| shuf -zn<count> -e *.<file_ext_in_curnt_dir> | xargs -0 cp -vt <target_dir> | |
| shuf -zn8 -e *.jpg | xargs -0 cp -vt target/ | |
| shuf shuffles the list of *.jpg files in the current directory. | |
| -z is to zero-terminate each line, so that files with special characters are treated correctly. | |
| -n8 exits shuf after 8 files. | |
| xargs -0 reads the input delimited by a null character (from shuf -z) and runs cp. |
| from pathlib import Path | |
| from tqdm import tqdm | |
| import pydicom | |
| import numpy as np | |
| from PIL import Image | |
| sz=224 | |
| PATH = Path('big') | |
| img_dir = PATH/'image' | |
| TEST = False |
| import matplotlib.pyplot as plt | |
| import matplotlib as mpl | |
| from matplotlib.patches import Rectangle | |
| import pydicom | |
| import numpy as np | |
| import torchvision as tv | |
| img = pydicom.dcmread('/Users/nikhil/workspace/src/rsna/dcm/00aecb01-a116-45a2-956c-08d2fa55433f.dcm').pixel_array | |
| img = np.expand_dims(img, -1) | |
| img_pil = tv.transforms.functional.to_pil_image(img) |
| # see gpu usage | |
| nvidia-smi | |
| # see gpu usage every 10 sec | |
| watch -n 10 nvidia-smi | |
| #CODE | |
| #Generate root password | |
| import random, string | |
| password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20)) | |
| #Download ngrok | |
| ! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip | |
| ! unzip -qq -n ngrok-stable-linux-amd64.zip | |
| #Setup sshd |
