Scrape Data Point Using Python

I am looking to scrape a data point using Python off of the url http://www.cavirtex.com/orderbook .

The data point I am looking to scrape is the lowest bid offer, which at the current moment looks like this:

<tr>
 <td><b>Jan. 19, 2014, 2:37 a.m.</b></td>
 <td><b>0.0775/0.1146</b></td>
 <td><b>860.00000</b></td>
 <td><b>66.65 CAD</b></td>
</tr>

The relevant point being the 860.00 . I am looking to build this into a script which can send me an email to alert me of certain price differentials compared to other exchanges.

I'm quite noobie so if in your explanations you could offer your thought process on why you've done certain things it would be very much appreciated.

Thank you in advance!

Edit: This is what I have so far which will return me the name of the title correctly, I'm having trouble grabbing the table data though.

import urllib2, sys
from bs4 import BeautifulSoup

site= "http://cavirtex.com/orderbook"
hdr = {'User-Agent': 'Mozilla/5.0'}
req = urllib2.Request(site,headers=hdr)
page = urllib2.urlopen(req)
soup = BeautifulSoup(page)
print soup.title



Here is the code for scraping the lowest bid from the 'Buying BTC' table:

from selenium import webdriver

fp = webdriver.FirefoxProfile()
browser = webdriver.Firefox(firefox_profile=fp)
browser.get('http://www.cavirtex.com/orderbook')

lowest_bid = float('inf')
elements = browser.find_elements_by_xpath('//div[@id="orderbook_buy"]/table/tbody/tr/td')

for element in elements:
    text = element.get_attribute('innerHTML').strip('<b>|</b>')
    try:
        bid = float(text)
        if lowest_bid > bid:
            lowest_bid = bid
    except:
        pass

browser.quit()
print lowest_bid

In order to install Selenium for Python on your Windows-PC, run from a command line:

pip install selenium (or pip install selenium --upgrade if you already have it).

If you want the 'Selling BTC' table instead, then change "orderbook_buy" to "orderbook_sell".

If you want the 'Last Trades' table instead, then change "orderbook_buy" to "orderbook_trades".

Note:

If you consider performance critical, then you can implement the data-scraping via URL-Connection instead of Selenium, and have your program running much faster. However, your code will probably end up being a lot "messier", due to the tedious XML parsing that you'll be obliged to apply...

Here is the code for sending the previous output in an email from yourself to yourself:

import smtplib,ssl

def SendMail(username,password,contents):
    server = Connect(username)
    try:
        server.login(username,password)
        server.sendmail(username,username,contents)
    except smtplib.SMTPException,error:
        Print(error)
    Disconnect(server)

def Connect(username):
    serverName = username[username.index("@")+1:username.index(".")]
    while True:
        try:
            server = smtplib.SMTP(serverDict[serverName])
        except smtplib.SMTPException,error:
            Print(error)
            continue
        try:
            server.ehlo()
            if server.has_extn("starttls"):
                server.starttls()
                server.ehlo()
        except (smtplib.SMTPException,ssl.SSLError),error:
            Print(error)
            Disconnect(server)
            continue
        break
    return server

def Disconnect(server):
    try:
        server.quit()
    except smtplib.SMTPException,error:
        Print(error)

serverDict = {
    "gmail"  :"smtp.gmail.com",
    "hotmail":"smtp.live.com",
    "yahoo"  :"smtp.mail.yahoo.com"
}

SendMail("your_username@your_provider.com","your_password",str(lowest_bid))

The above code should work if your email provider is either gmail or hotmail or yahoo.

Please note that depending on your firewall configuration, it may ask your permission upon the first time you try it...



Source: http://stackoverflow.com/questions/21217034/scrape-data-point-using-python

Data From Web Scraping Using Node.JS Request Is Different From Data Shown In The Browser

Right now, I am doing some simple web scraping, for example get the current train arrival/departure information for one railway station. Here is the example link, http://www.thetrainline.com/Live/arrivals/chester, from this link you can visit the current arrival trains in the chester station.

