Skip to main content

Class allowing for data models equivalently represented as Python dictionaries, JSON, and XML

Project description

Introduction

The DataModelDict class is used for handling data models that have equivalent representations in XML, JSON, and Python. Constructing data models in this way is convenient as it supports compatibility across different software tools, such as different types of databases.

The DataModelDict class:

  • is a child of OrderedDict,

  • has methods for converting to/from XML and JSON,

  • has methods for searching through elements, and

  • has methods that help with constructing and interacting with

    compliant data models.

Setup

The code has no requirements that limit which systems it can be used on, i.e. it should work on Linux, Mac and Windows computers.

The latest release can be installed using pip:

pip install DataModelDict

The code and all documentation is hosted on GitHub and can be directly downloaded at https://github.com/usnistgov/DataModelDict.

Conversions

Some considerations need to be taken into account for designing data models that allow for exact reversible transformations between the three formats:

  • Valid, full XML requires that there is exactly one root element.

    In other words, the top-level DataModelDict of a data model can have only one key.

  • Do not use lists of lists for representing data. The XML

    conversions are only reversible for lists of values or lists of dictionaries. Future updates may allow this.

  • Avoid using XML attributes if possible. While the XML conversions

    do reversibly handle attributes, it complicates the Python and JSON representations.

  • Embedded XML content, i.e. “text with <embed>embedded</embed>

    content”, might not be reversible:

  • XML subelements of the same name within an element should be given

    consecutively. When parsed, all values of subelements of the same name are collected together in a list. This will alter the original order of subelements if matching names were not originally consecutive.

Conversion from Python to JSON

The Python-JSON conversions use the standard Python JSON library. In converting from Python to JSON, all elements of the DataModelDict must be an instance of a supported data type (with unicode and long being specific to Python 2).

Python

JSON

dict

object

list, tuple

array

str, unicode

string

int, long, float

number

True

true

False

false

None

null

np.nan

NaN

np.inf

Infinity

-np.inf

-Infinity

As DataModelDict is a child of OrderedDict, it registers as being an instance of dict. Any other objects would first need to be converted to one of these types, e.g. a numpy array would need to be converted to a list.

Conversion from Python to XML

The Python-XML conversions use the xmltodict Python package. The XML content is constructed based on the Python data types.

Python

XML

dict

subelement

list, tuple

repeated element

str, unicode

text

int, long, float

text (from repr)

True

text = True

False

text = False

None

empty text field

np.nan

text = NaN

np.inf

text = Infinity

-np.inf

text = -Infinity

Some characters in the XML text fields will also be converted to avoid conflicts.

  • XML limited characters such as <, > and & are converted to their

    HTML entities.

  • n, t, r are converted to n, t, and r

Any dictionary keys starting with ‘@’ will be converted into XML attributes, and the dictionary key ‘#text’ is interpreted as the text value of the element.

Conversion from JSON to Python

The Python-JSON conversions use the standard Python JSON library. In converting from JSON to Python, the conversions of types is straight-forward.

JSON

Python 2

Python 3

object

DataModelDict

DataModelDict

array

list

list

string

unicode

str

number (int)

long

int

number (real)

float

float

true

True

True

false

False

False

null

None

None

NaN

np.nan

np.nan

Infinity

np.inf

np.inf

-Infinity

-np.inf

-np.inf

Conversion from XML to Python

The Python-XML conversions use the xmltodict Python package. The text fields will be interpreted based on the following sequential tests:

XML text

Python 2

Python 3

== ‘True’

True

True

== ‘False’

False

False

== ‘’

None

None

== ‘NaN’

np.nan

np.nan

== ‘Infinity’

np.inf

np.inf

== ‘-Infinity’

-np.inf

-np.inf

try: int(text)

long

int

try: float(text)

float

float

otherwise

unicode

str

The reverse conversions are done for the special characters mentioned in the Conversion from Python to XML section above.

Any ‘attr’ attribute fields are converted to elements named ‘@attr’ and corresponding ‘#text’ elements are created if needed.

Class Documentation

DataModelDict class for representing data models equivalently in Python, JSON, and XML.

class DataModelDict.DataModelDict(*args, kwargs)

Bases: collections.OrderedDict, object

Class for handling json/xml equivalent data structures.

append(key, value)

Adds a value for element key by either adding key to the dictionary or appending the value as a list to any current value.

Parameters:
  • key (str) – The dictionary key.

  • value – The value to add to the dictionary key. If

    key exists, the element is converted to a list if needed and value is appended.

aslist(key)

Gets the value of a dictionary key as a list. Useful for elements whose values may or may not be lists.

Parameters:

key (str) – Dictionary key

Returns:

The dictionary’s element value or [value] depending on if it already is a list.

Return type:

list

find(key, yes={}, no={})

Return the value of a subelement at any level uniquely identified by the specified conditions.

Parameters:
  • key (str) – Dictionary key to search for.

  • yes (dict) – Key-value terms which the subelement

    must have to be considered a match.

  • no (dict) – Key-value terms which the subelement

    must not have to be considered a match.

Returns:

The value of the uniquely identified subelement.

Return type:

any

Raises:

ValueError – If exactly one matching subelement is not identified.

finds(key, yes={}, no={})

Finds the values of all subelements at any level identified by the specified conditions.

