{"id":9334,"date":"2023-08-01T09:44:22","date_gmt":"2023-08-01T07:44:22","guid":{"rendered":"https:\/\/smartdatamodels.org\/?p=9334"},"modified":"2023-08-01T09:44:22","modified_gmt":"2023-08-01T07:44:22","slug":"new-version-of-the-python-package-pysmartdatamodels-0-6-0","status":"publish","type":"post","link":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-0\/","title":{"rendered":"New Version of the Python Package pysmartdatamodels 0.6.0"},"content":{"rendered":"<div class=\"mceTemp\"><\/div>\n<p>There is a new version of the python package for <a href=\"https:\/\/pypi.org\/project\/pysmartdatamodels\/\">pysmartdatamodels 0.6.0<\/a>.<\/p>\n<p>This python package includes all the data models and several functions to use them in your developments.<\/p>\n<p>Changelog:<\/p>\n<p>&#8211; Four new functions<\/p>\n<ul>\n<li>New functions to generate fake example files given the schema payload of the data model in normalized ngsi-ld format,\u00a0 key value ngsi-ld format and geojson feature format<\/li>\n<li>New function to update a broker compliant with a specific data model<\/li>\n<\/ul>\n<p>&#8211; Acknowledgement session has been added into the README.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-9355\" src=\"https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png\" alt=\"pysmartdatamodels 0.6.0\" width=\"652\" height=\"352\" srcset=\"https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-300x162.png 300w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-1024x553.png 1024w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-768x415.png 768w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-1536x829.png 1536w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-2048x1106.png 2048w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-648x350.png 648w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-150x81.png 150w, https:\/\/smartdatamodels.org\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-01-at-09.34.53-1320x713.png 1320w\" sizes=\"auto, (max-width: 652px) 100vw, 652px\" \/><\/p>\n<p>Get more details on the pypi page and feel free to try it out!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>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: &#8211; Four new functions New functions to generate fake example files given the schema payload of the data model in&#8230; <a class=\"continue-reading-link\" href=\"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-0\/\">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":[105,107,109,113,115,119,117,88,143,111,125,182,201],"tags":[],"class_list":["post-9334","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","category-smartlogistics"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":9905,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-the-python-package-pysmartdatamodels-0-6-1\/","url_meta":{"origin":9334,"position":0},"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":8176,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-0-5-41\/","url_meta":{"origin":9334,"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 &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":[]},{"id":10356,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-python-package-0-7-1\/","url_meta":{"origin":9334,"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":8157,"url":"https:\/\/smartdatamodels.org\/index.php\/the-data-models-available-for-python-developers-pysmartdatamodels-0-5-40-published-beta-version\/","url_meta":{"origin":9334,"position":3},"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":[]},{"id":7846,"url":"https:\/\/smartdatamodels.org\/index.php\/draft-of-a-python-package-available\/","url_meta":{"origin":9334,"position":4},"title":"Draft of a python package available","author":"maestro","date":"12\/12\/2022","format":false,"excerpt":"Now we have a draft version of a python package to integrate the smart data models with your developments. It is a beta version so you can expect some issues when using it. We will be glad if you report it at info@smartdatamodels.org or suggest new features. Thanks to Anthony\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\/2022\/11\/python-logo-master-v3-TM-flattened.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2022\/11\/python-logo-master-v3-TM-flattened.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/smartdatamodels.org\/wp-content\/uploads\/2022\/11\/python-logo-master-v3-TM-flattened.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":10291,"url":"https:\/\/smartdatamodels.org\/index.php\/new-version-of-pysmartdatamodels-package-0-6-4-with-adaptations-to-data-spaces\/","url_meta":{"origin":9334,"position":5},"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 &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\/02\/pysmartdatamodels_0.6.4.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]}],"_links":{"self":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/9334","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=9334"}],"version-history":[{"count":8,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/9334\/revisions"}],"predecessor-version":[{"id":9359,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/posts\/9334\/revisions\/9359"}],"wp:attachment":[{"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/media?parent=9334"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/categories?post=9334"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartdatamodels.org\/index.php\/wp-json\/wp\/v2\/tags?post=9334"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}