{"id":8176,"date":"2023-01-30T08:53:56","date_gmt":"2023-01-30T07:53:56","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=8176"},"modified":"2023-01-29T03:58:23","modified_gmt":"2023-01-29T02:58:23","slug":"new-version-of-pysmartdatamodels-0-5-41","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-0-5-41\/","title":{"rendered":"New version of pysmartdatamodels 0.5.41"},"content":{"rendered":"<p>There is a new version of the python package for <a href=\"https:\/\/pypi.org\/project\/pysmartdatamodels\/0.5.41\/\">smart data models\u00a0 pysmartdatamodels 0.5.41<\/a><\/p>\n<p>Changelog:<\/p>\n<p>&#8211; The README include now the basic documentation of each function<\/p>\n<ul>\n<li>New function to load in a dictionary all subjects and their data models, with their repository link, and related domains<\/li>\n<li>New function to load in a dictionary all the attributes in every data model including\u00a0 name of the property, data type, NGSI type, description, units, et<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>There is a new version of the python package for smart data models\u00a0 pysmartdatamodels 0.5.41 Changelog: &#8211; 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&#8230; <a class=\"continue-reading-link\" href=\"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-0-5-41\/\">More&#8230;<\/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":[105,107,109,113,115,119,117,88,143,111,125,182],"tags":[],"class_list":["post-8176","post","type-post","status-publish","format-standard","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"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":10131,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-package-0-6-3-release\/","url_meta":{"origin":8176,"position":0},"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 &quot;Smart Cities domain&quot;","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":32544,"url":"https:\/\/smartdatamodels.org\/index.php\/new-pysmartdatamodels-version-0-8-0-9-updated-to-1066-data-models\/","url_meta":{"origin":8176,"position":1},"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 &quot;Cross Sector&quot;","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":10356,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-python-package-0-7-1\/","url_meta":{"origin":8176,"position":2},"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 &quot;Cross Sector&quot;","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":9905,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-1\/","url_meta":{"origin":8176,"position":3},"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 &quot;Cross Sector&quot;","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":9334,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-0\/","url_meta":{"origin":8176,"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. 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 &quot;Cross Sector&quot;","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":8157,"url":"https:\/\/smartdatamodels.org\/index.php\/the-data-models-available-for-python-developers-pysmartdatamodels-0-5-40-published-beta-version\/","url_meta":{"origin":8176,"position":5},"title":"The data models available for python developers. pysmartdatamodels 0.5.40 published. Beta version.","author":"maestro","date":"27\/01\/2023","format":false,"excerpt":"Now you can find in pypi.org the python package pysmartdatamodels with 13 functions for the integrators of the data models (more than 800) in external systems and applications. It is a beta version. There is a function, update_data() that whenever is run, it updates the data models to the last\u2026","rel":"","context":"In &quot;Cross Sector&quot;","block_context":{"text":"Cross Sector","link":"https:\/\/smartdatamodels.org\/index.php\/category\/cross-sector\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/8176","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=8176"}],"version-history":[{"count":1,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/8176\/revisions"}],"predecessor-version":[{"id":8177,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/8176\/revisions\/8177"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=8176"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/categories?post=8176"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/tags?post=8176"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}