info.gianlucacosta.jardinero

Extensible web application for exploring natural languages


Keywords
dictionary, Wiktionary, wiki, pages, extract, terms, Python, TypeScript, React
License
MIT
Install
pip install info.gianlucacosta.jardinero==1.1.3

Documentation

Jardinero

Extensible web application for exploring natural languages

(main page screenshot)

Introduction

Natural languages are as sublime as exquisite flowers in a garden - and from such a naturalistic simile stems the name of this web application: Jardinero, meaning gardener.

I definitely needed a tool to perform morphological analysis over the Spanish language - that is, I wanted to find an answer to questions like:

Why some Spanish words end with -tad, whereas others end with -dad? What are the differences between them, in terms of both morphology and cardinality?

To solve this mystery - and several more - I decided to create Jardinero, a web application extracting my compact SQLite Spanish dictionary from Wikcionario, ready for custom SQL queries.

While developing the project, I felt it would be nice to extend the approach to any language, thus creating the whole open source architecture consisting of:

  • Eos-core - type-checked, dependency-free utility library for modern Python

  • WikiPrism - library for parsing wiki pages and creating dictionaries

  • Cervantes - WikiPrism-based library extracting a compact Spanish dictionary from Wikcionario

  • Jardinero: hybrid Python/TypeScript web application, with a Flask backend and a React frontend communicating via websockets

As a core aspect, the architecture can be easily extended by creating Python modules and packages named linguistic modules.

Main features

Jardinero's user interface enables users to:

  • create a SQLite dictionary from a wiki file - whose URL depends on the current linguistic module

  • perform queries - in SQL or even in a custom DSL - upon the internal dictionary

  • re-create the dictionary, especially when the data source gets frequent updates

(Pipeline screenshot)

Presentation on SpeakerDeck

To explore in detail how the overall architecture works, as well as the purpose and the creation process of its components, please consult my presentation on SpeakerDeck: The making of Jardinero.

(Presentation preview)

Requirements

Jardinero requires at least Python 3.10 - available at Python's official website or via your operating system's package manager.

Installation

You can install Jardinero just like any other PyPI package for your Python distribution:

pip install info.gianlucacosta.jardinero

Running Jardinero

  1. Jardinero requires a linguistic module - for example, Cervantes, dedicated to the Spanish language:

    pip install info.gianlucacosta.cervantes
  2. Jardinero should preferably be run with Python's -OO and -m command-line arguments:

    python -OO -m info.gianlucacosta.jardinero <linguistic module>

    which, in the case of Cervantes, becomes:

    python -OO -m info.gianlucacosta.jardinero info.gianlucacosta.cervantes
  3. Then, you can just point any browser to http://localhost:7000/

Running in developer mode

By omitting the -OO (and even the -O) flag, Jardinero will start in developer mode - which enables additional aspects:

  • Flask running with file watching enabled

  • More fine-grained logging

  • HTTP redirection to the frontend development server

  • Python's __debug__ global variable set to true - for example, in this case, Cervantes downloads from localhost and not from Wikcionario's official website

For simplicity, Jardinero's TOML project includes auxiliary scripts:

  • Install the frontend as an NPM package:

    poetry run poe install-frontend

    After that, to start the frontend server during development, you can run:

    poetry run poe start-frontend

    Alternatively, for better debugging introspection, you can always run yarn start on the related project - to start Webpack's dev server

  • Python's static HTTP server, serving files from your $HOME/Downloads directory:

    poetry run poe start-static

The above command lines can be further simplified if you add the following alias to your shell configuration - especially .profile for Bash:

alias poe='poetry run poe'

Once the above commands have been issued, you can just start Jardinero in development mode:

python -m info.gianlucacosta.jardinero <linguistic module>

and finally open your browser to the usual address - http://localhost:7000/

Extending Jardinero

Jardinero is designed to be extensible! I created it to explore the nuances of the Spanish language, but it can support arbitrary combinations of parameters:

  • source wiki URL - provided it points to a BZ2-compressed file

  • term-extraction algorithm from each wiki page

  • SQL schema in the SQLite db

It is definitely up to your needs and creativity! 😊

Your linguistic module can be just a Python module (or a package) - within the current Python module search path - containing these functions:

  • get_wiki_url: a () -> str function returning the URL of a BZ2-compressed XML wiki file, which in turn should have the format described in WikiPrism documentation

  • extract_terms: a (Page) -> list[TTerm] function, extracting a list of terms from a given wiki page

  • create_sqlite_dictionary: a (Connection) => SqliteDictionary[TTerm] function creating an instance of a WikiPrism SqliteDictionary from the given SQLite connection. In particular, it is the Dictionary that actually responds to queries, so you might want to design your own DSL via a custom subclass.

The exact meaning of TTerm depends on your linguistic model: to explore a real-world example, please refer to Cervantes - my library dedicated to the analysis of the Spanish language.

Final thoughts

Jardinero's core point is the web UI for creating and querying custom dictionaries, as well as its extensible engine.

Of course, there are limitations: if you need advanced features like pagination, charts, and even more analysis tools, you can still run Jardinero to create your custom SQL db, that will be stored at:

$HOME/.jardinero/<module name>/dictionary.db

Then, you can also use your favorite database explorer - such as the excellent, open source DB Browser for SQLite.

Further references

The making of Jardinero - Story of a software engineer who wanted to learn Spanish

Cervantes - Extract a compact Spanish dictionary from Wikcionario, with elegance

WikiPrism - Parse wiki pages and create dictionaries, fast, with Python

Eos-core - Type-checked, dependency-free utility library for modern Python

Special thanks