def parse(handle, validate=True):
"""Parses an XML file from the NCBI Entrez Utilities into python objects.
This function parses an XML file created by NCBI's Entrez Utilities,
returning a multilevel data structure of Python lists and dictionaries.
This function is suitable for XML files that (in Python) can be represented
as a list of individual records. Whereas 'read' reads the complete file
and returns a single Python list, 'parse' is a generator function that
returns the records one by one. This function is therefore particularly
useful for parsing large files.
Most XML files returned by NCBI's Entrez Utilities can be parsed by
this function, provided its DTD is available. Biopython includes the
DTDs for most commonly used Entrez Utilities.
If validate is True (default), the parser will validate the XML file
against the DTD, and raise an error if the XML file contains tags that
are not represented in the DTD. If validate is False, the parser will
simply skip such tags.
Whereas the data structure seems to consist of generic Python lists,
dictionaries, strings, and so on, each of these is actually a class
derived from the base type. This allows us to store the attributes
(if any) of each element in a dictionary my_element.attributes, and
the tag name in my_element.tag.
"""
from Parser import DataHandler
handler = DataHandler(validate)
records = handler.parse(handle)
return records
def parse(handle, validate=True):
"""Parses an XML file from the NCBI Entrez Utilities into python objects.
This function parses an XML file created by NCBI's Entrez Utilities,
returning a multilevel data structure of Python lists and dictionaries.
This function is suitable for XML files that (in Python) can be represented
as a list of individual records. Whereas 'read' reads the complete file
and returns a single Python list, 'parse' is a generator function that
returns the records one by one. This function is therefore particularly
useful for parsing large files.
Most XML files returned by NCBI's Entrez Utilities can be parsed by
this function, provided its DTD is available. Biopython includes the
DTDs for most commonly used Entrez Utilities.
If validate is True (default), the parser will validate the XML file
against the DTD, and raise an error if the XML file contains tags that
are not represented in the DTD. If validate is False, the parser will
simply skip such tags.
Whereas the data structure seems to consist of generic Python lists,
dictionaries, strings, and so on, each of these is actually a class
derived from the base type. This allows us to store the attributes
(if any) of each element in a dictionary my_element.attributes, and
the tag name in my_element.tag.
"""
from Parser import DataHandler
handler = DataHandler(validate)
records = handler.parse(handle)
return records
def parse(handle):
from Parser import DataHandler
DTDs = os.path.join(str(__path__[0]), "DTDs")
handler = DataHandler(DTDs)
records = handler.parse(handle)
return records
def read(handle):
"""Parses an XML file from the NCBI Entrez Utilities into python objects.
This function parses an XML file created by NCBI's Entrez Utilities,
returning a multilevel data structure of Python lists and dictionaries.
Most XML files returned by NCBI's Entrez Utilities can be parsed by
this function, provided its DTD is available. Biopython includes the
DTDs for most commonly used Entrez Utilities.
Whereas the data structure seems to consist of generic Python lists,
dictionaries, strings, and so on, each of these is actually a class
derived from the base type. This allows us to store the attributes
(if any) of each element in a dictionary my_element.attributes, and
the tag name in my_element.tag.
"""
from Parser import DataHandler
DTDs = os.path.join(__path__[0], "DTDs")
handler = DataHandler(DTDs)
record = handler.run(handle)
return record
def read(handle):
"""Parses an XML file from the NCBI Entrez Utilities into python objects.
This function parses an XML file created by NCBI's Entrez Utilities,
returning a multilevel data structure of Python lists and dictionaries.
Most XML files returned by NCBI's Entrez Utilities can be parsed by
this function, provided its DTD is available. Biopython includes the
DTDs for most commonly used Entrez Utilities.
Whereas the data structure seems to consist of generic Python lists,
dictionaries, strings, and so on, each of these is actually a class
derived from the base type. This allows us to store the attributes
(if any) of each element in a dictionary my_element.attributes, and
the tag name in my_element.tag.
"""
from Parser import DataHandler
DTDs = os.path.join(__path__[0], "DTDs")
handler = DataHandler(DTDs)
record = handler.run(handle)
return record
def parse(handle):
from Parser import DataHandler
DTDs = os.path.join(__path__[0], "DTDs")
handler = DataHandler(DTDs)
records = handler.parse(handle)
return records
