--- a
+++ b/qiita_db/metadata_template/constants.py
@@ -0,0 +1,91 @@
+# -----------------------------------------------------------------------------
+# Copyright (c) 2014--, The Qiita Development Team.
+#
+# Distributed under the terms of the BSD 3-clause License.
+#
+# The full license is in the file LICENSE, distributed with this software.
+# -----------------------------------------------------------------------------
+
+from collections import namedtuple
+from datetime import datetime
+
+Restriction = namedtuple('Restriction', ['columns', 'error_msg'])
+
+# A dict containing the restrictions that apply to the sample templates
+SAMPLE_TEMPLATE_COLUMNS = {
+    # The following columns are required by EBI for submission
+    'EBI': Restriction(columns={'collection_timestamp': datetime,
+                                'physical_specimen_location': str,
+                                'taxon_id': int,
+                                'description': str,
+                                'scientific_name': str},
+                       error_msg="EBI submission disabled"),
+    # The following columns are required for the official main QIITA site
+    'qiita_main': Restriction(columns={'sample_type': str,
+                                       'description': str,
+                                       'physical_specimen_remaining': bool,
+                                       'dna_extracted': bool,
+                                       'latitude': float,
+                                       'longitude': float,
+                                       'host_subject_id': str},
+                              error_msg="Processed data approval disabled")
+}
+
+# A dict containing the restrictions that apply to the prep templates
+PREP_TEMPLATE_COLUMNS = {
+    # The following columns are required by EBI for submission
+    'EBI': Restriction(
+        columns={'center_name': str,
+                 'platform': str,
+                 'instrument_model': str,
+                 'library_construction_protocol': str,
+                 'experiment_design_description': str},
+        error_msg="EBI submission disabled")
+}
+
+# Different prep templates have different requirements depending on the data
+# type. We create a dictionary for each of these special datatypes
+
+TARGET_GENE_DATA_TYPES = ['16S', '18S', 'ITS']
+
+PREP_TEMPLATE_COLUMNS_TARGET_GENE = {
+    # The following columns are required by QIIME to execute split libraries
+    'demultiplex': Restriction(
+        columns={'barcode': str},
+        error_msg="Demultiplexing disabled."),
+    # The following columns are required by Qiita to know how to execute split
+    # libraries using QIIME over a study with multiple illumina lanes
+    'demultiplex_multiple': Restriction(
+        columns={'barcode': str,
+                 'primer': str,
+                 'run_prefix': str},
+        error_msg="Demultiplexing with multiple input files disabled.")
+}
+
+# This list is useful to have if we want to loop through all the restrictions
+# in a template-independent manner
+ALL_RESTRICTIONS = [SAMPLE_TEMPLATE_COLUMNS, PREP_TEMPLATE_COLUMNS,
+                    PREP_TEMPLATE_COLUMNS_TARGET_GENE]
+
+# This is what we consider as "NaN" cell values on metadata import
+# from http://www.ebi.ac.uk/ena/about/missing-values-reporting
+EBI_NULL_VALUES = ['Not applicable', 'Missing: Not collected',
+                   'Missing: Not provided', 'Missing: Restricted access']
+
+# These are what will be considered 'True' bool values on metadata import
+TRUE_VALUES = ['Yes', 'yes', 'YES', 'Y', 'y', 'True', 'true', 'TRUE', 't', 'T']
+
+# These are what will be considered 'False' bool values on metadata import
+FALSE_VALUES = ['No', 'no', 'NO', 'N', 'n', 'False', 'false', 'FALSE',
+                'f', 'F']
+
+
+# A set holding all the controlled columns, useful to avoid recalculating it
+def _col_iterator():
+    for r_set in ALL_RESTRICTIONS:
+        for restriction in r_set.values():
+            for cols in restriction.columns.keys():
+                yield cols
+
+
+CONTROLLED_COLS = set(col for col in _col_iterator())