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135 lines
4.0 KiB
135 lines
4.0 KiB
import csv
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"""
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Required fields when inserting into the database.
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"""
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_required_fields = [
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# the "str" type means that this field can be any valid string.
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("metabolite_name", "str"),
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("formula", "str"),
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("person_name", "str"),
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# any field labeled a "float" needs to have a value in decimal notation.
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("mass", "float"),
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("final_mz", "float"),
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("final_rt", "float"),
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("final_adduct", "str"),
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("standard_grp", "str"),
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("person_name", "str"),
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("msms_detected", "yesno"), # Value can either be "Yes" or "No"
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("inchikey", "str"),
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]
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"""
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Optional fields and corresponding types when batch inserting into the database.
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"""
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_optional_fields = [
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("chemical_db_id", "str"),
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("library", "str"),
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("pubchem_cid", "int"), # Only integers are permitted.
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("pubmed_refcount", "int"),
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("standard_class", "str"),
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("inchikey14", "str"),
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("adduct", "str"),
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("detected_adducts", "str"),
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("adduct_calc_mz", "str"),
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("msms_purity", "float"),
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]
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"""
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All fields (excluding those that are commented) are mandatory to include.
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"""
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_query_fields = [
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("rt_min", "float"),
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("rt_max", "float"),
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("mz_min", "float"),
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("mz_max", "float"),
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# ("year_max", "int"),
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# ("day_max", "int"),
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# ("month_max", "int"),
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]
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def _validate_type(field: str, value: str, t):
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if t == "yesno":
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l = value.strip().lower()
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if l == "yes":
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return True
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elif l == "no":
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return False
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else:
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raise ValueError(
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f"Yes/No field {field} does not have a valid value {value}")
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elif t == "int":
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try:
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return int(value)
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except ValueError:
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raise ValueError(
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f"Integer field {field} does not have a valid value {value}")
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elif t == "float":
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try:
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return float(value)
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except ValueError:
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raise ValueError(
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f"Float field {field} does not have a valid value {value}")
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elif t == "str":
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return value
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else:
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raise ValueError("Impossible")
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def validate_insertion_csv_fields(reader: csv.DictReader) -> tuple[list[dict], str]:
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chemicals: list[dict] = []
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for row in reader:
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chemical = {}
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for field, t in _required_fields:
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if field not in row:
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return [], f"Required field \"{field}\" not present in csv"
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try:
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value = _validate_type(field, row[field], t)
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chemical[field] = value
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except ValueError as e:
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return [], str(e)
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for field, t in _optional_fields:
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if field not in row:
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continue
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try:
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value = _validate_type(field, row[field], t)
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chemical[field] = value
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except ValueError as e:
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return [], str(e)
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chemicals.append(chemical)
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return chemicals, ""
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def validate_query_csv_fields(reader: csv.DictReader) -> tuple[list[dict], str]:
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queries: list[dict] = []
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for row in reader:
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query = {}
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for field, t in _query_fields:
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if field not in row:
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return [], f"Required field \"{field}\" not present in csv"
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try:
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value = _validate_type(field, row[field], t)
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query[field] = value
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except ValueError as e:
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return [], str(e)
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# year_max, month_max, day_max = query.get(
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# 'year_max'), query.get('month_max'), query.get('day_max')
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# try:
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# d = date(year_max, month_max, day_max)
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# query["date"] = d
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# except ValueError as e:
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# return [], f"Invalid Date Value Provided for {month_max}/{day_max}/{year_max}"
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queries.append(query)
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return queries, ""
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