Clarify the use of get_spark_session and load_user_conf (for tests only!)

[JulienPeloton]

There was some confusion on when and why using get_spark_session and load_user_conf. These routines are mainly used in 2 contexts:

• Running the test suite
• Using spark3D within a standard ipython or notebook session

In those two cases, you need to load the JAR+deps within the session.

However, in a regular pyspark session, or in batch mode, you should not use it. Instead, link spark3D when starting the session:

pyspark --jars /path/to/spar3djar --master ...
# or
spark-submit --jars /path/to/spar3djar --master ...

If you installed pyspark3d via pip, the JAR is released with the python source files. To find its location:

python -c "import pyspark3d; print(pyspark3d.__file__)"

The doctests have been simplified by using extraglobs.

[codecov-io]

Codecov Report

Merging #99 into master will increase coverage by 0.17%. The diff coverage is n/a.

@@            Coverage Diff             @@
##           master      #99      +/-   ##
==========================================
+ Coverage   96.19%   96.37%   +0.17%     
==========================================
  Files          32       32              
  Lines        1210     1240      +30     
  Branches      217      217              
==========================================
+ Hits         1164     1195      +31     
+ Misses         46       45       -1

Flag	Coverage Δ
#python	94.3% <ø> (+0.79%)	:arrow_up:
#scala	97.24% <ø> (ø)	:arrow_up:

Impacted Files	Coverage Δ
pyspark3d_conf.py	88.23% <0%> (ø)	:arrow_up:
spatialOperator.py	100% <0%> (ø)	:arrow_up:
converters.py	100% <0%> (ø)	:arrow_up:
spatial3DRDD.py	100% <0%> (ø)	:arrow_up:
__init__.py	98.71% <0%> (+2.16%)	:arrow_up:

---

Continue to review full report at Codecov.

Legend - Click here to learn more Δ = absolute <relative> (impact), ø = not affected, ? = missing data Powered by Codecov. Last update d04876c...2dde0a3. Read the comment docs.