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Branching

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Instance	Branch

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Using Git Commit Message Templates to Write Better Commit Messages

The always enthusiastic and knowledgeable mr. @jasaltvik shared with our team an article on writing (good) Git commit messages: How to Write a Git Commit Message. This excellent article explains why good Git commit messages are important, and explains what constitutes a good commit message. I wholeheartedly agree with what @cbeams writes in his article. (Have you read it yet? If not, go read it now. I'll wait.) It's sensible stuff. So I decided to start following the

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# One liner
wget --recursive --page-requisites --adjust-extension --span-hosts --convert-links --restrict-file-names=windows --domains yoursite.com --no-parent yoursite.com

# Explained
wget \
     --recursive \ # Download the whole site.
     --page-requisites \ # Get all assets/elements (CSS/JS/images).
     --adjust-extension \ # Save files with .html on the end.
     --span-hosts \ # Include necessary assets from offsite as well.
     --convert-links \ # Update links to still work in the static version.

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import numpy as np

EPSILON = 1e-10


def _error(actual: np.ndarray, predicted: np.ndarray):
    """ Simple error """
    return actual - predicted

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layout	title	description	tags
default	SQL Style Guide	A guide to writing clean, clear, and consistent SQL.	data process

Purpose

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Specified model Django TestCase assertion

Django TestCase assert method for counting executed queries with a specified model.

Built using example from the django assertNumQueries method.

Usage:

with self.assertModelAndNumQueries([

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"""
Logical deletion for Django models. Uses is_void flag
to hide discarded items from queries. Overrides delete
methods to set flag and soft-delete instead of removing
rows from the database.
"""
from django.apps import apps
from django.contrib.admin.utils import NestedObjects
from django.db import models
from django.db.models import signals

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# You need to install scikit-learn:
# sudo pip install scikit-learn
#
# Dataset: Polarity dataset v2.0
# http://www.cs.cornell.edu/people/pabo/movie-review-data/
#
# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/19/sentiment-analysis-with-python-and-scikit-learn