azure.ai.formrecognizer package Azure SDK for Python 2.0.0 documentation

Summary of all the custom models on the account.

New in version v2.1: Support for to_dict and from_dict methods

Converts a dict in the shape of a AccountProperties to the model itself.

data (dict) – A dictionary in the shape of AccountProperties.

AccountProperties

AccountProperties

Returns a dict representation of AccountProperties.

dict

dict

Current count of trained custom models.

Max number of models that can be trained for this account.

An address field value.

New in version 2023-07-31: The unit, city_district, state_district, suburb, house, and level properties.

Converts a dict in the shape of a AddressValue to the model itself.

data (dict) – A dictionary in the shape of AddressValue.

AddressValue

AddressValue

Returns a dict representation of AddressValue.

dict

dict

Name of city, town, village, etc.

Districts or boroughs within a city, such as Brooklyn in New York City or City of Westminster in London.

Country/region.

Building name, such as World Trade Center.

House or building number.

Floor number, such as 3F.

Post office box number.

Postal code used for mail sorting.

Street name.

First-level administrative division.

Second-level administrative division used in certain locales.

Street-level address, excluding city, state, countryRegion, and postalCode.

Unofficial neighborhood name, like Chinatown.

Apartment or office number.

Document analysis features to enable.

Return a capitalized version of the string.

More specifically, make the first character have upper case and the rest lower case.

Return a version of the string suitable for caseless comparisons.

Return a centered string of length width.

Padding is done using the specified fill character (default is a space).

Return the number of non-overlapping occurrences of substring sub in string S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Encode the string using the codec registered for encoding.

The encoding in which to encode the string.

The error handling scheme to use for encoding errors. The default is ‘strict’ meaning that encoding errors raise a UnicodeEncodeError. Other possible values are ‘ignore’, ‘replace’ and ‘xmlcharrefreplace’ as well as any other name registered with codecs.register_error that can handle UnicodeEncodeErrors.

Return True if S ends with the specified suffix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. suffix can also be a tuple of strings to try.

Return a copy where all tab characters are expanded using spaces.

If tabsize is not given, a tab size of 8 characters is assumed.

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

Return a formatted version of S, using substitutions from args and kwargs. The substitutions are identified by braces (‘{’ and ‘}’).

Return a formatted version of S, using substitutions from mapping. The substitutions are identified by braces (‘{’ and ‘}’).

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

Return True if the string is an alpha-numeric string, False otherwise.

A string is alpha-numeric if all characters in the string are alpha-numeric and there is at least one character in the string.

Return True if the string is an alphabetic string, False otherwise.

A string is alphabetic if all characters in the string are alphabetic and there is at least one character in the string.

Return True if all characters in the string are ASCII, False otherwise.

ASCII characters have code points in the range U+0000-U+007F. Empty string is ASCII too.

Return True if the string is a decimal string, False otherwise.

A string is a decimal string if all characters in the string are decimal and there is at least one character in the string.

Return True if the string is a digit string, False otherwise.

A string is a digit string if all characters in the string are digits and there is at least one character in the string.

Return True if the string is a valid Python identifier, False otherwise.

Call keyword.iskeyword(s) to test whether string s is a reserved identifier, such as “def” or “class”.

Return True if the string is a lowercase string, False otherwise.

A string is lowercase if all cased characters in the string are lowercase and there is at least one cased character in the string.

Return True if the string is a numeric string, False otherwise.

A string is numeric if all characters in the string are numeric and there is at least one character in the string.

Return True if the string is printable, False otherwise.

A string is printable if all of its characters are considered printable in repr() or if it is empty.

Return True if the string is a whitespace string, False otherwise.

A string is whitespace if all characters in the string are whitespace and there is at least one character in the string.

Return True if the string is a title-cased string, False otherwise.

In a title-cased string, upper- and title-case characters may only follow uncased characters and lowercase characters only cased ones.

Return True if the string is an uppercase string, False otherwise.

A string is uppercase if all cased characters in the string are uppercase and there is at least one cased character in the string.

Concatenate any number of strings.

The string whose method is called is inserted in between each given string. The result is returned as a new string.

Example: ‘.’.join([‘ab’, ‘pq’, ‘rs’]) -> ‘ab.pq.rs’

Return a left-justified string of length width.

Padding is done using the specified fill character (default is a space).

Return a copy of the string converted to lowercase.

Return a copy of the string with leading whitespace removed.

If chars is given and not None, remove characters in chars instead.

Return a translation table usable for str.translate().

If there is only one argument, it must be a dictionary mapping Unicode ordinals (integers) or characters to Unicode ordinals, strings or None. Character keys will be then converted to ordinals. If there are two arguments, they must be strings of equal length, and in the resulting dictionary, each character in x will be mapped to the character at the same position in y. If there is a third argument, it must be a string, whose characters will be mapped to None in the result.

Partition the string into three parts using the given separator.

This will search for the separator in the string. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing the original string and two empty strings.

Return a str with the given prefix string removed if present.

If the string starts with the prefix string, return string[len(prefix):]. Otherwise, return a copy of the original string.

Return a str with the given suffix string removed if present.

If the string ends with the suffix string and that suffix is not empty, return string[:-len(suffix)]. Otherwise, return a copy of the original string.

Return a copy with all occurrences of substring old replaced by new.

Maximum number of occurrences to replace. -1 (the default value) means replace all occurrences.

