semantics3 0.0.1

Setup Work

Let’s lay the groundwork.

from semantics3 import Products

# Set up a client to talk to the Semantics3 API using your Semantics3 API Credentials
products = Products(
    api_key = "SEM3xxxxxxxxxxxxxxxxxxxxxx",
    api_secret = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
)

First Query aka ‘Hello World’:

Let’s make our first query! For this query, we are going to search for all Toshiba products that fall under the category of “Computers and Accessories”, whose cat_id is 4992.

# Build the query
products.products_field( "cat_id", 4992 )
products.products_field( "brand", "Toshiba" )

# Make the query
results = products.get_products();
#or
results = products.get()

# View the results of the query
print results

Explore the Category Tree

In this example we are going to be accessing the categories endpoint. We are going to be specifically exploiring the “Computers and Accessories” category, which has a cat_id of 4992. For more details regarding our category tree and associated cat_ids check out our API docs at https://www.semantics3.com/docs

# Build the query
products.categories_field( "cat_id", 4992 );

# Execute the query
results = products.get_categories();

# View the results of the query
print results

Nested Search Query

You can intuitively construct all your complex queries but just repeatedly using the products_field() or add() methods. Here is how we translate the following JSON query:

{
    "cat_id" : 4992,
    "brand"  : "Toshiba",
    "weight" : { "gte":1000000, "lt":1500000 },
    "sitedetails" : {
        "name" : "amazon.com",
        "latestoffers" : {
            "currency": "USD",
            "price"   : { "gte" : 100 }
        }
    }
}

This query returns all Toshiba products within a certain weight range narrowed down to just those that retailed recently on amazon.com for >= USD 100.

# Build the query
products = Products( api_key, api_secret )
products.products_field( "cat_id", 4992 )
products.products_field( "brand", "Toshiba" )
products.products_field( "weight", "gte", 1000000 )
products.products_field( "weight", "lt", 1500000 )
products.products_field( "sitedetails", "name", "amazon.com" )
products.products_field( "sitedetails", "latestoffers", "currency", "USD" )
products.products_field( "sitedetails", "latestoffers", "price", "gte", 100 )
# Let's make a modification - say we no longer want the weight attribute
products.remove( "products", "weight" );

# Make the query
results = products.get_products();
print results

Pagination

The Semantics3 API allows for pagination, so you can request for, say, 5 results, and then continue to obtain the next 5 from where you stopped previously. For the python semantics3 module, we have implemented this using iterators. All you have to do is specify a cache size, and use it the same way you would any iterator:

# Specify a cache size
products.cache(5)

# Iterate through the results
for i in products.iter():
    print i

Our library will automatically request for results 5 products at a time.

Explore Price Histories

For this example, we are going to look at a particular product that is sold by select merchants and has a price of >= USD 30 and seen after a specific date (specified as a UNIX timestamp).

# Build the query
products.offers_field( "sem3_id", "4znupRCkN6w2Q4Ke4s6sUC");
products.offers_field( "seller", ["LFleurs","Frys","Walmart"] );
products.offers_field( "currency", "USD");
products.offers_field( "price", "gte", 30);
products.offers_field( "lastrecorded_at", "gte", 1348654600);



# Make the query
results = products.get_offers()

# View the results of the query
print results