ChristopherNickels

"""
@authors: Lorenzo, Christopher
"""

from utils import read_income_statement, read_balance_sheet, read_cash_flow, companies

def fcff_forecast(comp):
    last_year = 2014
    income = read_income_statement(comp, 2009, 2014)
    ebitp = read_income_statement(comp, 2009, 2014)

ChristopherNickels

"""
@authors: Christopher, Lorenzo
"""

from utils import read_income_statement, read_balance_sheet, read_cash_flow, read_company_profile, companies

def fcff_forecast(comp):
    last_year = 2019
    income = read_income_statement(comp, 2014, 2019)
    ebit = read_income_statement(comp, 2014, 2019)

willkurt

parente

Summary

JupyterLab and Jupyter Notebook can display HTML-embedded images in notebook documents. You can use the IPython.display.HTML class to structure these images into a basic image gallery.

Example

The notebook below defines a gallery() function that accepts a list of image URLs, local image

fire-eggs

# Massages a Chrome bookmarks file into an HTML file.
#
# Features:
# - Folders are ordered alphabetically
# - Bookmarks are ordered alphabetically (by description)
# - Bookmarks are shown first, followed by folders
# - Folders can be expanded or collapsed. Initially collapsed.
# - Folders are indented nicely
# - A button is provided to expand/collapse all folders
#

dabeaz

# aproducer.py
#
# Async Producer-consumer problem.
# Challenge: How to implement the same functionality, but no threads.

import time
from collections import deque
import heapq

class Scheduler:

simonw

<?xml version="1.0" encoding="utf-8"?>
<kml xmlns="http://www.opengis.net/kml/2.2">
  <Document>
    <Placemark>
      <TimeStamp>
        <when>2015-12-18T19:12:32</when>
      </TimeStamp>
      <name>2015-12-18 19:12:32 Source: WhatsApp</name>
      <Point>
        <coordinates>-0.120970480144024,51.510383605957</coordinates>

sundowndev

Google dork cheatsheet

Search filters

Filter	Description	Example
allintext	Searches for occurrences of all the keywords given.	allintext:"keyword"
intext	Searches for the occurrences of keywords all at once or one at a time.	intext:"keyword"
inurl	Searches for a URL matching one of the keywords.	inurl:"keyword"
allinurl	Searches for a URL matching all the keywords in the query.	allinurl:"keyword"
intitle	Searches for occurrences of keywords in title all or one.	intitle:"keyword"

wkw37

iwatake2222

# -*- coding: utf-8 -*-
import cv2
import tensorflow as tf
import numpy as np

# https://www.tensorflow.org/lite/guide/hosted_models
# http://storage.googleapis.com/download.tensorflow.org/models/tflite/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.zip


def detect_from_camera():