Contains constants used by the NDEx2 Python Client

ndex2.constants.ASPECT_ID = 'id'

Key for aspect ID

ndex2.constants.ASPECT_VALUES = 'v'

Key for aspect values

ndex2.constants.ATTR_DATATYPE = 'd'

Key for attribute data type

ndex2.constants.ATTR_NAME = 'n'

Key for attribute name

ndex2.constants.BOOLEAN_DATATYPE = 'boolean'

Boolean data type for CX

ndex2.constants.CARTESIAN_LAYOUT_ASPECT = 'cartesianLayout'

Name of opaque aspect containing coordinates of nodes

"cartesianLayout": [ 
        "node": 0,
        "x": 25.0,
        "y": 50.0
    }, {
        "node": 1,
        "x": -10.0,
        "y": -200.0


Although the name implies a cartesian coordinate system, that is actually wrong. The Y access is inverted so lower values of Y are rendered higher on a graph. 0,0 is considered upper left corner, but negative values are allowed

ndex2.constants.DOUBLE_DATATYPE = 'double'

Double data type for CX

ndex2.constants.EDGES_ASPECT = 'edges'

Key for nodes attribute

ndex2.constants.EDGE_ID = '@id'

Key for id of edge

ndex2.constants.EDGE_INTERACTION = 'i'

Key for edge interaction

ndex2.constants.EDGE_INTERACTION_EXPANDED = 'interaction'

Expanded key for edge interaction

ndex2.constants.EDGE_SOURCE = 's'

Key for edge source

ndex2.constants.EDGE_TARGET = 't'

Key for edge target

ndex2.constants.INTEGER_DATATYPE = 'integer'

Integer data type for CX

ndex2.constants.LAYOUT_NODE = 'node'

Key for node id in CARTESIAN_LAYOUT_ASPECT opaque aspect

ndex2.constants.LAYOUT_X = 'x'

Key for X coordinate in CARTESIAN_LAYOUT_ASPECT opaque aspect

ndex2.constants.LAYOUT_Y = 'y'

Key for Y coordinate in CARTESIAN_LAYOUT_ASPECT opaque aspect

ndex2.constants.LAYOUT_Z = 'z'

Key for Z coordinate in CARTESIAN_LAYOUT_ASPECT opaque aspect

ndex2.constants.LIST_OF_BOOLEAN = 'list_of_boolean'

List of Boolean data type for CX

ndex2.constants.LIST_OF_DOUBLE = 'list_of_double'

List of Double data type for CX

ndex2.constants.LIST_OF_INTEGER = 'list_of_integer'

List of Integer data type for CX

ndex2.constants.LIST_OF_LONG = 'list_of_long'

List of Long data type for CX

ndex2.constants.LIST_OF_STRING = 'list_of_string'

List of String data type for CX

ndex2.constants.LONG_DATATYPE = 'long'

Long data type for CX

ndex2.constants.NET_ATTR_NAME = 'n'

Key for network attribute name

ndex2.constants.NET_ATTR_VALUE = 'v'

Key for network attribute value

ndex2.constants.NODES_ASPECT = 'nodes'

Key for nodes attribute

ndex2.constants.NODE_ATTR_DATATYPE = 'd'

Key for node attribute data type

ndex2.constants.NODE_ATTR_NAME = 'n'

Key for node attribute name

ndex2.constants.NODE_ATTR_PROPERTYOF = 'po'

Key for node property of

ndex2.constants.NODE_ATTR_VALUE = 'v'

Key for node attribute value

ndex2.constants.NODE_ID = '@id'

Key for id of node

ndex2.constants.NODE_NAME = 'n'

Key for node name

ndex2.constants.NODE_NAME_EXPANDED = 'name'

Expanded key for node name

ndex2.constants.NODE_REPRESENTS = 'r'

Key for node represents

ndex2.constants.STRING_DATATYPE = 'string'

