doc: add MkDocs documentation (#94)
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# About
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# Explanation
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# How-to Guides
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## Installation
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tantivy-py can be installed using from [pypi](pypi.org) using pip:
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pip install tantivy
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If no binary wheel is present for your operating system the bindings will be
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build from source, this means that Rust needs to be installed before building
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can succeed.
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Note that the bindings are using [PyO3](https://github.com/PyO3/pyo3), which
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only supports python3.
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## Set up a development environment to work on tantivy-py itself
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Setting up a development environment can be done in a virtual environment using
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[`nox`](https://nox.thea.codes) or using local packages using the provided `Makefile`.
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For the `nox` setup install the virtual environment and build the bindings using:
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python3 -m pip install nox
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nox
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For the `Makefile` based setup run:
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make
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Running the tests is done using:
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make test
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## Working on tantivy-py documentation
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Please be aware that this documentation is structured using the [Diátaxis](https://diataxis.fr/) framework. In very simple terms, this framework will suggest the correct location for different kinds of documentation. Please make sure you gain a basic understanding of the goals of the framework before making large pull requests with new documentation.
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This documentation uses the [MkDocs](https://mkdocs.readthedocs.io/en/stable/) framework. This package is specified as an optional dependency in the `pyproject.toml` file. To install all optional dev dependencies into your virtual env, run the following command:
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pip install .[dev]
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The [MkDocs](https://mkdocs.readthedocs.io/en/stable/) documentation itself is comprehensive. MkDocs provides some additional context and help around [writing with markdown](https://mkdocs.readthedocs.io/en/stable/user-guide/writing-your-docs/#writing-with-markdown).
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If all you want to do is make a few edits right away, the documentation content is in the `/docs` directory and consists of [Markdown](https://www.markdownguide.org/) files, which can be edited with any text editor.
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The most efficient way to work is to run a MkDocs livereload server in the background. This will launch a local web server on your dev machine, serve the docs (by default at `http://localhost:8000`), and automatically reload the page after you save any changes to the documentation files.
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# Welcome to tantivy-py
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tantivy-py is a wrapper for the [tantivy](https://github.com/quickwit-oss/tantivy) full-text search engine, which is inspired by Apache Lucene.
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tantivy-py is [licensed](https://github.com/quickwit-oss/tantivy-py/blob/master/LICENSE) under the [MIT License](https://www.tldrlegal.com/license/mit-license).
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## Important links
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- [tantivy-py code repository](https://github.com/quickwit-oss/tantivy-py)
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- [tantivy code repository](https://github.com/quickwit-oss/tantivy)
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- [tantivy Documentation](https://docs.rs/crate/tantivy/latest)
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- [tantivy query language](https://docs.rs/tantivy/latest/tantivy/query/struct.QueryParser.html#method.parse_query)
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## How to use this documentation
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This documentation uses the [Diátaxis](https://diataxis.fr/) framework. The following sections are clearly separated:
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- [Tutorials](tutorials.md): when you want to learn
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- [How-to Guides](howto.md): when need to accomplish a task
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- [Explanation](howto.md): when you need a broader understanding and the thinking behind why certain things are set up in a particular way.
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- [Reference](reference.md): when you need precise, detailed information
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# Reference
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## Valid Query Formats
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tantivy-py supports the [query language](https://docs.rs/tantivy/latest/tantivy/query/struct.QueryParser.html#method.parse_query) used in tantivy.
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Below a few basic query formats are shown:
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- AND and OR conjunctions.
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```python
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query = index.parse_query('(Old AND Man) OR Stream', ["title", "body"])
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(best_score, best_doc_address) = searcher.search(query, 3).hits[0]
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best_doc = searcher.doc(best_doc_address)
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```
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- +(includes) and -(excludes) operators.
