From 44b42e953ad2044261e7df37d1518d50cf7a5232 Mon Sep 17 00:00:00 2001
From: Jessica <JessicaS11@users.noreply.github.com>
Date: Tue, 14 Sep 2021 14:11:55 -0400
Subject: [PATCH] traffic/downloads statistics updates and limit traffic action
 to parent repo (#221)

* GitHub traffic auto-update to not run traffic action on forks.
---
 .github/workflows/traffic_action.yml          |    1 +
 doc/source/tracking/pypistats/downloads.svg   | 2022 ++++++++-------
 .../tracking/pypistats/downloads_data.csv     |  348 ++-
 .../tracking/pypistats/get_pypi_stats.ipynb   |   37 +-
 .../tracking/pypistats/sys_downloads_data.csv |  532 +++-
 doc/source/tracking/traffic/clones.csv        |  160 +-
 doc/source/tracking/traffic/plots.svg         | 2199 +++++++++++------
 doc/source/tracking/traffic/views.csv         |  172 +-
 8 files changed, 3590 insertions(+), 1881 deletions(-)

diff --git a/.github/workflows/traffic_action.yml b/.github/workflows/traffic_action.yml
index 42bc19b16..a7ce42739 100644
--- a/.github/workflows/traffic_action.yml
+++ b/.github/workflows/traffic_action.yml
@@ -12,6 +12,7 @@ jobs:
   traffic:
     # The type of runner that the job will run on
     runs-on: ubuntu-latest
+    if: github.repository_owner == 'icesat2py'
 
     # Steps represent a sequence of tasks that will be executed as part of the job
     steps:
diff --git a/doc/source/tracking/pypistats/downloads.svg b/doc/source/tracking/pypistats/downloads.svg
index c7cd86be3..a2d400123 100644
--- a/doc/source/tracking/pypistats/downloads.svg
+++ b/doc/source/tracking/pypistats/downloads.svg
@@ -1,17 +1,16 @@
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     <dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
-    <dc:date>2021-03-16T13:05:06.396594</dc:date>
+    <dc:date>2021-09-09T14:06:20.061393</dc:date>
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     <dc:creator>
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-      <dc:title>Matplotlib v3.3.4, https://matplotlib.org/</dc:title>
+      <dc:title>Matplotlib v3.4.2, https://matplotlib.org/</dc:title>
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diff --git a/doc/source/tracking/pypistats/downloads_data.csv b/doc/source/tracking/pypistats/downloads_data.csv
index bb089fbe2..4b60516d5 100644
--- a/doc/source/tracking/pypistats/downloads_data.csv
+++ b/doc/source/tracking/pypistats/downloads_data.csv
@@ -1,4 +1,351 @@
 category,date,downloads
+with_mirrors,2021-05-14,130
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+with_mirrors,2021-09-02,49
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+with_mirrors,2021-06-04,44
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+without_mirrors,2021-05-30,1
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+without_mirrors,2021-08-31,1
+without_mirrors,2021-09-08,1
 with_mirrors,2020-12-05,79
 with_mirrors,2020-12-04,68
 with_mirrors,2020-10-17,50
@@ -295,7 +642,6 @@ without_mirrors,2021-02-28,1
 without_mirrors,2021-03-04,1
 without_mirrors,2021-03-06,1
 without_mirrors,2021-03-08,1
-without_mirrors,2021-03-13,1
 with_mirrors,2020-09-12,33
 with_mirrors,2020-09-14,18
 with_mirrors,2020-09-13,17
diff --git a/doc/source/tracking/pypistats/get_pypi_stats.ipynb b/doc/source/tracking/pypistats/get_pypi_stats.ipynb
index 496017562..3a719e27c 100644
--- a/doc/source/tracking/pypistats/get_pypi_stats.ipynb
+++ b/doc/source/tracking/pypistats/get_pypi_stats.ipynb
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -27,7 +27,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -60,7 +60,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -69,7 +69,7 @@
     "# try:\n",
     "exist_sysdownloads = pd.read_csv(trackpath+sysdownloadfn)#.drop(columns=['percent'])\n",
     "# exist_sysdownloads = exist_sysdownloads[exist_sysdownloads.category != \"Total\"]\n",
-    "# exist_sysdownloads['category'] = exist_sysdownloads['category'].fillna(\"null\")\n",
+    "exist_sysdownloads['category'] = exist_sysdownloads['category'].fillna(\"null\")\n",
     "sysdl_data = sysdownloads.merge(exist_sysdownloads, how='outer', \n",
     "                              on=['category','date','downloads']).reindex()\n",
     "# except:\n",
@@ -80,30 +80,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "<ipython-input-5-9ae24e11e434>:5: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
-      "  chart.figure.show()\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x144 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "dl_data = dl_data.groupby(\"category\").get_group(\"without_mirrors\").sort_values(\"date\")\n",
     "\n",
@@ -137,7 +116,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.2"
+   "version": "3.9.4"
   }
  },
  "nbformat": 4,
diff --git a/doc/source/tracking/pypistats/sys_downloads_data.csv b/doc/source/tracking/pypistats/sys_downloads_data.csv
index b26986e5b..74ad8ab92 100644
--- a/doc/source/tracking/pypistats/sys_downloads_data.csv
+++ b/doc/source/tracking/pypistats/sys_downloads_data.csv
@@ -1,4 +1,346 @@
 category,date,downloads
+null,2021-03-12,28
+null,2021-03-29,25
+null,2021-03-26,22
+null,2021-06-30,21
+null,2021-07-26,20
+null,2021-05-13,19
+null,2021-04-06,18
+null,2021-05-14,17
+null,2021-07-25,17
+null,2021-08-06,16
+null,2021-07-17,15
+null,2021-08-12,15
+Linux,2021-08-16,14
+null,2021-04-17,14
+null,2021-04-01,13
+null,2021-04-03,13
+null,2021-04-04,13
+null,2021-04-05,13
+Linux,2021-07-29,12
+null,2021-03-27,12
+null,2021-03-30,12
+null,2021-06-11,12
+null,2021-03-25,11
+null,2021-06-29,10
+Linux,2021-06-25,9
+Linux,2021-06-26,9
+null,2021-07-01,9
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diff --git a/doc/source/tracking/traffic/clones.csv b/doc/source/tracking/traffic/clones.csv
index 5cf0c961f..2ee43b653 100644
--- a/doc/source/tracking/traffic/clones.csv
+++ b/doc/source/tracking/traffic/clones.csv
@@ -110,4 +110,162 @@ _date,total_clones,unique_clones
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index 1f7bf4d0b..ef6cc4e36 100644
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