I am using the node.js request module to do some simple web scraping,

app.get('/railway/arrival', function (req, res, next) {
    console.log("/railway/arrival/  "+req.query["city"]);
    var city = req.query["city"];
    if(typeof city == undefined || city == undefined) { console.log("if it undefined"); city ="liverpool-james-street";}
    getRailwayArrival(city,
       function(err,data){
           res.send(data);
        }
       );
});

function getRailwayArrival(station,callback){
   request({
    uri: "http://www.thetrainline.com/Live/arrivals/"+station,
   }, function(error, response, body) {
      var $ = cheerio.load(body);

      var a = new Array();
      $(".results-contents li a").each(function() {
        var link = $(this);
        //var href = link.attr("href");
        var due = $(this).find('.due').text().replace(/(\r\n|\n|\r|\t)/gm,"");   
        var destination = $(this).find('.destination').text().replace(/(\r\n|\n|\r|\t)/gm,"");
        var on_time = $(this).find('.on-time-yes .on-time').text().replace(/(\r\n|\n|\r|\t)/gm,"");
        if(on_time == undefined)  var on_time_no = $(this).find('.on-time-no').text().replace(/(\r\n|\n|\r|\t)/gm,"");
        var platform = $(this).find('.platform').text().replace(/(\r\n|\n|\r|\t)/gm,"");

        var obj = new Object();
        obj.due = due;obj.destination = destination; obj.on_time = on_time; obj.platform = platform;
        a.push(obj);
console.log("arrival  ".green+due+"  "+destination+"  "+on_time+"  "+platform+"  "+on_time_no);      
    });
    console.log("get station data  "+a.length +"   "+ $(".updated-time").text());
    callback(null,a);

  });
}

The code works by giving me a list of data, however these data are different from the data seen in the browser, though the data come from the same url. I don't know why it is like that. is it because that their server can distinguish the requests sent from server and browser, that if the request is from server, so they sent me the wrong data. How can I overcome this problem ?

thanks in advance.

2 Answers

They must have stored session per click event. Means if u visit that page first time, it will store session and validate that session for next action you perform. Say, u select some value from drop down list. for that click again new value of session is generated that will load data for ur selected combobox value. then u click on show list then that previous session value is validated and you get accurate data.

Now see, if you not catch that session value programatically and not pass as parameter with that request, you will get default loaded data or not get any thing. So, its chalenging for you to chatch that data.Use firebug for help.

Another issue here could be that the generated content occurs through JavaScript run on your machine. jsdom is a module which will provide such content but is not as lightweight.

Cheerio does not execute these scripts and as a result content may not be visible (as you're experiencing). This is an article I read a while back and caused me to have the same discovery, just open the article and search for "jsdom is more powerful" for a quick answer:

Source:http://stackoverflow.com/questions/15785360/data-from-web-scraping-using-node-js-request-is-different-from-data-shown-in-the?rq=1

Digging Up Dollars With Data Mining - An Executive's Guide

Introduction

Traditionally, organizations use data tactically - to manage operations. For a competitive edge, strong organizations use data strategically - to expand the business, to improve profitability, to reduce costs, and to market more effectively. Data mining (DM) creates information assets that an organization can leverage to achieve these strategic objectives.

In this article, we address some of the key questions executives have about data mining. These include:

•     What is data mining?

•     What can it do for my organization?

•     How can my organization get started?

Business Definition of Data Mining

Data mining is a new component in an enterprise's decision support system (DSS) architecture. It complements and interlocks with other DSS capabilities such as query and reporting, on-line analytical processing (OLAP), data visualization, and traditional statistical analysis. These other DSS technologies are generally retrospective. They provide reports, tables, and graphs of what happened in the past. A user who knows what she's looking for can answer specific questions like: "How many new accounts were opened in the Midwest region last quarter," "Which stores had the largest change in revenues compared to the same month last year," or "Did we meet our goal of a ten-percent increase in holiday sales?"

We define data mining as "the data-driven discovery and modeling of hidden patterns in large volumes of data." Data mining differs from the retrospective technologies above because it produces models - models that capture and represent the hidden patterns in the data. With it, a user can discover patterns and build models automatically, without knowing exactly what she's looking for. The models are both descriptive and prospective. They address why things happened and what is likely to happen next. A user can pose "what-if" questions to a data-mining model that can not be queried directly from the database or warehouse. Examples include: "What is the expected lifetime value of every customer account," "Which customers are likely to open a money market account," or "Will this customer cancel our service if we introduce fees?"

The information technologies associated with DM are neural networks, genetic algorithms, fuzzy logic, and rule induction. It is outside the scope of this article to elaborate on all of these technologies. Instead, we will focus on business needs and how data mining solutions for these needs can translate into dollars.

