Indexing
Indexing is the organization or use of positions, keys, or lookup structures to identify and retrieve selected data or elements.
Get Programming: Learn to code with Python
- How it is used
- Selects characters and list items by position, then supplies boundaries for splitting full names.
- How deep it goes
- Works through zero-based and negative character positions plus out-of-range list errors, without exploring implementation internals.
- Examples
- Uses a grocery list and a full-name splitting program to show element access and slice boundaries.
- What you can do after
- Apply it via Python square brackets to read elements, extract name substrings, and update mutable list items.
Read how Get Programming: Learn to code with Python explains indexing →
Grokking Data Structures
An array index is the position used to identify an element within an array.
- How it is used
- Locates array elements for access, insertion, counting, traversal, and array-backed heap relationships.
- How deep it goes
- Defines positions, explains zero-based bounds and memory-location calculation, and works through insertion and counting; defers fuller heap operations.
- Examples
- Uses numbered drawers, die-roll counters, a capacity-checked Python insertion method, and parent–child positions in a heap.
- What you can do after
- Apply it via Python arrays to translate positions into valid indexes, update counters, and avoid inserting beyond capacity.
Modern C, Third Edition
Array indexing is the C operation of selecting an array element with an index expression, such as A[i].
- How it is used
- Selects array and pointer elements in initialization examples, array-processing functions, and matrix multiplication.
- How deep it goes
- Defines zero-based positions, derives indexing from pointer addition and dereferencing, then addresses parameter rewriting and bounds constraints.
- Examples
- Uses a five-element designated initializer, pointer-based summation, and indexed matrix multiplication.
- What you can do after
- Evaluate/understand it by translating `A[i]` to `*(A+i)` and checking that accesses respect array bounds.
Learn Rust in a Month of Lunches
Indexing selects elements in an ordered collection by their numeric positions.
- How it is used
- Selects an array entry by position or identifies positions for an array slice.
- How deep it goes
- Works through square-bracket indexing and slice ranges, but does not develop array operations beyond getting entries and slices.
- Examples
- Uses a three-number array to get its second item and a ten-number array to compare slice ranges.
- What you can do after
- Practice/perform array entry selection and create slices with exclusive or inclusive range endpoints.
Read how Learn Rust in a Month of Lunches explains indexing →
Pro Angular 16
An array index is a numeric position used to access an element in an array.
- How it is used
- Uses positions to read or change array elements and to identify rows generated by Angular `*ngFor`.
- How deep it goes
- Shows bracket reads and assignments, then works through zero-based `ngFor` indices, counters, and position-dependent row styling.
- Examples
- Demonstrates replacing an array’s first value and numbering product-table rows as a position out of a total.
- What you can do after
- Apply it via TypeScript brackets and Angular `*ngFor` to update array values and display row positions.
Generative AI in Action
Data indexing is the organization of stored data into searchable structures that support efficient information retrieval.
- How it is used
- Supports RAG by organizing source data for retrieval, including enterprise information unavailable in an LLM’s training data.
- How deep it goes
- Defines Redis index fields and vector settings, while also addressing data selection and source-system constraints.
- Examples
- Uses blog posts read through RSS and a Redis `posts` index with metadata and an HNSW vector field.
- What you can do after
- Configure a Redis index schema for blog content, metadata, and vector search.
Modern C
An index is an integer position used to identify an item in an array.
- How it is used
- Uses integer positions to initialize, read, and traverse array elements in C.
- How deep it goes
- Defines zero-based positions, then explains pointer arithmetic and array-parameter rewriting without reconstructing lengths.
- Examples
- Uses designated initializers, pointer-based summation, array slices, and matrix multiplication to demonstrate indexed access.
- What you can do after
- Apply it via C array notation, designated initializers, pointer arithmetic, and multidimensional function parameters.
Build AI-Enhanced Web Apps
Document indexing is the organization of document content into searchable structures for efficient information retrieval.
- How it is used
- Prepares document content for semantic retrieval in a RAG workflow.
- How deep it goes
- Details collection, chunking, embeddings, metadata, and vector storage, with code focused on directory ingestion and index creation.
- Examples
- Uses a directory of PDF files, processed into chunks and indexed with HNSWLib.
- What you can do after
- Build a semantically searchable document index using embeddings and a vector store.
Deep Learning with R, Third Edition
Indexing is the mapping of text tokens to integer positions in a vocabulary.
- How it is used
- Converts split text tokens into integer IDs as the final stage of tokenization.
