{"id":10291,"date":"2024-02-26T01:57:16","date_gmt":"2024-02-26T00:57:16","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=10291"},"modified":"2024-02-26T01:57:16","modified_gmt":"2024-02-26T00:57:16","slug":"new-version-of-pysmartdatamodels-package-0-6-4-with-adaptations-to-data-spaces","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-package-0-6-4-with-adaptations-to-data-spaces\/","title":{"rendered":"New version of pysmartdatamodels package 0.6.4 with adaptations to Data Spaces"},"content":{"rendered":"

There is a new version of the python package pysmartdatamodels<\/a><\/p>\n

to use it you have just to type<\/p>\n

pip install pysmartdatamodels<\/p>\n

in your system<\/p>\n

Besides the update in the list of data models it includes two new functions
\n– look_for_data_model<\/em><\/strong> that allows approximate searches for a data model based on their name
\n– list_datamodel_metadata<\/em><\/strong> that returns the metadata of a data model including context link, data model version, model tags, link to the schema and to the yaml version of the schema, title, description, $id, required, links to the examples, link to the adopters, link to the contributors of the subject and a link to the sql export of a data model<\/p>\n

\"\"<\/p>\n

These new functions are the result of some requests of data spaces managers and several others will be included soon to help you out in the management of the semantic contents of a data space.<\/p>\n

A code example of these two new functions<\/p>\n

from<\/span> pysmartdatamodels<\/span> import<\/span> pysmartdatamodels<\/span> as<\/span> sdm\r\n<\/span>\r\nsubject<\/span> =<\/span> \"dataModel.Weather\"<\/span>\r\ndataModel<\/span> =<\/span> \"WeatherForecast\"<\/span>\r\n# Look for a data model name <\/span>\r\nprint<\/span>(<\/span>\"22 : \"<\/span>)<\/span>\r\nprint<\/span>(<\/span>sdm<\/span>.<\/span>look_for_datamodel<\/span>(<\/span>\"WeatherFora\"<\/span>,<\/span> 84<\/span>))<\/span>\r\n# retrieve the metadata, context, version, model tags, schema, yaml schema, title, description, $id, required, examples, adopters, contributors and sql export of a data model<\/span>\r\nprint<\/span>(<\/span>\"23 : \"<\/span>)<\/span>\r\nprint<\/span>(<\/span>sdm<\/span>.<\/span>list_datamodel_metadata<\/span>(<\/span>dataModel<\/span>,<\/span> subject<\/span>))<\/span><\/pre>\n","protected":false},"excerpt":{"rendered":"
There is a new version of the python package pysmartdatamodels to use it you have just to type pip install pysmartdatamodels in your system Besides the update in the list of data models it includes two new functions – look_for_data_model that allows approximate searches for a data model based on… More…<\/a><\/p>\n","protected":false},"author":1,"featured_media":10292,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[105,107,109,113,115,119,117,88,143,111,125,182,201],"tags":[],"class_list":["post-10291","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cross-sector","category-smart-cities","category-smart-energy-domain","category-smart-environment","category-smart-manufacturing","category-smart-robotics","category-smart-water","category-smart-sensoring","category-smartaeronautics","category-smart-agrifood","category-smartdestinations","category-smarthealth","category-smartlogistics"],"jetpack_publicize_connections":[],"jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":9334,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-0\/","url_meta":{"origin":10291,"position":0},"title":"New Version of the Python Package pysmartdatamodels 0.6.0","author":"maestro","date":"01\/08\/2023","format":false,"excerpt":"There is a new version of the python package for pysmartdatamodels 0.6.0. This python package includes all the data models and several functions to use them in your developments. Changelog: - Four new functions New functions to generate fake example files given the schema payload of the data model in\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"pysmartdatamodels 0.6.0","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":8176,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-0-5-41\/","url_meta":{"origin":10291,"position":1},"title":"New version of pysmartdatamodels 0.5.41","author":"maestro","date":"30\/01\/2023","format":false,"excerpt":"There is a new version of the python package for smart data models\u00a0 pysmartdatamodels 0.5.41 Changelog: - The README include now the basic documentation of each function New function to load in a dictionary all subjects and their data models, with their repository link, and related domains New function to\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":10131,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-package-0-6-3-release\/","url_meta":{"origin":10291,"position":2},"title":"New pysmartdatamodels package 0.6.3 Release","author":"maestro","date":"02\/11\/2023","format":false,"excerpt":"We are thrilled to announce the latest update to pysmartdatamodels Python package, version 0.6.3, featuring a new function: generate_sql_schema()This addition enabling seamless generation of SQL schemas with just a few lines of code! Introducing\u00a0 generate_sql_schemqa() Function: With the new function, generate_sql_schemqa()\u00a0 pysmartdatamodels simplifies the process of creating SQL schemas for\u2026","rel":"","context":"In "Smart Cities domain"","block_context":{"text":"Smart Cities domain","link":"https:\/\/smartdatamodels.org\/index.php\/category\/smart-cities\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":10356,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-python-package-0-7-1\/","url_meta":{"origin":10291,"position":3},"title":"New version of pysmartdatamodels python package 0.7.1","author":"maestro","date":"07\/05\/2024","format":false,"excerpt":"The changes in this new version are: - Including new function validate_dcat_ap_distribution_sdm - Updating the comments of most of the functions - Some code improvements by jilin.he@fiware.org - Included a new directory with templates for the creation of a data model. Not used yet but next version they will be\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2024\/05\/pysmartdatamodels_0.7.1.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":42952,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-version-0-8-0-11-more-reliable-sql-schema-generation\/","url_meta":{"origin":10291,"position":4},"title":"New pysmartdatamodels Version 0.8.0.11: More Reliable SQL Schema Generation","author":"Agent","date":"04\/10\/2026","format":false,"excerpt":"We are happy to announce a new release of our Python package, pysmartdatamodels, version 0.8.0.11, focused on making the SQL schema generation function more robust, fixing how the package exposes its functions, and keeping our GitHub source and published package in sync. What\u2019s New in This Version? More Reliable SQL\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":43057,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-version-0-8-2-0-semantic-identification-for-data-spaces\/","url_meta":{"origin":10291,"position":5},"title":"New pysmartdatamodels Version 0.8.2.0: Semantic Identification for Data Spaces","author":"Agent","date":"09\/10\/2026","format":false,"excerpt":"We are happy to announce a new release of our Python package, pysmartdatamodels, version 0.8.2.0. The headline feature is aimed squarely at data spaces: a new function that can give semantic meaning to a payload even when the party who sent it never provided one. What\u2019s New in This Version?\u2026","rel":"","context":"In "Cross Sector"","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2026\/10\/pysmartdatamodels-300x67.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]}],"jetpack_featured_media_url":"https:\/\/smartdatamodels.org\/wp-content\/uploads\/2024\/02\/pysmartdatamodels_0.6.4.png","_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/10291","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/comments?post=10291"}],"version-history":[{"count":5,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/10291\/revisions"}],"predecessor-version":[{"id":10297,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/10291\/revisions\/10297"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media\/10292"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=10291"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/categories?post=10291"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/tags?post=10291"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}