Mapping Business Needs to Solutions and Profits

What can data mining do for your organization? In the introduction, we described several strategic opportunities for an organization to use data for advantage: business expansion, profitability, cost reduction, and sales and marketing. Let's consider these opportunities very concretely through several examples where companies successfully applied DM.

Expanding your business: Keystone Financial of Williamsport, PA, wanted to expand their customer base and attract new accounts through a LoanCheck offer. To initiate a loan, a recipient just had to go to a Keystone branch and cash the LoanCheck. Keystone introduced the $5000 LoanCheck by mailing a promotion to existing customers.

The Keystone database tracks about 300 characteristics for each customer. These characteristics include whether the person had already opened loans in the past two years, the number of active credit cards, the balance levels on those cards, and finally whether or not they responded to the $5000 LoanCheck offer. Keystone used data mining to sift through the 300 customer characteristics, find the most significant ones, and build a model of response to the LoanCheck offer. Then, they applied the model to a list of 400,000 prospects obtained from a credit bureau.

By selectively mailing to the best-rated prospects determined by the DM model, Keystone generated $1.6M in additional net income from 12,000 new customers.

Reducing costs: Empire Blue Cross/Blue Shield is New York State's largest health insurer. To compete with other healthcare companies, Empire must provide quality service and minimize costs. Attacking costs in the form of fraud and abuse is a cornerstone of Empire's strategy, and it requires considerable investigative skill as well as sophisticated information technology.

The latter includes a data mining application that profiles each physician in the Empire network based on patient claim records in their database. From the profile, the application detects subtle deviations in physician behavior relative to her/his peer group. These deviations are reported to fraud investigators as a "suspicion index." A physician who performs a high number of procedures per visit, charges 40% more per patient, or sees many patients on the weekend would be flagged immediately from the suspicion index score.

What has this DM effort returned to Empire? In the first three years, they realized fraud-and-abuse savings of $29M, $36M, and $39M respectively.

Improving sales effectiveness and profitability: Pharmaceutical sales representatives have a broad assortment of tools for promoting products to physicians. These tools include clinical literature, product samples, dinner meetings, teleconferences, golf outings, and more. Knowing which promotions will be most effective with which doctors is extremely valuable since wrong decisions can cost the company hundreds of dollars for the sales call and even more in lost revenue.

The reps for a large pharmaceutical company collectively make tens of thousands of sales calls. One drug maker linked six months of promotional activity with corresponding sales figures in a database, which they then used to build a predictive model for each doctor. The data-mining models revealed, for instance, that among six different promotional alternatives, only two had a significant impact on the prescribing behavior of physicians. Using all the knowledge embedded in the data-mining models, the promotional mix for each doctor was customized to maximize ROI.

Although this new program was rolled out just recently, early responses indicate that the drug maker will exceed the $1.4M sales increase originally projected. Given that this increase is generated with no new promotional spending, profits are expected to increase by a similar amount.

Looking back at this set of examples, we must ask, "Why was data mining necessary?" For Keystone, response to the loan offer did not exist in the new credit bureau database of 400,000 potential customers. The model predicted the response given the other available customer characteristics. For Empire, the suspicion index quantified the differences between physician practices and peer (model) behavior. Appropriate physician behavior was a multi-variable aggregate produced by data mining - once again, not available in the database. For the drug maker, the promotion and sales databases contained the historical record of activity. An automated data mining method was necessary to model each doctor and determine the best combination of promotions to increase future sales.

Getting Started

In each case presented above, data mining yielded significant benefits to the business. Some were top-line results that increased revenues or expanded the customer base. Others were bottom-line improvements resulting from cost-savings and enhanced productivity. The natural next question is, "How can my organization get started and begin to realize the competitive advantages of DM?"

In our experience, pilot projects are the most successful vehicles for introducing data mining. A pilot project is a short, well-planned effort to bring DM into an organization. Good pilot projects focus on one very specific business need, and they involve business users up front and throughout the project. The duration of a typical pilot project is one to three months, and it generally requires 4 to 10 people part-time.

The role of the executive in such pilot projects is two-pronged. At the outset, the executive participates in setting the strategic goals and objectives for the project. During the project and prior to roll out, the executive takes part by supervising the measurement and evaluation of results. Lack of executive sponsorship and failure to involve business users are two primary reasons DM initiatives stall or fall short.

