WikiDataPy 0.0.1

enabling users to perform a variety of operations such as searching entities, retrieving claims, performing SPARQL queries, and even visualizing knowledge graphs.

WikidataPy

WikidataPy is a Python library designed for seamless interaction with Wikidata's knowledgebase, enabling users to perform a variety of operations such as searching entities, retrieving claims, performing SPARQL queries, and even visualizing knowledge graphs.

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Features

• Entity Search and Retrieval: Search for entities using labels, descriptions, or aliases.
• Read and Write Operations:
  • Retrieve claims and other entity details.
  • Add or edit claims and entities.
  • Perform bulk operations using CSV files.
• SPARQL Query Execution: Execute custom SPARQL queries for advanced data retrieval.
• Knowledge Graph Visualization: Visualize the relationships between entities and their properties.
• Test Environment Support: Perform operations on test.wikidata.org to avoid affecting production data.

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Installation

pip install WikiDataPy

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Usage

for Usage refer to usage scripts in github repository
each method has docstring writter for ease of understanding parameters, accepted CSV format and other things

There are 4 modules and classes in which functionality is divided and some methods provided are

1. WikiReader: searchEntities , getEntitiesByIds , getClaims , getEntitiesRelatedToGiven

2. WikiWriter: (Requires wikidata account's username, password )

   • methods: login , getCSRFtoken , logout, addClaim, removeClaims, createOrEditEntity, delete_entity(admins,moderators), setLabel, setDescription, setAliases, addRemoveAliases

     usage

     • create object : w = WikiWriter(your_username,your_password)
     • login : w.login()
     • get token: w.getCSRFtoken()
     • perform operations : w.getClaims(), w.createOrEditEntity() etc
     • logout : w.logout()

3. BulkWriter: (Requires wikidata account's username, password )

   • methods and accepted CSV format with / without header:

     • addClaimsFromCSV : <entity_id, property_id, value_id>
     • addClaimsFromNamesCSV : <entity_name, property_id, value_name>
     • createEntitiesFromCSV : <language_code_1,label_1,description_1,alias1,language_code2,label_2,description2,alias2,...>
     • editEntitiesFromCSV : <entity_id,language_code,label,description,aliases>

     usage

     • create object : w = BulkWriter(your_username,your_password)
     • login : w.login()
     • get token: w.getCSRFtoken()
     • perform operations : w.addClaimsFromNamesCSV(), w.createEntitiesFromCSV() etc
     • logout : w.logout()

4. WikiGraph: buildGraph , plotGraph (with IDs), plotNamedGraph (with names )

   • usage
     • create object : w = WikiGraph("Q42") or WikiGraph("Ronaldo")
     • call w.buildGraph(radius,out_degree) : default are (3,3)
     • call w.plotGraph() or w.plotNamedGraph() with save file name optionally

5. WikiSparql: Execute custom SPARQL queries for advanced data retrieval.

   • methods
     • execute(query) : execute single query
     • execute_many(source_text,...) : execute many queries from a text file that are delimited (default "---")
     • find_entities_by_property(pname,ename) : Fetches entities based on a specified property and entity type.

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Contributing

Contributions are welcome! Feel free to submit issues or pull requests for new features or bug fixes.

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