potiuk commented on code in PR #25780:
URL: https://github.com/apache/airflow/pull/25780#discussion_r956385787


##########
docs/apache-airflow/best-practices.rst:
##########
@@ -619,3 +621,221 @@ Prune data before upgrading
 ---------------------------
 
 Some database migrations can be time-consuming.  If your metadata database is 
very large, consider pruning some of the old data with the :ref:`db 
clean<cli-db-clean>` command prior to performing the upgrade.  *Use with 
caution.*
+
+
+Handling Python dependencies
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Airflow has many Python dependencies and sometimes the Airflow dependencies 
are conflicting with dependencies that your
+task code expects. Since - by default - Airflow environment is just a single 
set of Python dependencies and single
+Python environment, often there might also be cases that some of your tasks 
require different dependencies than other tasks
+and the dependencies basically conflict between those tasks.
+
+If you are using pre-defined Airflow Operators to talk to external services, 
there is not much choice, but usually those
+operators will have dependencies that are not conflicting with basic Airflow 
dependencies. Airflow uses constraints mechanism
+which means that you have a "fixed" set of dependencies that the community 
guarantees that Airflow can be installed with
+(including all community providers) without triggering conflicts. However you 
can upgrade the providers
+independently and their constraints do not limit you so the chance of a 
conflicting dependency is lower (you still have
+to test those dependencies). Therefore when you are using pre-defined 
operators, chance is that you will have
+little, to no problems with conflicting dependencies.
+
+However, when you are approaching Airflow in a more "modern way", where you 
use TaskFlow Api and most of
+your operators are written using custom python code, or when you want to write 
your own Custom Operator,

Review Comment:
   I changed it to "pythonic" from modern



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