Square brackets are a common syntax used in programming languages to access elements in an array or list. They are used to indicate the position of an element, starting from 0. For example, in JavaScript:

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const myArray = [10, 20, 30];
console.log(myArray[1]); // Output: 20

In this example, we are accessing the second element of the array myArray using square bracket syntax with the index position of 1.

To add the last two indices of a Python list, you can use the "+" operator. Here's an example:

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# creating a list
my_list = [3, 7, 9, 2, 8]

# adding the last two indices
result = my_list[-1] + my_list[-2]

print(result) # output: 10

In this example, we have a list my_list with five integers. To add the last two indices, we first use the negative indexing to retrieve the second and last elements of the list: my_list[-1] gives us 8, and my_list[-2] gives us 2. We then simply add these together using the "+" operator and store the result in a variable called result. Finally, we print out the value of result, which is 10.

To get the last two indices in a list in Python, you can use negative indexing and slicing.

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my_list = [1, 2, 3, 4, 5, 6, 7, 8]
last_two = my_list[-2:]
print(last_two)

This will output:

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[7, 8]

In this example, we use negative indexing to get the second-to-last and last indices, and then slice the list to include both.

Coding a search engine requires a variety of skills and technologies, depending on the complexity of the search engine and its performance requirements. Generally, search engine development involves three main components: indexing, document processing and query processing.

Indexing is the process of creating an index of web documents or other text sources so that keywords can be quickly retrieved. Indexing involves constructing an inverted index, a data structure which maps terms (words or phrases) to documents that contain that term. Popular algorithms for indexing include TF-IDF and BM25.

Document processing involves processing the content of web documents and other text sources. Processing includes tasks such as stop word filtering, part-of-speech tagging and stemming, which help increase the precision of the search engine results.

Query processing identifies the relevant documents to a user query, by reading through the index. Popular algorithms for query processing include vector space and language models.

Search engines are usually built using programming languages such as Java, C# or Python. Web frameworks and libraries such as Apache Solr or Lucene can help with developing a search engine. Additionally, there are a variety of off-the-shelf search engines such as Elasticsearch and Endeca.