In reading this article, perhaps you've developed a vision and want to proceed - to address a pressing business problem by sponsoring a data mining pilot project. Twisting the old adage, we say "just because you should doesn't mean you can." Be aware that a capability assessment needs to be an integral component of a DM pilot project. The assessment takes a critical look at data and data access, personnel and their skills, equipment, and software. Organizations typically underestimate the impact of data mining (and information technology in general) on their people, their processes, and their corporate culture. The pilot project provides a relatively high-reward, low-cost, and low-risk opportunity to quantify the potential impact of DM.

Another stumbling block for an organization is deciding to defer any data mining activity until a data warehouse is built. Our experience indicates that, oftentimes, DM could and should come first. The purpose of the data warehouse is to provide users the opportunity to study customer and market behavior both retrospectively and prospectively. A data mining pilot project can provide important insight into the fields and aggregates that need to be designed into the warehouse to make it really valuable. Further, the cost savings or revenue generation provided by DM can provide bootstrap funding for a data warehouse or related initiatives.

Source:http://ezinearticles.com/?Digging-Up-Dollars-With-Data-Mining---An-Executives-Guide&id=6052872

Automated SEO Tools Can Keep You Out of the SERPs

Every day, thousands of newcomers enter the world of internet marketing. They join all of the popular forums, follow popular advice, and purchase a bunch of tools to automate the process. While all three of these things are full of potential problems and pitfalls, it is the automated tools that have the potential to cause the greatest harm.

Why do People Buy Automated SEO Tools?

Automated SEO tools make some very grand promises. First, they promise to eliminate all of the hard work and effort that is needed to succeed with making money online. Next, they promise to give you an "edge" over your competitors. Finally, they promise to do it all for less than outsourcing.

But most of these tools don't work properly, meaning that any money you spent is money wasted. If you can't use it, you can't get any sort of return on your investment.

The few that do work properly, though, typically use techniques that are frowned upon by the search engines. They violate the terms of service, as well as commonly accepted web etiquette.

For instance, Scrape Box is a tool that is designed to find blogs on which you can comment and generate back links. It's a valuable tool if you're using it to automate the finding of relevant blogs. After that, though, it can only get you in trouble.

Just like most of these tools, Scrape Box is going to guide you through the process of creating a generic comment template. It will then assist you with "spinning" that comment, so that you can have hundreds (or even thousands) of "unique" versions.

What ends up happening, though, is that you end up with comments that resemble gibberish more than anything else. The tool then pushes these comments to blogs with links back to your website. And that's when everything goes downhill.

Search Engine Algorithms vs Automated SEO Tools

The most recent batch of algorithm updates, like Panda and Penguin, are designed to help Google better identify spam that is used for nothing other than search engine optimization. When you use Scrape Box to build and publish your content, you're spamming the web.

When Google's spiders crawl the content on these blogs and identify them as spam, they'll also note the fact that a link was sent back to your site. If you have too many of these, it will raise a red flag and your site may end up deindexed.

If you're lucky, you won't be penalized that harshly. Instead, all of your links will end up devalued. That isn't much better, though, because then the original cash investment in the tool, as well as all of the time you spent setting everything up, will be for nothing.

All of the popular SEO automation tools focus on spamming the web to build back links. This includes:

    Tools designed to automate blog comments

    Tools designed to automate article directory submissions

    Tools designed to submit your site to social bookmarking directories

    Tools designed to spin your content for uniqueness

The end results are disappointing, at best. You spend money on a tool that pushes out thousands of back links that never really help your SEO campaign. Ultimately, your site develops a back link profile that is so damaged that no amount of hard, legitimate work can ever overcome it.

Slow and Steady Wins the Race

The allure and appeal of these tools is simple to understand. They eliminate all of the hard work that would go into building a real back link profile. The problem, though, is easy to understand.

If you were to perform these tasks manually it would take a long time. But the quality of the back links you receive will far outweigh anything the automated tools could do for you.

Sure, you might not be able to manually generate a thousand back links in one day. But Google knows that, and when you do so you immediately set off a red flag. That's not how you build a solid, long lasting ranking.

By handling each step in your SEO campaign manually you will build a more natural and diverse back link footprint over time. Your rankings won't come quickly, but they'll stick for a very long time.

