Adding upstream version 1.39.0.upstream/1.39.0

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

3 files changed, 49 insertions, 13 deletions

diff --git a/collectors/python.d.plugin/pandas/README.md b/collectors/python.d.plugin/pandas/README.md
index 14154947..19b11d5b 100644
--- a/collectors/python.d.plugin/pandas/README.md
+++ b/collectors/python.d.plugin/pandas/README.md
@@ -1,16 +1,15 @@
-<!--
-title: "Pandas"
-custom_edit_url: https://github.com/netdata/netdata/edit/master/collectors/python.d.plugin/pandas/README.md
--->
-
-# Pandas Netdata Collector
+# Ingest structured data (Pandas)
 
 <a href="https://pandas.pydata.org/" target="_blank">
   <img src="https://pandas.pydata.org/docs/_static/pandas.svg" alt="Pandas" width="100px" height="50px" />
  </a>
 
-A python collector using [pandas](https://pandas.pydata.org/) to pull data and do pandas based 
-preprocessing before feeding to Netdata.
+[Pandas](https://pandas.pydata.org/) is a de-facto standard in reading and processing most types of structured data in Python.
+If you have metrics appearing in a CSV, JSON, XML, HTML, or [other supported format](https://pandas.pydata.org/docs/user_guide/io.html), 
+either locally or via some HTTP endpoint, you can easily ingest and present those metrics in Netdata, by leveraging the Pandas collector.
+
+The collector uses [pandas](https://pandas.pydata.org/) to pull data and do pandas-based 
+preprocessing, before feeding to Netdata.
 
 ## Requirements
 
@@ -20,6 +19,12 @@ This collector depends on some Python (Python 3 only) packages that can usually
 sudo pip install pandas requests
 ```
 
+Note: If you would like to use [`pandas.read_sql`](https://pandas.pydata.org/docs/reference/api/pandas.read_sql.html) to query a database, you will need to install the below packages as well.
+
+```bash
+sudo pip install 'sqlalchemy<2.0' psycopg2-binary
+```
+
 ## Configuration
 
 Below is an example configuration to query some json weather data from [Open-Meteo](https://open-meteo.com), 
@@ -66,12 +71,11 @@ temperature:
 
 `chart_configs` is a list of dictionary objects where each one defines the sequence of `df_steps` to be run using [`pandas`](https://pandas.pydata.org/), 
 and the `name`, `title` etc to define the 
-[CHART variables](https://learn.netdata.cloud/docs/agent/collectors/python.d.plugin#global-variables-order-and-chart) 
+[CHART variables](https://github.com/netdata/netdata/blob/master/docs/guides/python-collector.md#create-charts) 
 that will control how the results will look in netdata.
 
 The example configuration above would result in a `data` dictionary like the below being collected by Netdata 
-at each time step. They keys in this dictionary will be the 
-[dimension](https://learn.netdata.cloud/docs/agent/web#dimensions) names on the chart.
+at each time step. They keys in this dictionary will be the "dimensions" of the chart.
 
 ```javascript
 {'athens_max': 26.2, 'athens_mean': 19.45952380952381, 'athens_min': 12.2, 'berlin_max': 17.4, 'berlin_mean': 10.764285714285714, 'berlin_min': 5.7, 'dublin_max': 15.3, 'dublin_mean': 12.008928571428571, 'dublin_min': 6.6, 'london_max': 18.9, 'london_mean': 12.510714285714286, 'london_min': 5.2, 'paris_max': 19.4, 'paris_mean': 12.054166666666665, 'paris_min': 4.8}
diff --git a/collectors/python.d.plugin/pandas/pandas.chart.py b/collectors/python.d.plugin/pandas/pandas.chart.py
index 8eb4452f..7977bcb3 100644
--- a/collectors/python.d.plugin/pandas/pandas.chart.py
+++ b/collectors/python.d.plugin/pandas/pandas.chart.py
@@ -3,6 +3,7 @@
 # Author: Andrew Maguire (andrewm4894)
 # SPDX-License-Identifier: GPL-3.0-or-later
 
+import os
 import pandas as pd
 
 try:
@@ -11,6 +12,12 @@ try:
 except ImportError:
     HAS_REQUESTS = False
 
+try:
+    from sqlalchemy import create_engine
+    HAS_SQLALCHEMY = True
+except ImportError:
+    HAS_SQLALCHEMY = False
+
 from bases.FrameworkServices.SimpleService import SimpleService
 
 ORDER = []
@@ -46,7 +53,10 @@ class Service(SimpleService):
         """ensure charts and dims all configured and that we can get data"""
 
         if not HAS_REQUESTS:
-            self.warn('requests library could not be imported')
+            self.warning('requests library could not be imported')
+
+        if not HAS_SQLALCHEMY:
+            self.warning('sqlalchemy library could not be imported')
 
         if not self.chart_configs:
             self.error('chart_configs must be defined')
diff --git a/collectors/python.d.plugin/pandas/pandas.conf b/collectors/python.d.plugin/pandas/pandas.conf
index 6684af9d..ca523ed3 100644
--- a/collectors/python.d.plugin/pandas/pandas.conf
+++ b/collectors/python.d.plugin/pandas/pandas.conf
@@ -188,4 +188,26 @@ update_every: 5
 #         df_steps: >
 #           pd.read_xml('http://metwdb-openaccess.ichec.ie/metno-wdb2ts/locationforecast?lat=54.7210798611;long=-8.7237392806', xpath='./product/time[1]/location/temperature', parser='etree')|
 #           df.rename(columns={'value': 'dublin'})|
-#           df[['dublin']]|
\ No newline at end of file
+#           df[['dublin']]|
+
+# example showing a read_sql from a postgres database using sqlalchemy.
+# note: example assumes a running postgress db on localhost with a netdata users and password netdata.
+# sql:
+#     name: "sql"
+#     update_every: 5
+#     chart_configs:
+#       - name: "sql"
+#         title: "SQL Example"
+#         family: "sql.example"
+#         context: "example"
+#         type: "line"
+#         units: "percent"
+#         df_steps: >
+#           pd.read_sql_query(
+#             sql='\
+#                 select \
+#                     random()*100 as metric_1, \
+#                     random()*100 as metric_2 \
+#                ',
+#             con=create_engine('postgresql://localhost/postgres?user=netdata&password=netdata')
+#             );