String data type for CX

ndex2.constants.VALID_ATTRIBUTE_DATATYPES = ['boolean', 'double', 'integer', 'long', 'string', 'list_of_boolean', 'list_of_double', 'list_of_integer', 'list_of_long', 'list_of_string']

List of valid attribute data types


class ndex2.util.DataConverter[source]

Base class for subclasses that convert CX data types to/from native data types

convert_value(value=None, datatype=None)[source]

Defines method to converts value from CX to native data type using datatype as a guide


NotImplementedError – Always raises this error cause subclasses should implement


Always raises NotImplementedError

class ndex2.util.PandasDataConverter[source]

Converts CX values to native Python data types via PandasDataConverter.convert_value() method

Added in version 3.5.0.

convert_value(value=None, datatype=None)[source]

Converts value parameter passed in to type based on value of datatype parameter passed in. This is used in data conversion by to_pandas_dataframe()

Added in version 3.5.0.

Conversion rules for different values of datatype parameter:

Example usage:

from ndex2.util import PandasDataConverter

converter = PandasDataConverter()

# converts number to type str
res = converter.convert_value(123, 'string')

# would output <class 'str'>

NDExError – If there is an error with conversion


Converted value

Return type:

list, str, int, float, or bool

class ndex2.client.DecimalEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)[source]

Custom json.JSONEncoder that handles numpy.integer, decimal.Decimal, and bytes that can appear in CX data

Constructor for JSONEncoder, with sensible defaults.

If skipkeys is false, then it is a TypeError to attempt encoding of keys that are not str, int, float or None. If skipkeys is True, such items are simply skipped.

If ensure_ascii is true, the output is guaranteed to be str objects with all incoming non-ASCII characters escaped. If ensure_ascii is false, the output can contain non-ASCII characters.

If check_circular is true, then lists, dicts, and custom encoded objects will be checked for circular references during encoding to prevent an infinite recursion (which would cause an RecursionError). Otherwise, no such check takes place.

If allow_nan is true, then NaN, Infinity, and -Infinity will be encoded as such. This behavior is not JSON specification compliant, but is consistent with most JavaScript based encoders and decoders. Otherwise, it will be a ValueError to encode such floats.

If sort_keys is true, then the output of dictionaries will be sorted by key; this is useful for regression tests to ensure that JSON serializations can be compared on a day-to-day basis.

If indent is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines. None is the most compact representation.

If specified, separators should be an (item_separator, key_separator) tuple. The default is (’, ‘, ‘: ‘) if indent is None and (‘,’, ‘: ‘) otherwise. To get the most compact JSON representation, you should specify (‘,’, ‘:’) to eliminate whitespace.

If specified, default is a function that gets called for objects that can’t otherwise be serialized. It should return a JSON encodable version of the object or raise a TypeError.


Overrides default behavior by converting numpy.integer to int, decimal.Decimal to float, and bytes to ascii decoded str and defaults to json.JSONEncoder() for all other object types for o


o – object to convert


converted object o


class ndex2.exceptions.NDExError[source]

Base Exception for all NDEx2 Python Client Exceptions


Many methods in this code base still incorrectly raise errors not derived from this base class

class ndex2.exceptions.NDExNotFoundError[source]

Raised if resource requested was not found

class ndex2.exceptions.NDExUnauthorizedError[source]

Raised if unable to authenticate, either due to lack of or invalid credentials.

class ndex2.exceptions.NDExInvalidParameterError[source]

Raised if invalid parameter is passed in

class ndex2.exceptions.NDExInvalidCXError[source]

Raised due to invalid CX

class ndex2.exceptions.NDExUnsupportedCallError[source]

Raised if call is unsupported, for example a method that is only supported in 2.0+ of NDEx server is attempted against a server running 1.0

class ndex2.exceptions.NDExInvalidCX2Error[source]

Raised due to invalid CX

Added in version 3.6.0.

class ndex2.exceptions.NDExAlreadyExists[source]

Raised when node, edge etc. already exists.

Added in version 3.6.0.