Update HTML reports using Github Actions (#63)

* Github Actions for building examples as artifacts

.github/workflows/build.yml

@@ -11,7 +11,6 @@ on:
 
 jobs:
   build:
-
     runs-on: ubuntu-latest
 
     steps:
@@ -35,3 +34,34 @@ jobs:
       run: |
         pip install pytest
         pytest
+
+  examples:
+    runs-on: ubuntu-latest
+    needs: build
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.6
+        uses: actions/setup-python@v1
+        with:
+          python-version: 3.6
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e .
+      - name:
+        run: |
+          cd examples
+          python synthetic_data.py
+          python flight_delays.py
+
+      - uses: actions/upload-artifact@v2
+        with:
+          name: synthetic-report
+          path: examples/test_data_report.html
+          if-no-files-found: error
+
+      - uses: actions/upload-artifact@v2
+        with:
+          name: flight-delays-report
+          path: examples/flight_delays_report.html
+          if-no-files-found: error

examples/flight_delays.py

@@ -0,0 +1,22 @@
+import pandas as pd
+
+import popmon
+from popmon import resources
+
+# open synthetic data
+df = pd.read_csv(
+    resources.data("flight_delays.csv.gz"), index_col=0, parse_dates=["DATE"]
+)
+
+# generate stability report using automatic binning of all encountered features
+# (importing popmon automatically adds this functionality to a dataframe)
+report = df.pm_stability_report(
+    time_axis="DATE",
+    time_width="1w",
+    time_offset="2015-07-02",
+    extended_report=False,
+    pull_rules={"*_pull": [10, 7, -7, -10]},
+)
+
+# or save the report to file
+report.to_file("flight_delays_report.html")

examples/synthetic_data.py

@@ -0,0 +1,14 @@
+import pandas as pd
+
+import popmon
+from popmon import resources
+
+# open synthetic data
+df = pd.read_csv(resources.data("test.csv.gz"), parse_dates=["date"])
+
+# generate stability report using automatic binning of all encountered features
+# (importing popmon automatically adds this functionality to a dataframe)
+report = df.pm_stability_report(time_axis="date", features=["date:age", "date:gender"])
+
+# or save the report to file
+report.to_file("test_data_report.html")

