chore: convert poetry format and remove optional dependencies

examples/quickstart.py

@@ -0,0 +1,39 @@
+# Quickstart
+# This script provides a quick demonstration of the basic usage of tagreader. It will show you the steps from importing the package to fetching data and making a plot. Some cells contain links to more details that can be found in the [manual](../docs/manual.md).
+
+# Start by importing the package:
+from tagreader import IMSClient, list_sources
+
+# If we don't know the name of the data source, we can check which PI (piwebapi) and IP.21 (aspenone) servers we have access to via Web API ([more details](https://equinor.github.io/tagreader-python/docs/about/usage/data-source)):
+print(list_sources("aspenone"))
+
+# Let's establish a web API connection to PINO.
+c = IMSClient(datasource="TRB")
+
+# After connecting, we can search for a tag ([more details](../docs/manual.md#searching-for-tags)):
+tags = list(map(str, c.search("AverageC*", return_desc=False)))
+
+# Selecting three of the tags found above, we can read values for a duration of 3.5 hours starting January 5th at 8 in the morning with 3-minute (180-seconds) intervals. The default query method is interpolated, but several other methods are available by providing the `read_type` argument. Timestamps are parsed using [pandas.Timestamp](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timestamp.html), and can therefore be provided in many different string formats. [More details](../docs/manual.md#reading_data)
+df = c.read(
+    tags,
+    "05-Jan-2024 08:00:00",
+    "15/01/24 11:30am",
+    180,
+)
+# *Note*: Tags with maps (relevant for some InfoPlus.21 servers) can be specified on the form `'tag;map'`, e.g. `'17B-HIC192;CS A_AUTO'`.
+
+# The result from the last call is a Pandas dataframe, and can be manipulated as such:
+print(df.tail())
+print(df["AverageCPUTimeTest"].size)
+print(df["AverageCPUTimeVals"].loc["2024-01-05 11:24:00"])
+print(max(df["AverageCPUTimeVals"]))
+
+# Sometimes it can be handy to obtain the unit and description for the tags:
+units = c.get_units(tags)
+desc = c.get_descriptions(tags)
+print(units)
+print(desc)
+
+# Requires matplotlib to be installed.
+# tag = tags[0]
+# df[tag].plot(grid=True, title=desc[tag]).set_ylabel(units[tag])