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This brief guide describes the basic steps for creating your first search index.
First of all you need to create an index. An index can be created in memory or on disk. An index created in memory is lost when your program exits unless it is saved to disk with the save_to method. In contrast, an index created on disk may be loaded in the future to continue working. Details on creating an index are described in the section Creating an index. The following example shows how to create an index on disk.
from groupdocs.search import Index
# Creating an index in the specified folder
index = Index("./index")
print("Index folder:", index.index_info.index_folder)
Index folder: index
To continue working with a previously created index, it must be loaded. The constructors of the Index class that take an index folder path load the index if it exists in the specified folder, and create a new index otherwise. An existing index is overwritten only if the overwrite_if_exists parameter is True, for example Index("./index", True). The constructors without a folder path, Index() and Index(settings), create a new index in memory.
The Index class is disposable. When an index is no longer needed, call its dispose method or use the index in a with statement to release the resources used by the index. The following example creates an index, closes it, and then loads the existing index from the same folder.
from groupdocs.search import Index
# Creating an index and indexing documents; the with statement releases the index
with Index("./index") as index:
index.add("./documents")
# Loading the existing index from the same folder
index = Index("./index")
print("Indexed documents:", len(index.get_indexed_documents()))
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
Indexed documents: 5
NoteSince version 26.10, an index created by a previous version cannot be opened until it is updated with the IndexUpdater class; the constructor raises RuntimeError. See Index format and compatibility.
After creating an index, you need to add documents to the index for indexing. Indexing documents can be successful or unsuccessful for various reasons, for example, due to read errors from the disk or the presence of a password to access a document. To receive information about indexing errors, you can subscribe to the error_occurred event. An event handler is a function that takes the sender and the event arguments. To work with events, see the section Search index events. The following example shows how to subscribe to the error_occurred event; the documents folder contains a password-protected document whose password is not provided.
from groupdocs.search import Index
index = Index("./index")
def on_error_occurred(sender, args):
print(args.message) # Writing error messages to the console
index.events.error_occurred += on_error_occurred
index.add("./documents")
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
Error during text extraction from documents\protected.docx
GroupDocs.Parser.Exceptions.InvalidPasswordException: Exception of type 'GroupDocs.Parser.Exceptions.InvalidPasswordException' was thrown.
at .(Stream , LoadOptions , Boolean )
at .()
at .()
at GroupDocs.Parser.Parser.GetMetadata()
at .()
at .(Document , , String )
Document indexing can be performed synchronously or asynchronously. Synchronous indexing means that a thread that started the indexing process will be busy until the operation is completed. The following example shows how to perform indexing synchronously.
from groupdocs.search import Index
index = Index("./index") # Creating an index in the specified folder
index.add("./documents") # Synchronous indexing documents from the specified folder
print("Indexed documents:", len(index.get_indexed_documents()))
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
Indexed documents: 5
More often, however, it is necessary to perform indexing asynchronously, with the ability to execute other tasks in the thread that launched the operation. A detailed description of all aspects of the indexing process is provided in the section Indexing. The following example shows how to perform indexing asynchronously. The event handler is called on an engine thread, so the example waits for the end of the operation with a threading.Event.
import threading
from groupdocs.search import Index
from groupdocs.search.options import IndexingOptions
# Creating an index
index = Index("./index")
finished = threading.Event()
# Subscribing to the event
def on_operation_finished(sender, args):
# There should be a code indicating the completion of the operation
print("Operation finished:", args.operation_type.name)
finished.set()
index.events.operation_finished += on_operation_finished
# Setting the flag for asynchronous indexing
options = IndexingOptions()
options.is_async = True
# Asynchronous indexing documents from the specified folder
# The current method terminates before the operation completes
index.add("./documents", options)
# Other tasks can be performed here; then wait for the operation to complete
finished.wait()
print("Indexed documents:", len(index.get_indexed_documents()))
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
Operation finished: INDEXING
Indexed documents: 5
When documents are indexed, the index is ready to handle search queries. The following types of search queries are supported: simple, fuzzy, case sensitive, boolean, phrase, faceted, with wildcards, and others. Description of search queries of various types is presented in the section Searching. The example below indexes documents as in the previous examples and shows how to perform simple search in an index.
from groupdocs.search import Index
index = Index("./index")
index.add("./documents")
query = "Einstein" # Specify a search query
result = index.search(query) # Searching in the index
print("Documents found:", result.document_count)
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
Documents found: 2
When a search is completed, you need to somehow interpret a result. The result can be represented by a simple list of documents found, or the words and phrases found can be highlighted in the text of the document. For more information on processing search results, see Search results. The example below shows how to list found documents in the console.
NoteIn the evaluation mode, only the first 10 found documents can be retrieved: the get_found_document method raises LicenseRestrictionException for a document number of 10 or greater. See Licensing and evaluation.
from groupdocs.search import Index
index = Index("./index")
index.add("./documents")
query = "Einstein" # Specify a search query
# Search in index
result = index.search(query)
# Printing the result
print("Documents found:", result.document_count)
print("Total occurrences found:", result.occurrence_count)
for i in range(result.document_count):
document = result.get_found_document(i)
print("\tDocument:", document.document_info.file_path)
print("\tOccurrences:", document.occurrence_count)
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
Documents found: 2
Total occurrences found: 6
Document: documents\einstein.txt
Occurrences: 4
Document: documents\nobel-prize-1921.txt
Occurrences: 2
The following example shows how to highlight search results in the text of a document. Detailed information on how to highlight search results is described in the section Highlighting search results.
import os
from groupdocs.search import Index
from groupdocs.search.common import FileOutputAdapter
from groupdocs.search.highlighters import DocumentHighlighter
from groupdocs.search.options import OutputFormat
index = Index("./index")
index.add("./documents")
query = "Einstein" # Specify a search query
result = index.search(query) # Search in the index
if result.document_count > 0:
document = result.get_found_document(0) # Getting the first found document
os.makedirs("./output", exist_ok=True)
output_adapter = FileOutputAdapter(OutputFormat.HTML, "./output/Highlighted.html") # Creating the output adapter to a file
highlighter = DocumentHighlighter(output_adapter) # Creating the highlighter object
index.highlight(document, highlighter) # Generating output HTML formatted document with highlighted search results
The following sample files are used in this example: documents/einstein.txt, documents/nobel-prize-1921.txt, documents/relativity.txt, documents/time.txt, documents/protected.docx
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>documents\einstein.txt</title>
</head>
<body>
<p>documents\einstein.txt</p>
<p></p>
<h3>filename</h3>
[TRUNCATED]
To learn more about search features and get familiar how to enhance your search solution, please refer to the advanced usage section.
You may easily run the code from documentation articles and see the features in action in our GitHub examples:
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