dfm

#include <Python.h>
#include <numpy/arrayobject.h>
#include "chi2.h"

/* Docstrings */
static char module_docstring[] =
    "This module provides an interface for calculating chi-squared using C.";
static char chi2_docstring[] =
    "Calculate the chi-squared of some data given a model.";

Glench

import time
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
import envoy
import os
import datetime

class NotebookConverterHandler(FileSystemEventHandler):
    def on_modified(self, event):
        if event.src_path.endswith('.ipynb'):

damianavila

"""
Usage: python remove_output.py notebook.ipynb [ > without_output.ipynb ]
Modified from remove_output by Minrk

"""
import sys
import io
import os
from IPython.nbformat.current import read, write

grenade

#!/bin/bash

# generate new personal ed25519 ssh keys
ssh-keygen -o -a 100 -t ed25519 -f ~/.ssh/id_ed25519 -C "rob thijssen <rthijssen@gmail.com>"
ssh-keygen -o -a 100 -t ed25519 -f ~/.ssh/id_robtn -C "rob thijssen <rob@rob.tn>"

# generate new host cert authority (host_ca) ed25519 ssh key
# used for signing host keys and creating host certs
ssh-keygen -t ed25519 -f manta_host_ca -C manta.network

mobilemind

# delete local tag '12345'
git tag -d 12345
# delete remote tag '12345' (eg, GitHub version too)
git push origin :refs/tags/12345
# alternative approach
git push --delete origin tagName
git tag -d tagName

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

mattfahrner

#! /usr/bin/python

import sys
import ldap
from ldap.controls import SimplePagedResultsControl
from distutils.version import LooseVersion

# Check if we're using the Python "ldap" 2.4 or greater API
LDAP24API = LooseVersion(ldap.__version__) >= LooseVersion('2.4')

vlandham

Here's a little walkthrough of how Yannick and I are using feature branches and pull requests to develop new features and adding them to the project. Below are the steps I take when working on a new feature. Hopefully this, along with watching the process on Github, will serve as a starting point to having everyone use a similar workflow.

Questions, comments, and suggestions for improvements welcome!

Start with the latest on master

When starting a new feature, I make sure to start with the latest and greatest codebase:

git checkout master

zhujunsan

What / Why

Deploy key is a SSH key set in your repo to grant client read-only (as well as r/w, if you want) access to your repo.

As the name says, its primary function is to be used in the deploy process in replace of username/password, where only read access is needed. Therefore keep the repo safe from the attack, in case the server side is fallen.

How to

1. Generate a ssh key

jnnt

#!/usr/bin/env python
#-*- coding: utf-8 -*-

# RescueTime Data Export

import os
import requests
from datetime import date, datetime
from dateutil.rrule import rrule, MONTHLY
from dateutil.parser import parse