popmon/notebooks/popmon_tutorial_advanced.ipynb

@@ -14,7 +14,8 @@
    },
    "outputs": [],
    "source": [
-    "from IPython.core.display import display, HTML\n",
+    "from IPython.core.display import HTML, display\n",
+    "\n",
     "display(HTML(\"<style>.container { width:80% !important; }</style>\"))\n",
     "display(HTML(\"<style>div.output_scroll { height: 44em; }</style>\"))"
    ]
@@ -27,6 +28,7 @@
    "source": [
     "# install popmon (if not installed yet)\n",
     "import sys\n",
+    "\n",
     "!{sys.executable} -m pip install popmon"
    ]
   },
@@ -37,6 +39,7 @@
    "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "\n",
     "import popmon\n",
     "from popmon import resources"
    ]
@@ -55,7 +58,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = pd.read_csv(resources.data(\"flight_delays.csv.gz\"), index_col=0, parse_dates=[\"DATE\"])"
+    "df = pd.read_csv(\n",
+    "    resources.data(\"flight_delays.csv.gz\"), index_col=0, parse_dates=[\"DATE\"]\n",
+    ")"
    ]
   },
   {
@@ -72,7 +77,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.pm_stability_report(time_axis='DATE')"
+    "df.pm_stability_report(time_axis=\"DATE\")"
    ]
   },
   {
@@ -92,7 +97,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02', extended_report=False)"
+    "df.pm_stability_report(\n",
+    "    time_axis=\"DATE\", time_width=\"1w\", time_offset=\"2015-07-02\", extended_report=False\n",
+    ")"
    ]
   },
   {
@@ -109,7 +116,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02', extended_report=False, pull_rules={\"*_pull\": [10, 7, -7, -10]})"
+    "df.pm_stability_report(\n",
+    "    time_axis=\"DATE\",\n",
+    "    time_width=\"1w\",\n",
+    "    time_offset=\"2015-07-02\",\n",
+    "    extended_report=False,\n",
+    "    pull_rules={\"*_pull\": [10, 7, -7, -10]},\n",
+    ")"
    ]
   },
   {
@@ -133,7 +146,10 @@
    "source": [
     "# download histogrammar jar files if not already installed, used for histogramming of spark dataframe\n",
     "from pyspark.sql import SparkSession\n",
-    "spark = SparkSession.builder.config('spark.jars.packages','org.diana-hep:histogrammar-sparksql_2.11:1.0.4').getOrCreate()"
+    "\n",
+    "spark = SparkSession.builder.config(\n",
+    "    \"spark.jars.packages\", \"org.diana-hep:histogrammar-sparksql_2.11:1.0.4\"\n",
+    ").getOrCreate()"
    ]
   },
   {
@@ -151,7 +167,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sdf.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02', extended_report=False)"
+    "sdf.pm_stability_report(\n",
+    "    time_axis=\"DATE\", time_width=\"1w\", time_offset=\"2015-07-02\", extended_report=False\n",
+    ")"
    ]
   },
   {
@@ -172,8 +190,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_ref = pd.read_csv(resources.data(\"flight_delays_reference.csv.gz\"), index_col=0, parse_dates=['DATE'])\n",
-    "df.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02', extended_report=False, reference_type='external', reference=df_ref)"
+    "df_ref = pd.read_csv(\n",
+    "    resources.data(\"flight_delays_reference.csv.gz\"), index_col=0, parse_dates=[\"DATE\"]\n",
+    ")\n",
+    "df.pm_stability_report(\n",
+    "    time_axis=\"DATE\",\n",
+    "    time_width=\"1w\",\n",
+    "    time_offset=\"2015-07-02\",\n",
+    "    extended_report=False,\n",
+    "    reference_type=\"external\",\n",
+    "    reference=df_ref,\n",
+    ")"
    ]
   },
   {
@@ -190,7 +217,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02', extended_report=False, reference_type=\"expanding\")"
+    "df.pm_stability_report(\n",
+    "    time_axis=\"DATE\",\n",
+    "    time_width=\"1w\",\n",
+    "    time_offset=\"2015-07-02\",\n",
+    "    extended_report=False,\n",
+    "    reference_type=\"expanding\",\n",
+    ")"
    ]
   },
   {
@@ -208,7 +241,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02', extended_report=False, reference_type=\"rolling\", window=5)"
+    "df.pm_stability_report(\n",
+    "    time_axis=\"DATE\",\n",
+    "    time_width=\"1w\",\n",
+    "    time_offset=\"2015-07-02\",\n",
+    "    extended_report=False,\n",
+    "    reference_type=\"rolling\",\n",
+    "    window=5,\n",
+    ")"
    ]
   },
   {
@@ -226,8 +266,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "report = df.pm_stability_report(time_axis='DATE', time_width='1w', time_offset='2015-07-02')\n",
-    "split_hists = report.datastore['split_hists']['DEPARTURE_DELAY']\n",
+    "report = df.pm_stability_report(\n",
+    "    time_axis=\"DATE\", time_width=\"1w\", time_offset=\"2015-07-02\"\n",
+    ")\n",
+    "split_hists = report.datastore[\"split_hists\"][\"DEPARTURE_DELAY\"]\n",
     "split_hists"
    ]
   },
@@ -279,9 +321,10 @@
    "outputs": [],
    "source": [
     "import pickle\n",
-    "with open('report.pkl', 'wb') as f: \n",
+    "\n",
+    "with open(\"report.pkl\", \"wb\") as f:\n",
     "    pickle.dump(report, f)\n",
-    "report.to_file('report.html')"
+    "report.to_file(\"report.html\")"
    ]
   },
   {
@@ -298,8 +341,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "report.regenerate(last_n=0, skip_first_n=0, skip_last_n=0, plot_hist_n=2, skip_empty_plots=True,\n",
-    "                  report_filepath=None, store_key='html_report', sections_key='report_sections')"
+    "report.regenerate(\n",
+    "    last_n=0,\n",
+    "    skip_first_n=0,\n",
+    "    skip_last_n=0,\n",
+    "    plot_hist_n=2,\n",
+    "    skip_empty_plots=True,\n",
+    "    report_filepath=None,\n",
+    "    store_key=\"html_report\",\n",
+    "    sections_key=\"report_sections\",\n",
+    ")\n",
    ]
   },
   {
@@ -322,15 +373,23 @@
     "from popmon.base import Pipeline\n",
     "from popmon.visualization import SectionGenerator, ReportGenerator\n",
     "\n",
-    "monitoring_rules = {\"*_pull\": [7, 4, -4, -7], \"*_zscore\": [7, 4, -4, -7], \"[!p]*_unknown_labels\": [0.5, 0.5, 0, 0]}\n",
+    "monitoring_rules = {\n",
+    "    \"*_pull\": [7, 4, -4, -7],\n",
+    "    \"*_zscore\": [7, 4, -4, -7],\n",
+    "    \"[!p]*_unknown_labels\": [0.5, 0.5, 0, 0],\n",
+    "}\n",
     "datastore = dict()\n",
-    "datastore['hists'] = df.pm_make_histograms(time_axis='DATE', time_width='1w', time_offset='2015-07-02')\n",
+    "datastore[\"hists\"] = df.pm_make_histograms(\n",
+    "    time_axis=\"DATE\", time_width=\"1w\", time_offset=\"2015-07-02\"\n",
+    ")\n",
     "\n",
     "modules = [\n",
-    "    HistSplitter(read_key='hists', store_key='split_hists', feature_begins_with='DATE'),\n",
-    "    HistProfiler(read_key='split_hists', store_key='profiles'),\n",
-    "    SectionGenerator(section_name='Profiles', read_key=\"profiles\", store_key=\"report_sections\"),\n",
-    "    ReportGenerator(read_key=\"report_sections\", store_key=\"html_report\")\n",
+    "    HistSplitter(read_key=\"hists\", store_key=\"split_hists\", feature_begins_with=\"DATE\"),\n",
+    "    HistProfiler(read_key=\"split_hists\", store_key=\"profiles\"),\n",
+    "    SectionGenerator(\n",
+    "        section_name=\"Profiles\", read_key=\"profiles\", store_key=\"report_sections\"\n",
+    "    ),\n",
+    "    ReportGenerator(read_key=\"report_sections\", store_key=\"html_report\"),\n",
     "]\n",
     "\n",
     "pipeline = Pipeline(modules)\n",
@@ -356,15 +415,25 @@
     "from popmon.analysis.comparison.hist_comparer import ReferenceHistComparer\n",
     "\n",
     "datastore = dict()\n",
-    "datastore['hists'] = df.pm_make_histograms(time_axis='DATE', time_width='1w', time_offset='2015-07-02')\n",
+    "datastore[\"hists\"] = df.pm_make_histograms(\n",
+    "    time_axis=\"DATE\", time_width=\"1w\", time_offset=\"2015-07-02\"\n",
+    ")\n",
     "\n",
     "modules = [\n",
-    "    HistSplitter(read_key='hists', store_key='split_hists', feature_begins_with='DATE'),\n",
-    "    HistProfiler(read_key='split_hists', store_key='profiles'),\n",
-    "    ReferenceHistComparer(reference_key='split_hists', assign_to_key='split_hists', store_key='comparisons'),\n",
-    "    SectionGenerator(section_name='Profiles', read_key=\"profiles\", store_key=\"report_sections\"),\n",
-    "    SectionGenerator(section_name=\"Comparisons\", read_key=\"comparisons\", store_key=\"report_sections\"),\n",
-    "    ReportGenerator(read_key=\"report_sections\", store_key=\"html_report\")\n",
+    "    HistSplitter(read_key=\"hists\", store_key=\"split_hists\", feature_begins_with=\"DATE\"),\n",
+    "    HistProfiler(read_key=\"split_hists\", store_key=\"profiles\"),\n",
+    "    ReferenceHistComparer(\n",
+    "        reference_key=\"split_hists\",\n",
+    "        assign_to_key=\"split_hists\",\n",
+    "        store_key=\"comparisons\",\n",
+    "    ),\n",
+    "    SectionGenerator(\n",
+    "        section_name=\"Profiles\", read_key=\"profiles\", store_key=\"report_sections\"\n",
+    "    ),\n",
+    "    SectionGenerator(\n",
+    "        section_name=\"Comparisons\", read_key=\"comparisons\", store_key=\"report_sections\"\n",
+    "    ),\n",
+    "    ReportGenerator(read_key=\"report_sections\", store_key=\"html_report\"),\n",
     "]\n",
     "\n",
     "pipeline = Pipeline(modules)\n",
@@ -421,4 +490,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

