feat: plotly express

The histograms, heatmaps and comparisons have been replaced with interactive Plotly graphs.
Plotly.js is used to build the graphs on the go from JSON. Initial tests show that plotly
reports are smaller in size compared to matplotlib and the takes way less time for report
generation compared to matplotlib. use parameter 'online_report' to use plotly.js from CDN
 server and use report online. Else, plotly.js is embedded in the report and can be used
 offline too.

BREAKING CHANGE: matplotlib-related config is removed

Author: pradyot-09

NOTICE

@@ -21,7 +21,7 @@
 # pyyaml: https://github.com/yaml/pyyaml/blob/master/LICENSE
 # jinja2: https://github.com/noirbizarre/jinja2/blob/master/LICENSE
 # tqdm: https://github.com/tqdm/tqdm/blob/master/LICENCE
-# matplotlib: https://github.com/matplotlib/matplotlib/blob/master/LICENSE/LICENSE
+# plotly: https://github.com/plotly/plotly.py/blob/master/LICENSE.txt
 # joblib: https://github.com/joblib/joblib/blob/master/LICENSE.txt
 # pybase64: https://github.com/mayeut/pybase64/blob/master/LICENSE
 # htmlmin: https://github.com/mankyd/htmlmin/blob/master/LICENSE

popmon/config.py

@@ -29,9 +29,6 @@
 # (see https://joblib.readthedocs.io/en/latest/generated/joblib.Parallel.html for details)
 parallel_args = {"n_jobs": 1}
 
-# Usage the `ing_matplotlib_theme`
-themed = True
-
 
 class SectionModel(BaseModel):
     name: str
@@ -108,7 +105,7 @@ class HistogramSectionModel(SectionModel):
     top_n: int = 20
     """plot heatmap for top 'n' categories. default is 20 (optional)"""
 
-    cmap: str = "autumn_r"
+    cmap: str = "ylorrd"
     """colormap for histogram heatmaps"""
 
 
@@ -171,6 +168,9 @@ class Report(BaseModel):
     """if True, show all the generated statistics in the report (optional)
     if set to False, then smaller show_stats (see below)"""
 
+    online_report: bool = True
+    """Use a CDN to host resources, or embed them into the report."""
+
     show_stats: List[str] = [
         "distinct*",
         "filled*",
@@ -194,6 +194,9 @@ class Report(BaseModel):
     ]
     """list of statistic name patterns to show in the report. If None, show all (optional)"""
 
+    zline_color: List[str] = ["#FF0000", "#FFC800"]
+    """"Configure line colors in barplots of Comparisons and Profiles section. First and second elements as hex color code in list will replace the default red and yellow respectively"""
+
     section: Section = Section()
     """Configuration for the individual sections"""
 

popmon/notebooks/popmon_tutorial_advanced.ipynb

@@ -467,7 +467,11 @@
     "                store_key=\"report_sections\",\n",
     "                settings=report_settings,\n",
     "            ),\n",
-    "            ReportGenerator(read_key=\"report_sections\", store_key=\"html_report\"),\n",
+    "            ReportGenerator(\n",
+    "                read_key=\"report_sections\",\n",
+    "                store_key=\"html_report\",\n",
+    "                settings=report_settings,\n",
+    "            ),\n",
     "        ]\n",
     "        super().__init__(modules)\n",
     "\n",
@@ -525,7 +529,11 @@
     "                store_key=\"report_sections\",\n",
     "                settings=report_settings,\n",
     "            ),\n",
-    "            ReportGenerator(read_key=\"report_sections\", store_key=\"html_report\"),\n",
+    "            ReportGenerator(\n",
+    "                read_key=\"report_sections\",\n",
+    "                store_key=\"html_report\",\n",
+    "                settings=report_settings,\n",
+    "            ),\n",
     "        ]\n",
     "        super().__init__(modules)\n",
     "\n",

popmon/pipeline/report_pipelines.py

@@ -233,7 +233,9 @@ def __init__(
                 settings=settings,
             ),
             # generate report
-            ReportGenerator(read_key=sections_key, store_key=store_key),
+            ReportGenerator(
+                read_key=sections_key, store_key=store_key, settings=settings
+            ),
         ]
         if (
             isinstance(settings.report_filepath, (str, Path))

popmon/resources.py

@@ -19,7 +19,7 @@
 
 
 # Resources lookup file for popmon
-
+import json
 import pathlib
 
 from jinja2 import Environment, FileSystemLoader
@@ -53,6 +53,31 @@
 _TEMPLATES_ENV.filters["fmt_metric"] = lambda x: x.replace("_", " ")
 