Parameters:
  • key (str) – Dictionary key to search for.

  • yes (dict) – Key-value terms which the subelement

    must have to be considered a match.

  • no (dict) – Key-value terms which the subelement

    must not have to be considered a match.

Returns:

The values of any matching subelements.

Return type:

list

iteraslist(key)

Iterates through the values of a dictionary key. Useful for elements whose values may or may not be lists.

Parameters:

key (str) – Dictionary key

Yields:

any – The dictionary’s value or each element in value if value is a list.

iterfinds(key, yes={}, no={})

Iterates over the values of all subelements at any level identified by the specified conditions.

Parameters:
  • key (str) – Dictionary key to search for.

  • yes (dict) – Key-value terms which the subelement

    must have to be considered a match.

  • no (dict) – Key-value terms which the subelement

    must not have to be considered a match.

Yields:

any – The values of any matching subelements.

iterpaths(key, yes={}, no={})

Iterates over the path lists to all elements at any level identified by the specified conditions.

Parameters:
  • key (str) – Dictionary key to search for.

  • yes (dict) – Key-value terms which the subelement

    must have to be considered a match.

  • no (dict) – Key-value terms which the subelement

    must not have to be considered a match.

Yields:

list of str – The path lists to any matching subelements.

itervaluepaths()

Iterates over path lists to all value elements at any level.

Yields:

list – The path lists to all value subelements.

json(fp=None, *args, kwargs)

Converts the DataModelDict to JSON content.

Parameters:
  • fp (file-like object or None, optional) – An

    open file to write the content to. If None (default), then the content is returned as a str.

  • *args (any) – Any other positional arguments

    accepted by json.dump(s)

  • **kwargs (any) – Any other keyword arguments

    accepted by json.dump(s)

Returns:

The JSON content (only returned if fp is None).

Return type:

str, optional

load(model, format=None)

Read in values from a json/xml string or file-like object.

Parameters:
  • model (str or file-like object) – The XML or

    JSON content to read. This is allowed to be either a file path, a string representation, or an open file-like object in byte mode.

  • format (str or None, optional) – Allows for

    the format of the content to be explicitly stated (‘xml’ or ‘json’). If None (default), will try to determine which format based on if the first character of model is ‘<’ or ‘{‘.

Raises:

ValueError – If format is None and unable to identify XML/JON content, or if format is not equal to ‘xml’ or ‘json’.

path(key, yes={}, no={})

Return the path list of a subelement at any level uniquely identified by the specified conditions. Issues an error if either no match, or multiple matches are found.

Parameters:
  • key (str) – Dictionary key to search for.

  • yes (dict) – Key-value terms which the subelement

    must have to be considered a match.

  • no (dict) – Key-value terms which the subelement

    must not have to be considered a match.

Returns:

The subelement path list to the uniquely identified subelement.

Return type:

list of str

Raises:

ValueError – If exactly one matching subelement is not identified.

paths(key, yes={}, no={})

Return a list of all path lists of all elements at any level identified by the specified conditions.

Parameters:
  • key (str) – Dictionary key to search for.

  • yes (dict) – Key-value terms which the subelement

    must have to be considered a match.

  • no (dict) – Key-value terms which the subelement

    must not have to be considered a match.

Returns:

The path lists for any matching subelements.

Return type:

list

xml(fp=None, indent=None, kwargs)

Return the DataModelDict as XML content.

Parameters:
  • fp (file-like object or None, optional) – An

    open file to write the content to. If None (default), then the content is returned as a str.

  • indent (int, str or None, optional) – If

    int, number of spaces to indent lines. If str, will use that as the indentation. If None (default), the content will be inline.

  • **kwargs (any) – Other keywords supported by

    xmltodict.unparse, except for output which is replaced by fp, and preprocessor, which is controlled.

Returns:

The XML content (only returned if fp is None).

Return type:

str, optional

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DataModelDict-0.9.7.tar.gz (13.5 kB view details)

Uploaded Source

Built Distribution

DataModelDict-0.9.7-py3-none-any.whl (11.4 kB view details)

Uploaded Python 3

File details

Details for the file DataModelDict-0.9.7.tar.gz.

File metadata

  • Download URL: DataModelDict-0.9.7.tar.gz
  • Upload date:
  • Size: 13.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for DataModelDict-0.9.7.tar.gz
Algorithm Hash digest
SHA256 b1be7573cb4401aa250fd00f2e6392543f6f2498f8e02f6313595aa220e5c99e
MD5 a2de4cc9b467ac6e7aba65b9c9e4528d
BLAKE2b-256 f66124018e6544067f8f655419d3d6a927779e099e10b825c2ed2f94fef24f96

See more details on using hashes here.

File details

Details for the file DataModelDict-0.9.7-py3-none-any.whl.

File metadata

  • Download URL: DataModelDict-0.9.7-py3-none-any.whl
  • Upload date:
  • Size: 11.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for DataModelDict-0.9.7-py3-none-any.whl
Algorithm Hash digest
SHA256 1a82a133f095cf2425ffc5560718f2a568de04cc252cc4b4663207418bb4669d
MD5 e0f9c15cbba3395e5a29badf6b79257e
BLAKE2b-256 9a2b4c2eee4b057f2884e0c3c1fad14e96a53ce978456d7a91dee3582be158f2

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page