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```python
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query = index.parse_query('+Old +Man chef -fished', ["title", "body"])
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(best_score, best_doc_address) = searcher.search(query, 3).hits[0]
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best_doc = searcher.doc(best_doc_address)
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```
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Note: in a query like above, a word with no +/- acts like an OR.
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- phrase search.
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```python
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query = index.parse_query('"eighty-four days"', ["title", "body"])
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(best_score, best_doc_address) = searcher.search(query, 3).hits[0]
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best_doc = searcher.doc(best_doc_address)
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```
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- integer search
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```python
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query = index.parse_query('"eighty-four days"', ["doc_id"])
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(best_score, best_doc_address) = searcher.search(query, 3).hits[0]
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best_doc = searcher.doc(best_doc_address)
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```
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Note: for integer search, the integer field should be indexed.
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For more possible query formats and possible query options, see [Tantivy Query Parser Docs.](https://docs.rs/tantivy/latest/tantivy/query/struct.QueryParser.html)
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# Tutorials
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## Building an index and populating it
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```python
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import tantivy
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# Declaring our schema.
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schema_builder = tantivy.SchemaBuilder()
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schema_builder.add_text_field("title", stored=True)
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schema_builder.add_text_field("body", stored=True)
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schema_builder.add_integer_field("doc_id",stored=True)
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schema = schema_builder.build()
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# Creating our index (in memory)
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index = tantivy.Index(schema)
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```
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To have a persistent index, use the path
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parameter to store the index on the disk, e.g:
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```python
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index = tantivy.Index(schema, path=os.getcwd() + '/index')
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```
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By default, tantivy offers the following tokenizers
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which can be used in tantivy-py:
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- `default`
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`default` is the tokenizer that will be used if you do not
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assign a specific tokenizer to your text field.
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It will chop your text on punctuation and whitespaces,
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removes tokens that are longer than 40 chars, and lowercase your text.
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- `raw`
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Does not actual tokenizer your text. It keeps it entirely unprocessed.
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It can be useful to index uuids, or urls for instance.
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- `en_stem`
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In addition to what `default` does, the `en_stem` tokenizer also
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apply stemming to your tokens. Stemming consists in trimming words to
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remove their inflection. This tokenizer is slower than the default one,
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but is recommended to improve recall.
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to use the above tokenizers, simply provide them as a parameter to `add_text_field`. e.g.
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```python
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schema_builder.add_text_field("body", stored=True, tokenizer_name='en_stem')
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```
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## Adding one document.
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```python
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writer = index.writer()
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writer.add_document(tantivy.Document(
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doc_id=1,
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title=["The Old Man and the Sea"],
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body=["""He was an old man who fished alone in a skiff in the Gulf Stream and he had gone eighty-four days now without taking a fish."""],
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))
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# ... and committing
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writer.commit()
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```
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## Building and Executing Queries
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First you need to get a searcher for the index
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```python
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# Reload the index to ensure it points to the last commit.
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index.reload()
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searcher = index.searcher()
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```
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Then you need to get a valid query object by parsing your query on the index.
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```python
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query = index.parse_query("fish days", ["title", "body"])
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(best_score, best_doc_address) = searcher.search(query, 3).hits[0]
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best_doc = searcher.doc(best_doc_address)
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assert best_doc["title"] == ["The Old Man and the Sea"]
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print(best_doc)
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```
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site_name: tantivy-py
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# site_url: https://example.com
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nav:
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- Home: index.md
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- Tutorials: tutorials.md
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- How-to Guides: howto.md
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- Explanation: explanation.md
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- Reference: reference.md
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- About: about.md
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theme: readthedocs
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# Can nest documents under above sections
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# - 'User Guide':
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# - 'Writing your docs': 'writing-your-docs.md'
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# - 'Styling your docs': 'styling-your-docs.md'
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name = "tantivy"
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requires-python = ">=3.7"
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[project.optional-dependencies]
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dev = [
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"nox",
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"mkdocs",
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]
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[tool.maturin]
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bindings = "pyo3"
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