 
+def js_list(encoder, data):
+    pairs = [js_val(encoder, v) for v in data]
+    return "[" + ", ".join(pairs) + "]"
+
+
+def js_dict(encoder, data):
+    pairs = [k + ": " + js_val(encoder, v) for k, v in data.items()]
+    return "{" + ", ".join(pairs) + "}"
+
+
+def js_val(encoder, data):
+    if isinstance(data, dict):
+        val = js_dict(encoder, data)
+    elif isinstance(data, list):
+        val = js_list(encoder, data)
+    else:
+        val = encoder.encode(data)
+    return val
+
+
+_TEMPLATES_ENV.filters["json_plot"] = lambda x: js_val(
+    json.JSONEncoder(ensure_ascii=False), x
+)
+
+
 def _resource(resource_type, name: str) -> str:
     """Return the full path filename of a resource.
 

popmon/visualization/__init__.py

@@ -28,13 +28,6 @@
     TrafficLightSectionGenerator,
 )
 
-# set matplotlib backend to batch mode when running in shell
-# need to do this *before* matplotlib.pyplot gets imported
-from ..visualization.backend import set_matplotlib_backend
-
-set_matplotlib_backend()
-
-
 __all__ = [
     "SectionGenerator",
     "HistogramSection",

popmon/visualization/alert_section_generator.py

@@ -150,7 +150,11 @@ def transform(
                 plots = [e for e in plots if len(e["plot"])]
 
             features_w_metrics.append(
-                {"name": feature, "plots": sorted(plots, key=lambda plot: plot["name"])}
+                {
+                    "name": feature,
+                    "plot_type_layouts": {"traffic_lights": ""},
+                    "plots": sorted(plots, key=lambda plot: plot["name"]),
+                }
             )
 
         sections.append(

popmon/visualization/backend.py

@@ -140,17 +140,33 @@ def transform(self, data_obj: dict, sections: Optional[list] = None):
             ]
             plots = parallel(_plot_histograms, args)
 
+            plot_type_layouts = {}
+
             # filter out potential empty plots
             plots = [e for e in plots if len(e["plot"])]
             plots = sorted(plots, key=lambda plot: plot["name"])
+            if len(plots) > 0:
+                plot_type_layouts["histogram"] = plots[0]["layout"]
 
             # filter out potential empty heatmap plots, then prepend them to the sorted histograms
-            hplots = [h for h in heatmaps if isinstance(h, dict) and len(h["plot"])]
-
-            plots = hplots + plots
+            hplots = []
+            for h in heatmaps:
+                if isinstance(h, dict):
+                    if len(h["plot"]):
+                        hplots.append(h)
 
-            features_w_metrics.append({"name": feature, "plots": plots})
+            if len(hplots) > 0:
+                plot_type_layouts["heatmap"] = hplots[0]["layout"]
 
+            plots = hplots + plots
+            # print(plot_types,layouts)
+            features_w_metrics.append(
+                {
+                    "name": feature,
+                    "plot_type_layouts": plot_type_layouts,
+                    "plots": plots,
+                }
+            )
         sections.append(
             {
                 "section_title": self.section_name,
@@ -230,11 +246,17 @@ def _plot_histograms(feature, date, hc_list, hist_names, top_n, max_nbins=1000):
             hists, feature, hist_names, y_label, is_num, is_ts
         )
     elif hc_list[0].n_dim == 2:
-        plot = ""
+        plot = {}
     else:
-        plot = ""
+        plot = {}
 
-    return {"name": date, "description": "", "plot": plot}
+    return {
+        "name": date,
+        "type": "histogram",
+        "description": "",
+        "plot": plot.get("data", ""),
+        "layout": plot.get("layout", ""),
+    }
 
 
 def _plot_heatmap(
@@ -321,13 +343,15 @@ def _plot_heatmap(
         if isinstance(heatmaps, list):
             plot = [hist_lookup(heatmaps, hist_name) for hist_name in hist_names]
         elif isinstance(heatmaps, dict):
-            plot = [heatmaps["plot"]]
+            plot = [heatmaps]
 
         plots = [
             {
                 "name": hist_names_formatted[hist_name],
-                "description": descriptions[hist_name],
-                "plot": pl,
+                "type": "heatmap",
+                "description": "",
+                "plot": pl["plot"],
+                "layout": pl["layout"],
                 "full_width": True,
             }
             for pl, hist_name in zip(plot, hist_names)
@@ -364,4 +388,4 @@ def get_top_categories(entries_list, bins, top_n):
 def hist_lookup(plot, hist_name):
     for pl in plot:
         if pl["name"] == hist_name:
-            return pl["plot"]
+            return pl

popmon/visualization/histogram_section.py

@@ -177,6 +177,7 @@ def _plot_metrics(
 
     return {
         "name": "Alert frequency per Feature",
+        "type": "alert",
         "description": "",
         "plot": plot,
         "full_width": True,