popmon/notebooks/popmon_tutorial_basic.ipynb

@@ -16,6 +16,7 @@
    "source": [
     "# (optional) Adjust the jupyter notebook style for easier navigation of the reports\n",
     "from IPython.core.display import display, HTML\n",
+    "\n",
     "# Wider notebook\n",
     "display(HTML(\"<style>.container { width:80% !important; }</style>\"))\n",
     "# Cells are higher by default\n",
@@ -37,6 +38,7 @@
    "source": [
     "# install popmon (if not installed yet)\n",
     "import sys\n",
+    "\n",
     "!{sys.executable} -m pip install popmon"
    ]
   },
@@ -79,7 +81,11 @@
    "source": [
     "# first we generate histograms,\n",
     "# but we could load pre-generated histograms from a pickle or json file as well.\n",
-    "hists = df.pm_make_histograms(time_axis=\"date\", time_width='2w', features=['date:age', 'date:gender', 'date:isActive'])"
+    "hists = df.pm_make_histograms(\n",
+    "    time_axis=\"date\",\n",
+    "    time_width=\"2w\",\n",
+    "    features=[\"date:age\", \"date:gender\", \"date:isActive\"],\n",
+    ")"
    ]
   },
   {
@@ -109,7 +115,7 @@
    },
    "outputs": [],
    "source": [
-    "report # or report_.to_notebook_iframe()"
+    "report  # or report_.to_notebook_iframe()"
    ]
   },
   {
@@ -145,7 +151,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "report_ = df.pm_stability_report(time_axis=\"date\", time_width='2w', features=['date:age', 'date:isActive', 'date:eyeColor'])"
+    "report_ = df.pm_stability_report(\n",
+    "    time_axis=\"date\",\n",
+    "    time_width=\"2w\",\n",
+    "    features=[\"date:age\", \"date:isActive\", \"date:eyeColor\"],\n",
+    ")"
    ]
   },
   {