sql_io.py: put_table(): Ignoring all rows for unrecoverable errors: Even in multi-row mode, just return whatever the default value or column was, instead of creating an output table containing the default value filled in for every row. This also assists the optimization to skip empty levels of taxonconcepts, because it folds the empty level to that level's parent level rather than creating a whole new temp table with ultimately the same contents.

sql_gen.py: not_false_re, not_true_re: Appended \b to ensure that true/false is only matched as a single word

sql_gen.py: simplify_expr(): Also simplify "NOT false" to true

sql_gen.py: simplify_expr(): Also simplify "NOT true" to false

sql_io.py: put_table(): ignore_cond(): Changed "Ignoring rows where" message with the negated (filter-out) condition to "Ignoring rows that don't satisfy" with the filter condition for clarity

sql_io.py: put_table(): ignore_cond(): If cond simplifies to false, remove all rows instead of filtering out individual rows which will all be filtered out. This optimization should improve import times of tables, such as taxonconcept, which use a check constraint instead of NOT NULL constraints to prevent empty rows. The taxonomic schema refactoring caused the creation of many more levels of taxonconcepts, many of which (such as variety, forma, cultivar) are empty for most datasources, so this optimization should also reduce overall import times for datasources that have any empty levels of taxonconcept. Note that this optimization is only possible now that sql_gen.simplify_expr() is able to simplify all the way to a single boolean value for the taxonconcept_required_key constraint.

Moved expression transforming functions from sql.py to sql_gen.py because they do not manipulate an actual database and merely generate SQL

sql.py: Added true_expr, false_expr and use them where their values are used

sql.py: simplify_expr(): Also simplify "AND true" expressions

sql.py: simplify_expr(): Also simplify "AND false" expressions