marazmiki

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

import argparse
import os
import sys
import time
import atexit
import logging
import signal

Makefile

all : laplace.so

laplace.so : laplace.h laplace.c
	gcc -O3 -fopenmp -fPIC -c laplace.c
	gcc -O3 -fopenmp -fPIC -shared -o liblaplace.so laplace.o
	rm -f laplace.o

clean:
	rm -f laplace.so

staticfloat

Julia Debugging Procedures

So you managed to break Julia. Congratulations! Collected here are some general procedures you can undergo for common symptoms encountered when something goes awry. Including the information from these debugging steps can greatly help the maintainers when tracking down a segfault or trying to figure out why your script is running slower than expected.

If you've been directed to this page, find the symptom that best matches what you're experiencing and follow the instructions to generate the debugging information requested. Table of symptoms:

• Segfaults during bootstrap (sysimg.jl)

• Segfaults when running a script

helgee

program doptest

implicit none

double precision :: x
double precision :: xend
double precision, dimension(1) :: rtol
double precision, dimension(1) :: atol
double precision, dimension(6) :: y
double precision, dimension(6) :: y1

takluyver

Copy nbflatten.py to somewhere on $PATH. Then, in the root of a git repository, run these commands:

echo "*.ipynb diff=ipynb" >> .gitattributes 
git config diff.ipynb.textconv nbflatten.py

When you change a notebook and run git diff, you'll see the diff of flattened, simplified notebooks, rather than the full JSON. This does lose some information (metadata, non-text output), but it makes it easier to see simple changes in the notebook.

This doesn't help with merging conflicting changes in notebooks. For that, see nbdiff.org.

jakevdp

# By Jake VanderPlas
# License: BSD-style

import matplotlib.pyplot as plt
import numpy as np


def discrete_cmap(N, base_cmap=None):
    """Create an N-bin discrete colormap from the specified input map"""

jfeist

#!/bin/sh
jq -r 'def banner: "\(.) " + (28-(.|length))*"-";
("Non-cell info" | banner), del(.cells), "",
(.cells[] |  ("\(.cell_type) cell" | banner),
	     "\(.source|add)",
	     if ($show_output == "1") then
                 "",
		 ( select(.cell_type=="code" and (.outputs|length)>0) |
		   ("output" | banner),
		   (.outputs[] |

gioper86

from cassandra.cluster import Cluster
from cassandra.auth import PlainTextAuthProvider
import pandas as pd

def pandas_factory(colnames, rows):
    return pd.DataFrame(rows, columns=colnames)

cluster = Cluster(
    contact_points=['127.0.0.1'], 
    auth_provider = PlainTextAuthProvider(username='cassandra', password='cassandra')

whizzzkid

# Instructions for 4.14 and cuda 9.1
# If upgrading from 4.13 and cuda 9.0
$ sudo apt-get purge --auto-remove libcud*
$ sudo apt-get purge --auto-remove cuda*
$ sudo apt-get purge --auto-remove nvidia*
# also remove the container directory direcotory at /usr/local/cuda-9.0/

# Important libs required with 4.14.x with Cuda 9.X
$ sudo apt install libelf1 libelf-dev

alexanderhupfer

# Plot logtime in realtime using bokeh and tail -f
# Tested with python 3.5 and bokeh 0.12.4
# OSX/Linux only
# usage:
# 1. run 'bokeh serve'
# 2. run 'python3.5 main.py logfile.csv'
# assumes a logfile.csv with format:
# min_ask,1489758134.150000,1077.00,1076.78,0.45
# max_bid,1489758139.660000,1076.56,1076.76,0.41
# min_ask,1489758142.076000,1076.95,1076.76,0.40