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{{Project|Has project output=Tool|Has sponsor=McNair ProjectsCenter

We wanted to create a google web crawler that could collect data from web google searches specific to individual cities. The searches could be in the format of "incubator" + "city, state". It was modeled off of previous researcher's web crawler which collected information on accelerators. We could not simply modify their web crawler as it used an outdated python module.

==Beautiful Soup Implementation==When we created the web crawler, our first implementation used beautiful soup to directly "request" the url. The crawler opens took the text same input file containing a list of locations in the format "(city, state"on each line, with each entry separated by a newline. It appends the google search query domain "https://www.google.com/search?q=" to the front of the key term "incubator" newlines) and appropriately attaches formatted queries in the city and state name, using google escape characters for commas and spacessame manner. Then, using beautifulsoup, the script opens each of the generated urls and parses the resulting page to collect the titles and urls of the results. The titles and urls are data collected is stored in a csv tab separated text file in the following format* first with each row: containing city, state* second row: titles of results* third row: urls , title of results* fourth row: blankThis pattern repeats for each cityresult, state query.url

Relevant files, including python script, text files and csv files are located in E:\projects\Kauffman Incubator Project\01 Classify entrepreneurship ecosystem organizations\GoogleCrawler  This crawler was frequently blocked, as directly performed queries to google and parsed the results with beautiful soup. Additionally, this implementation would only collect eight results for each location. To prevent the crawler from being blocked and collect more results, we decided to switch and use selenium. == Things to note/What needs work ==The scraper coded using beautifulSoup does not work, it is frequently blocked by google. The scraper coded using Selenium pushes in the URL to google rather than typing in the search term and hitting enter. The Selenium script also does not collect results from multiple pages, I believe it collects results only from the first page at the moment.  == How to Run == The scripts incubator_scrape_data.py, and incubator_selenium_scrape.py were coded on a Mac in a virtualenv using python 3.6.5 The following packages were loaded into the environment for the Selenium Script:* numpy 1.16.2 * pandas 0.24.2 * pip 19.1.1 * python-dateutil 2.8.0 * pytz 2019.1 * selenium 3.141.0* setuptools 41.0.0 * six 1.12.0 * urllib3 1.24.1 * wheel 0.33.1 ==Five Cities== We retrieved the first 10 pages of results for each city in our 'five' cities. These included:*Washington, DC and surrounds:**Arlington VA**Alexandria VA**Crystal City VA**Fairfax VA**Washington DC**Springfield MD**Bethesda MD**Gaithersburg MD**Rockville MD**Frederick MD*Burlington VT*Boulder, CO and select other CO cities:**Boulder CO**Colorado Springs CO**Fort Collins CO*The Twin Cities and adjacent city:**St. Paul MN**Minneapolis MN**Bloomington MN*Austin TX