View one_line_handler.py
import logging
class OneLineHandler(logging.StreamHandler):
def emit(self, record):
try:
msg = self.format(record)
stream = self.stream
stream.write('\u001b[1000D' + msg)
View pyav_rtmp_example.py
# -*- coding: utf8 -*-
import av
# Откроем ресурс на чтение
input_resource = av.open(
'rtmp://src_stream:1935/play'
)
# Откроем ресурс на запись.
output_resource = av.open(
View aggregate_concat.py
"""
From http://harkablog.com/inside-the-django-orm-aggregates.html
with a couple of fixes.
Usage: MyModel.objects.all().annotate(new_attribute=GroupConcat('related__attribute', separator=':')
"""
from django.db.models import Aggregate
from django.db.models.sql.aggregates import Aggregate as SQLAggregate
View dns_resolver_middleware.py
# -*- coding: utf8 -*-
from __future__ import absolute_import, division, print_function
import socket
from urlparse import urlparse
class DnsResolverMiddleware(object):
"""
View region_tree.py
from apps.genapi import models
class RegionTreeManager(models.Manager):
def handle_qs(self, qs):
not_detailed_query = "not find_in_set('detailed', Options)"
not_deleted_query = "not find_in_set('deleted', Options)"
qs = qs.extra(where=[not_detailed_query, not_deleted_query])
View bashline.sty
% !TeX encoding = UTF-8
\ProvidesPackage{bashline}[2016/10/24 v. 0.1]
\makeatletter
\newcommand{\bashline@file@name}[1]{%
/tmp/${USER}-${HOSTNAME}-\jobname-#1.tex%
}
\newread\bashline@file
\newcommand{\bashline@command@one}[2][tmp]{%
\immediate\write18{#2 > \bashline@file@name{#1}}
View dict_to_xml.py
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import lxml.etree as et
import six
def dumps(data):
name = data.keys()[0]
value = data[name]
View process_pool_executor_example.py
import itertools
import multiprocessing as mp
from concurrent.futures import ProcessPoolExecutor, as_completed
from .base_extractor import BaseExtractor
class ParallelExtractor(BaseExtractor):
POOL_SIZE = mp.cpu_count()
IMAGE_GROUP_SIZE = 512
View pyav_example.py
import av
from av.video.frame import VideoFrame
from av.video.stream import VideoStream
# В этом списке будем хранить кадры в виде numpy-векторов.
array_list = []
# Откроем контейнер на чтение
input_container = av.open('input.mp4')
View map_parallel_pymp_example.py
# Python 2.* only. For Python 3.* please use concurrent.futures.ProcessPoolExecutor
def map_parallel_pymp(obj_list, filter_list, **kwargs):
"""
Applies several filters from filter_seq
to video frames from obj_seq in parallel manner
using pymp (OpenMP for Python).
Under construction