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1. Running the spiders

#start aquarium
#In a new terminal run aquarium as root or sudo, logs will print to screen
cd /home/group9p1/aquarium
docker-compose up

#first download new alexa 1M list into the crawler directory
python read.py

#populate a section of the list for the crawler to scrape
#the populate script take a start number, end number, and a padding number
#to scrap sites 1-100 with a padding of 5
python populate.py 1 100 5

#run the spider
#In a new terminal run the spider as root or sudo, logs will print to screen and 
scrapy crawl getData


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2. Database

All scripts will be stored in /home/group9p1/javascripts/http/<url>/
Database collection 'currDB' is currently used. This can be changed by
cd  data_crawler/settings.py
change MONGODB_COLLECTION  to the new collection name

To view the database content
python client.py

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3. Training the classifier

To train the classifier with the training data set in ml/train2.csv
cd ml
python train.py

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4. Testing the classifier
cd ml
python classifier_test.py <path to test csv>

The test csv should have 28 comma separated values with an expected label at the 29th positions. The first line of the file should be of the form '<no of records>, 28'


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HELPER files:
python testClass.py :to read data from a delimiter separated list of scripts and write their features to a csv file
python read.py: update alexa list to latest in alexaUrls.txt
python client.py: print entries in mongo
checkScript.py is for running input scripts through VirusTotal