- How deep it goes
- Defines indexing and demonstrates vocabulary matching, without detailing model internals.
- Examples
- Uses a sentence, a word vocabulary, and R matching to show tokens mapped to integer positions.
- What you can do after
- Apply R's match() to map split tokens to vocabulary indices, with unmatched tokens returning 0 in the example.
Read how Deep Learning with R, Third Edition explains indexing →
Deep Learning with PyTorch, Second Edition
Selecting tensor elements or slices by using tensor values as indices or masks.
- How it is used
- Supports expressive tensor manipulation and data filtering while preparing inputs for neural-network work.
- How deep it goes
- Explains list-like ranges, multidimensional slices, Boolean filtering, and storage-level indexing, but defers broader tensor operations.
- Examples
- Uses Python lists, two-dimensional points, wine-quality masks, threshold predictions, and image, text, and source-code exercises.
- What you can do after
- Apply indexing in PyTorch to slice dimensions, filter rows with Boolean masks, and compare selected data categories.
Read how Deep Learning with PyTorch, Second Edition explains indexing →
Natural Language Processing in Action, Second Edition
Indexing is the construction of auxiliary structures that organize document content for efficient retrieval.
- How it is used
- Uses inverted indexing to speed full-text keyword search and retrieve human-authored sources for LLM grounding.
- How deep it goes
- Defines forward and inverted indexes, contrasts O(1) lookup with O(n) scanning, and notes trigram handling of word variants.
- Examples
- Uses a textbook index analogy and searches for “cat” and “cats” to illustrate retrieval and exact-match limits.
- What you can do after
- Apply indexing to retrieve documents matching search terms efficiently, including variants such as “cat” and “cats.”
Read how Natural Language Processing in Action, Second Edition explains indexing →
Deep Learning with Python, Third Edition
The stage of text preprocessing that maps tokens to integer indices for numeric model input.
- How it is used
- Converts tokenized text into integer IDs for numeric model input.
- How deep it goes
- Demonstrates vocabulary lookup and unknown-token handling, then defers mapping IDs into a model's latent space.
- Examples
- Uses a word-level vocabulary to index a sentence containing an out-of-vocabulary word.
- What you can do after
- Build it from scratch by mapping vocabulary tokens to IDs and assigning a fallback ID to unknown tokens.
Read how Deep Learning with Python, Third Edition explains indexing →
Grokking Simplicity
A numeric position identifying an element within an indexed array.
- How it is used
- Uses array positions to connect searches with cart updates, removals, and reusable lower-level functions.
- How deep it goes
- Traces indexing through for loops, comparisons, null results, and arrayGet/arraySet abstractions.
- Examples
- Uses cart searches, item removal, membership checks, and price updates as concrete indexed-array examples.
- What you can do after
- Diagnose/debug with it by tracing how array positions flow from searches into updates and removals.
Python Workout, Second Edition
An index is a numeric position identifying an element within an ordered sequence.
- How it is used
- Retrieves sequence elements, extracts ranges, and pairs iteration values with numeric positions.
- How deep it goes
- Explains element access, negative positions, slice boundaries, result types, bounds, and enumerate, without descending into implementation internals.
- Examples
- Demonstrates enumerate over a string, first-and-last retrieval, list and tuple slices, and out-of-range endpoints.
- What you can do after
- Apply it via Python brackets, slices, negative positions, and enumerate to retrieve or label sequence data.
The Well-Grounded Rubyist, Fourth Edition
An index is a numeric or key-based identifier for an element in a collection, including an ordinal position in an ordered collection.
- How it is used
- Retrieves collection elements by position or key, locates substrings, and labels items with iteration counters.
- How deep it goes
- Distinguishes string search positions, array indexes, hash keys, and iteration counters, including the absence of Hash#each_index.
- Examples
- Uses substring searches, numbered president lists, and hash iteration counters to illustrate indexing.
- What you can do after
- Apply indexing to locate substrings, retrieve collection entries, and label iterated items with their ordinal positions.
Read how The Well-Grounded Rubyist, Fourth Edition explains indexing →
Related concepts
- arrayused by · An array is an indexed, ordered collection of elements arranged in one or more dimensions, with elements accessed by position.
- partial indexincludes · A partial index is a database index containing entries only for records that satisfy a specified predicate.
- covering indexincludes · A covering index is an index containing all columns needed to evaluate and return a query, avoiding access to the base table.
- tuplepart of · A tuple is a finite, ordered collection of elements treated as a single composite value or record.
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