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Running Python from the Task Scheduler

Running Python from the Task Scheduler

Python, System Administration
Background Running Python from the Windows Task Scheduler is a really useful capability. It allows you to run Python in production on a Windows system, and can save countless hours of work. For instance, running code like extracting data from a database on an automated, regular basis is a common need at many companies. How to run Python from the command line Before we go into how to schedule a Python script to run, you need to understand how to run Python from the command line. To open the command prompt (command line), press the windows key and type cmd into the search box. Next, suppose your python script is called cool_python_script.py, and is saved under C:\Users. You can run this script from the command prompt by typing the below…
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RoboBrowser: Automating Online Forms

RoboBrowser: Automating Online Forms

Python, Web Scraping
Background RoboBrowser is a Python 3.x package for crawling through the web and submitting online forms. It works similarly to the older Python 2.x package, mechanize. This post is going to give a simple introduction using RoboBrowser to submit a form on Wunderground for scraping historical weather data. Initial setup RoboBrowser can be installed via pip: [code lang="python"] pip install robobrowser [/code] Let's do the initial setup of the script by loading the RoboBrowser package. We'll also load pandas, as we'll be using that a little bit later. [code lang="python"] from robobrowser import RoboBrowser import pandas as pd [/code] Create RoboBrowser Object Next, we create a RoboBrowser object. This object functions similarly to an actual web browser. It allows you to navigate to different websites, fill in forms, and get…
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Parsing Dates with Pandas

Parsing Dates with Pandas

Pandas, Python
The pandas package is one of the most powerful Python packages available. One useful feature of pandas is its Timestamp method. This provides functionality to convert strings in a variety of formats to dates. The problem we're trying to solve in this article is how to parse dates from strings that may contain additional text / words. We will look at this problem using pandas. In the first step, we'll load the pandas package. [code lang="python"] '''Load pandas package ''' import pandas as pd [/code] Next, let's create a sample string containing a made-up date with other text. For now, assume the dates will not contain spaces (we will re-examine this later). Taking this assumption, we use the split method, available for strings in Python, to create a list of…
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File Manipulation with Python

File Manipulation with Python

File Manipulation, Python, System Administration
Getting started Python is great for automating file creation, deletion, and other types of file manipulations.  Two of the primary packages used to perform these types of tasks are os and shutil.  We'll be covering a few useful highlights from each of these. [code lang="python"] import os import shutil [/code] How to get and change your current working directory You can get your current working directory using os.getcwd: [code lang="python"] os.getcwd() [/code] Any actions you take without specifying a directory will be assumed to be associated with your current working directory i.e. if you create or search for a file without specifying a directory, Python will assume you're in the value of os.getcwd(). To change your working directory, use os.chdir: [code lang="python"] os.chdir("C:/path/to/new/directory") [/code] How to merge a directory name…
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Scraping Articles About Stocks

Scraping Articles About Stocks

Python, Web Scraping
See recommended books here. The following article will show you an example of how to scrape articles about stocks from the Web using Python 3.  Specifically, we'll be looking at articles linked from http://www.nasdaq.com. If you're not familiar with list comprehensions, you may want to check this, as we'll be using them in our code. Initial, Specific Example Let's start with a specific stock -- say, Netflix, for example.  Articles linked to a specific stock ticker from Nasdaq's website have the following pattern: http://www.nasdaq.com/symbol/TICKER/news-headlines, where TICKER is replaced with whatever ticker you want.  In our case, we will start by dealing specifically with Netflix's (NFLX) stock.  So our site of interest is: http://www.nasdaq.com/symbol/nflx/news-headlines The first step is to load the requests and BeautifulSoup packages.  Here, we'll also set the variable site equal to…
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