Initial commit: Odoo 18.0-20251222 extra-addons

web_widget_bokeh_chart/readme/CONTRIBUTORS.md

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+- Jordi Ballester Alomar \<<jordi.ballester@forgeflow.com>\>
+- Lois Rilo Antelo \<<lois.rilo@forgeflow.com>\>
+- Artem Kostyuk \<<a.kostyuk@mobilunity.com>\>
+- Christopher Ormaza \<<chris.ormaza@forgeflow.com>\>
+- Enric Tobella \<<etobella@creublanca.es>\>
+- Oriol Miranda Garrido \<<oriol.miranda@forgeflow.com>\>
+- Bernat Puig Font \<<bernat.puig@forgeflow.com>\>

web_widget_bokeh_chart/readme/CREDITS.md

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+- This module uses the library [Bokeh](https://github.com/bokeh/bokeh)
+  which is under the open-source BSD 3-clause "New" or "Revised"
+  License. Copyright (c) 2012, Anaconda, Inc.
+- Odoo Community Association (OCA)

web_widget_bokeh_chart/readme/DESCRIPTION.md

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+This module add the possibility to insert Bokeh charts into Odoo
+standard views.
+
+![Bokeh Chart inserted into an Odoo view](../static/description/example.png)
+
+[Bokeh](https://bokeh.pydata.org) is a Python interactive visualization
+library that targets modern web browsers for presentation. Its goal is
+to provide elegant, concise construction of basic exploratory and
+advanced custom graphics in the style of D3.js, but also deliver this
+capability with high-performance interactivity over very large or
+streaming datasets. Bokeh can help anyone who would like to quickly and
+easily create interactive plots, dashboards, and data applications.
+
+If you want to see some samples of bokeh's capabilities follow this
+[link](https://bokeh.pydata.org/en/latest/docs/gallery.html).

web_widget_bokeh_chart/readme/INSTALL.md

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+You need to install the python bokeh library:
+
+    pip3 install bokeh==3.1.1

web_widget_bokeh_chart/readme/ROADMAP.md

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+1.  On 17, we could remove the char field and only use the Json Field

web_widget_bokeh_chart/readme/USAGE.md

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+To insert a Bokeh chart in a view proceed as follows:
+
+## Using a Char field
+
+1.  Declare a text computed field like this:
+
+        bokeh_chart = fields.Text(
+            string='Bokeh Chart',
+            compute='_compute_bokeh_chart',
+        )
+
+2.  At the top of the module add the following imports:
+
+        from bokeh.plotting import figure
+        from bokeh.embed import components
+        import json
+
+3.  In its computed method do:
+
+        def _compute_bokeh_chart(self):
+            for rec in self:
+                # Design your bokeh figure:
+                p = figure()
+                line = p.line([0, 2], [1, 8], line_width=5)
+                # (...)
+                # fill the record field with both markup and the script of a chart.
+                script, div = components(p, wrap_script=False)
+                rec.bokeh_chart = json.dumps({"div": div, "script": script})
+
+4.  In the view, add something like this wherever you want to display
+    your bokeh chart:
+
+        <div>
+            <field name="bokeh_chart" widget="bokeh_chart" nolabel="1"/>
+        </div>
+
+## Using a Json field
+
+1.  Declare a json computed field like this:
+
+        bokeh_chart = fields.Json(
+            string='Bokeh Chart',
+            compute='_compute_bokeh_chart',
+        )
+
+2.  At the top of the module add the following imports:
+
+        from bokeh.plotting import figure
+        from bokeh.embed import components
+
+3.  In its computed method do:
+
+        def _compute_bokeh_chart(self):
+            for rec in self:
+                # Design your bokeh figure:
+                p = figure()
+                line = p.line([0, 2], [1, 8], line_width=5)
+                # (...)
+                # fill the record field with both markup and the script of a chart.
+                script, div = components(p, wrap_script=False)
+                rec.bokeh_chart = {"div": div, "script": script}
+
+4.  In the view, add something like this wherever you want to display
+    your bokeh chart:
+
+        <div>
+            <field name="bokeh_chart" widget="bokeh_chart_json