intro outline

outline.md

@@ -24,15 +24,26 @@
 ### Session PM1 GIT
 
 ### Session PM2 Python Intro (basic overview) (Sebastian)
+
 - python+anaconda+conda+jupyter+history
-- operators, data structures (tuples, lists, dicts, nparrays, panda.df, etc)
-- object types (string, number, boolean, complex, etc)
-- provided functions + methods, atrributes
-- control flows: loops + conditions
+- (notebooks vs. interpreter vs. scripts)
+- object types (string, number, boolean, complex, etc) and operators
+- data structures (tuples, lists, dicts, nparrays, panda.df, etc)
 - list comprehensions
+- provided functions + methods, attributes
+- (where/how to find help / documentation)
+- control flow: loops + conditionals
+- (code indentation)
 - numpy
+- (io)
 - read file, simple plot (or in session PM2)
 
+### What is missing?
+
+- coding style, naming conventions
+- tour through python standard library
+- the limits of Python
+
 ## DAY 2 AM
 
 ### Session AM1 Python (structuring code, defensive programming, using prepared ts files) (Frank)
@@ -75,3 +86,20 @@ gridded data Europe:
 - github/gitlab release
 - outro, feedback
 
+
+## Badly needed but out of scope this time
+
+- writing better code (could be extra lecture in a later SWC)
+  - how to name things
+  - clean code (the first broken window analogon)
+  - security
+  - dependency hell
+  - avoiding global variables
+  - avoiding state / side effects / thread safety
+  - complexity reduction / avoiding if-orgies etc.
+  - don't repeat yourself
+  - reuseability 
+  - data structuring flat vs nested
+  - oo - the good, the bad, the ugly
+  - data models: tree vs relational vs tabular vs array ways of thinking
+