Anja Pilz aplz

## test_parameterized_exception.py
import pytest
from typing import List

def method_under_test(values: List[int]) -> int:
    """dummy method"""
    if 0 in values:
        raise(ValueError("Zeros are not supported"))
    return sum(values)

@pytest.mark.parametrize(

## numpy_vector_to_dlib_sparse_vector.py
"""How to create a sparse vector for dlib from a numpy array.

dlib: http://dlib.net/
"""
import dlib
import numpy

vector = [0,2,0]
sv = dlib.sparse_vector()
for i in numpy.nonzero(vector)[0]:

## analyze_ngram.js
GET _analyze
{
  "text": "Quick fox",
  "tokenizer": {
    "type": "ngram",
    "min_gram": 3,
    "max_gram": 4,
    "token_chars": [
      "letter",
      "digit"

## gist:f4eea39b5a5e80ca28cfeb71872f77fd
tui,label
T001,Organism
T002,Plant
T004,Fungus
T005,Virus
T007,Bacterium
T008,Animal
T010,Vertebrate
T011,Amphibian
T012,Bird

## scroll.py
# coding:utf-8

from elasticsearch import Elasticsearch
import json

# Define config
host = "127.0.0.1"
port = 9200
timeout = 1000
index = "index"

## disable_spell_checker.txt
place the line below above the offensive code part
# noinspection SpellCheckingInspection

for IDEA, the analogon is
@SuppressWarnings("SpellCheckingInspection")

## es_german_analyzer.py
es = Elasticsearch()
tokens = es.indices.analyze(
  body={"analyzer": "german",
        "text": "Die junge Informatikerin Katie Bouman machte die "
                "historische Aufnahme eines schwarzen Lochs "
                "möglich."})['tokens']
for token in tokens:
  print(token)


## bulk_upsert_generator.py
for doc in collection:
    yield {
        '_id': id, '_type': TYPE,
        '_index': index,
        # with "doc_as_upsert": True, the document is either updated
        # or created if it does not already exist.
        '_op_type': 'update', 'doc': doc, "doc_as_upsert": True
    }

## copy_directory_filtered_by_timestamp_range.sh
find . -type f -newermt '2018/10/14' -not -newermt '2018/10/21'| cpio -pvdmB <your-directory>

## copy_files_by_timestamp_range.sh
for i in `find . -type f -newermt '2018/10/14' -not -newermt '2018/10/21'`; do cp -p $i <your_folder>/; done
	import pytest
	from typing import List

	def method_under_test(values: List[int]) -> int:
	"""dummy method"""
	if 0 in values:
	raise(ValueError("Zeros are not supported"))
	return sum(values)

	@pytest.mark.parametrize(
	"""How to create a sparse vector for dlib from a numpy array.

	dlib: http://dlib.net/
	"""
	import dlib
	import numpy

	vector = [0,2,0]
	sv = dlib.sparse_vector()
	for i in numpy.nonzero(vector)[0]:
	GET _analyze
	{
	"text": "Quick fox",
	"tokenizer": {
	"type": "ngram",
	"min_gram": 3,
	"max_gram": 4,
	"token_chars": [
	"letter",
	"digit"
	tui,label
	T001,Organism
	T002,Plant
	T004,Fungus
	T005,Virus
	T007,Bacterium
	T008,Animal
	T010,Vertebrate
	T011,Amphibian
	T012,Bird
	# coding:utf-8

	from elasticsearch import Elasticsearch
	import json

	# Define config
	host = "127.0.0.1"
	port = 9200
	timeout = 1000
	index = "index"
	place the line below above the offensive code part
	# noinspection SpellCheckingInspection

	for IDEA, the analogon is
	@SuppressWarnings("SpellCheckingInspection")
	es = Elasticsearch()
	tokens = es.indices.analyze(
	body={"analyzer": "german",
	"text": "Die junge Informatikerin Katie Bouman machte die "
	"historische Aufnahme eines schwarzen Lochs "
	"möglich."})['tokens']
	for token in tokens:
	print(token)
	for doc in collection:
	yield {
	'_id': id, '_type': TYPE,
	'_index': index,
	# with "doc_as_upsert": True, the document is either updated
	# or created if it does not already exist.
	'_op_type': 'update', 'doc': doc, "doc_as_upsert": True
	}