Source:http://ezinearticles.com/?Automated-SEO-Tools-Can-Keep-You-Out-of-the-SERPs&id=7427357

Benefits of Outsourcing Data Entry Work in India

Now Days it's a trend to outsource Data Entry Work to reliable service provider who provides excellent output out of their work. Many Companies or Organization prefer to outsource data entry work to offshore location. One of the key reasons why it's become so popular is the fact that the services they provide from highly qualified professionals with cost effective and time bound.

India is well positioned to address global BPO needs. Statistics expose that nearly half of the Fortune 800 companies believe India as a reliable target for offshore outsourcing.

There are lots of benefits of outsourcing data entry work in India

o Reduce capital costs of infrastructure
o Increase productivity and efficiency
o Reduce storage needs
o Latest standard and technology
o Extremely trained workforce
o Quick turn around time with high accuracy
o Strong quality maintained
o Saving human resources
o Focus on your core business.
o Competitive pricing which are low as 40-60% of the prevailing US costs
o Excellent training infrastructure

Data Entry is the procedure of handling and processing over data. There are different forms of data entry like data entry for survey forms, legal services, entry for medical claim forms. Data for keeping track for credit and debit card transactions.

Data entry online services include entering data into websites, e-books, entering image in different format, Data processing and submitting forms, creating database for indexing and mailing for data entered. It also used in insurance claim entry. Procedure of processing of the forms and insurances claims are kept track of data entry services. Scanned image are required for file access and credit and debit card entry.

Data Entry is one of the leading elements for running a business successfully.

Offshore Data Entry has great infrastructure for data entry work projects. We have great equipments, facilities which provide you accurate data entry with high data security. Our data entry services, data entry contract give you quality assurance.

Source:http://ezinearticles.com/?Benefits-of-Outsourcing-Data-Entry-Work-in-India&id=1269756

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product.

MLM and Network marketing company also use data extraction and data scrapping services to to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called a email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Datamining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just a other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.

Source: http://ezinearticles.com/?How-Web-Data-Extraction-Services-Will-Save-Your-Time-and-Money-by-Automatic-Data-Collection&id=5159023

How to Start an Online Data Backup Business

The data storage industry has evolved into higher levels of sophistication in managing them through secure data centers. Be it maintaining them by mammoth data grids in mine vaults or shared computers like cloud computing, businesses that have started managing third party data have grown bigger and bigger and data management has become a very lucrative industry offering the pedestal for start up software companies to join the bandwagon.

Things that start up service providers should look for in setting up a profitable business are discussed in a very prolific manner. The kind of backup service a start up venture would want to offer depends mainly on the hardware,software and proximity to the client's work site from where the data gets backed up.

Taking these factors into consideration, we as a software vendor to many managed service providers document our experience to help users be enriched with the required knowledge to compete with the myriad businesses in the same league.

First things first, one has to sell the backup service as a package that would include both on-premise and remote backup services. On premise service, as the name suggests, entails data being stored at your client's place using their own data grids. Whereas remote backup service is to have the data loaded into third party hosting like cloud computing servers where client data is transferred through the internet. The latter practice has become very popular in terms of ease of use and cost effectiveness,especially fitting to the likes of start ups who would want to offer backup service for small consumers in their locality,university and small businesses. You can vend your services either to home consumers or people running small businesses depending on your initial hardware costs.

Secondly you need to look for the right software that would suit your data needs. Some recommendations would be to install backup software that helps in smooth transfer of data from your clients computer over to the backup server. It should have all the properties that I mentioned in my earlier articles, so that you do not have to encounter hassles and mess with your client's precious data.

Beware that any fallout on your service would be squarely blamed on you by the client and would adversely hit your relationship with other clientele. Under data exigencies the software used should be able to restore the data that might have got lost in the client's computer and recovered completely as original without even a single byte of data being lost. This aspect should not be ignored as most of the software fail when it comes to restoring the data back. We see to it that the software we build is resilient to huge data transfers and does not fall apart when needed the most.

Lastly, since it is a very niche industry,you have to select your target audience proportionate to the capabilities that would help deliver seamless service even across geographies. Also you need to have a good web portal of your business that elucidates the features of the service and also the pricing for instance whether it is a basic,premium or advanced backup plan. A good support service is required to assist your customers. With these we are very sure that one would definitely succeed and grow the business to greater heights, albeit these steps are not sacrosanct, one can tailor make it to their capabilities and business goals.

Source:http://ezinearticles.com/?How-to-Start-an-Online-Data-Backup-Business&id=3620906