{"id":10131,"date":"2023-11-02T15:55:02","date_gmt":"2023-11-02T14:55:02","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=10131"},"modified":"2023-11-02T15:56:08","modified_gmt":"2023-11-02T14:56:08","slug":"new-pysmartdatamodels-package-0-6-3-release","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-package-0-6-3-release\/","title":{"rendered":"New pysmartdatamodels package 0.6.3 Release"},"content":{"rendered":"

We are thrilled to announce the latest update to pysmartdatamodels Python package, version 0.6.3, featuring a new function: generate_sql_schema()<\/code>This addition enabling seamless generation of SQL schemas with just a few lines of code!<\/p>\n

Introducing\u00a0 generate_sql_schemqa() Function:<\/strong><\/p>\n

With the new function, generate_sql_schemqa()\u00a0 <\/strong>pysmartdatamodels simplifies the process of creating SQL schemas for your data models by providing as input the model.yaml<\/strong> representation of a Smart Data Model.<\/p>\n","protected":false},"excerpt":{"rendered":"

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… More…<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"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}},"categories":[107,109,113,115,119,117,88,143,111,125,182,201],"tags":[],"class_list":["post-10131","post","type-post","status-publish","format-standard","hentry","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_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":10291,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-package-0-6-4-with-adaptations-to-data-spaces\/","url_meta":{"origin":10131,"position":0},"title":"New version of pysmartdatamodels package 0.6.4 with adaptations to Data Spaces","author":"maestro","date":"26\/02\/2024","format":false,"excerpt":"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\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\/02\/pysmartdatamodels_0.6.4.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":8176,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-0-5-41\/","url_meta":{"origin":10131,"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":9905,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-1\/","url_meta":{"origin":10131,"position":2},"title":"New Version of the Python Package pysmartdatamodels 0.6.1","author":"maestro","date":"09\/10\/2023","format":false,"excerpt":"There is a new version of the python package for pysmartdatamodels 0.6.1. This python package includes all the data models and several functions to use them in your developments. Changelog: - Two updated functions New extension for function update_broker() to allow updating nonexistent attribute into broker Function validate_data_model_schema(), with wider\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\/2023\/10\/Screenshot-2023-10-09-at-13.59.19-1024x685.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/10\/Screenshot-2023-10-09-at-13.59.19-1024x685.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/10\/Screenshot-2023-10-09-at-13.59.19-1024x685.png?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2023\/10\/Screenshot-2023-10-09-at-13.59.19-1024x685.png?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":32544,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-version-0-8-0-9-updated-to-1066-data-models\/","url_meta":{"origin":10131,"position":3},"title":"New pysmartdatamodels Version 0.8.0.9. Updated to 1066 data models","author":"maestro","date":"09\/03\/2026","format":false,"excerpt":"We are thrilled to announce a significant new release of our Python package, pysmartdatamodels, designed to empower developers and streamline the contribution process for our community. This update is packed with new data models till 6-3-26. Yo do not need to update the package if you use the function it\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\/03\/Screenshot-from-2026-03-07-20-55-08.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2026\/03\/Screenshot-from-2026-03-07-20-55-08.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2026\/03\/Screenshot-from-2026-03-07-20-55-08.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":9334,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-0\/","url_meta":{"origin":10131,"position":4},"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. 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Now it allows to have in the metadata of a data model the direct links to the specification in the 8 languages. you can access thanks to the function list_datamodel_metadata and accessing the objects with the keys, spec, spec_DE, spec_ES,\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\/02\/pysdm_0.6.4.1.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]}],"_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/10131","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=10131"}],"version-history":[{"count":7,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/10131\/revisions"}],"predecessor-version":[{"id":10138,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/10131\/revisions\/10138"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=10131"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/categories?post=10131"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/tags?post=10131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}