If the optional argument count is given, only the first count occurrences are replaced.

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

Return a right-justified string of length width.

Padding is done using the specified fill character (default is a space).

Partition the string into three parts using the given separator.

This will search for the separator in the string, starting at the end. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing two empty strings and the original string.

Return a list of the substrings in the string, using sep as the separator string.

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the end of the string and works to the front.

Return a copy of the string with trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

Return a list of the substrings in the string, using sep as the separator string.

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the front of the string and works to the end.

Note, str.split() is mainly useful for data that has been intentionally delimited. With natural text that includes punctuation, consider using the regular expression module.

Return a list of the lines in the string, breaking at line boundaries.

Line breaks are not included in the resulting list unless keepends is given and true.

Return True if S starts with the specified prefix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. prefix can also be a tuple of strings to try.

Return a copy of the string with leading and trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

Convert uppercase characters to lowercase and lowercase characters to uppercase.

Return a version of the string where each word is titlecased.

More specifically, words start with uppercased characters and all remaining cased characters have lower case.

Replace each character in the string using the given translation table.

Translation table, which must be a mapping of Unicode ordinals to Unicode ordinals, strings, or None.

The table must implement lookup/indexing via __getitem__, for instance a dictionary or list. If this operation raises LookupError, the character is left untouched. Characters mapped to None are deleted.

Return a copy of the string converted to uppercase.

Pad a numeric string with zeros on the left, to fill a field of the given width.

The string is never truncated.

Enable the detection of barcodes in the document.

Enable the detection of mathematical expressions in the document.

Enable the detection of general key value pairs (form fields) in the document.

Enable the detection of the text content language.

Perform OCR at a higher resolution to handle documents with fine print.

Enable the recognition of various font styles.

Document analysis result.

Converts a dict in the shape of a AnalyzeResult to the model itself.

data (dict) – A dictionary in the shape of AnalyzeResult.

AnalyzeResult

AnalyzeResult

Returns a dict representation of AnalyzeResult.

dict

dict

API version used to produce this result.

Concatenate string representation of all textual and visual elements in reading order.

Extracted documents.

Extracted key-value pairs.

Detected languages in the document.

Model ID used to produce this result.

Analyzed pages.

Extracted paragraphs.

Extracted font styles.

Extracted tables.

An object describing the location and semantic content of a document.

Converts a dict in the shape of a AnalyzedDocument to the model itself.

data (dict) – A dictionary in the shape of AnalyzedDocument.

AnalyzedDocument

AnalyzedDocument

Returns a dict representation of AnalyzedDocument.

dict

dict

Bounding regions covering the document.

Confidence of correctly extracting the document.

The type of document that was analyzed.

A dictionary of named field values.

The location of the document in the reading order concatenated content.

Content source for a file list in Azure Blob Storage.

Converts a dict in the shape of a BlobFileListSource to the model itself.

data (dict) – A dictionary in the shape of BlobFileListSource.

BlobFileListSource

BlobFileListSource

Returns a dict representation of BlobFileListSource.

Dict[str, Any]

Dict[str, Any]

Azure Blob Storage container URL.

Path to a JSONL file within the container specifying a subset of documents for training.

Content source for Azure Blob Storage.

Converts a dict in the shape of a BlobSource to the model itself.

data (dict) – A dictionary in the shape of BlobSource.

BlobSource

BlobSource

Returns a dict representation of BlobSource.

Dict[str, Any]

Dict[str, Any]

Azure Blob Storage container URL.

Blob name prefix.

The bounding region corresponding to a page.

Converts a dict in the shape of a BoundingRegion to the model itself.

data (dict) – A dictionary in the shape of BoundingRegion.

BoundingRegion

BoundingRegion

Returns a dict representation of BoundingRegion.

dict

dict

The 1-based number of the page in which this content is present.

A list of points representing the bounding polygon that outlines the document component. The points are listed in clockwise order relative to the document component orientation starting from the top-left. Units are in pixels for images and inches for PDF.

Training data source.

Converts a dict in the shape of a ClassifierDocumentTypeDetails to the model itself.

data (dict) – A dictionary in the shape of ClassifierDocumentTypeDetails.

ClassifierDocumentTypeDetails

ClassifierDocumentTypeDetails

Returns a dict representation of ClassifierDocumentTypeDetails.

Dict[str, Any]

Dict[str, Any]

Content source containing the training data.

“azureBlob” and “azureBlobFileList”.

Type of training data source, known values are

A currency value element.

New in version 2023-07-31: The code property.

Converts a dict in the shape of a CurrencyValue to the model itself.

data (dict) – A dictionary in the shape of CurrencyValue.

CurrencyValue

CurrencyValue

Returns a dict representation of CurrencyValue.

dict

dict

The currency amount.

Resolved currency code (ISO 4217), if any.

The currency symbol, if found.

Details regarding the custom models under the Form Recognizer resource.

Converts a dict in the shape of a CustomDocumentModelsDetails to the model itself.

data (dict) – A dictionary in the shape of CustomDocumentModelsDetails.

CustomDocumentModelsDetails

CustomDocumentModelsDetails

Returns a dict representation of CustomDocumentModelsDetails.

dict

dict

Number of custom models in the current resource.

Maximum number of custom models supported in the current resource.

Represents a trained model.

New in version v2.1: The model_name and properties properties, support for to_dict and from_dict methods

Converts a dict in the shape of a CustomFormModel to the model itself.

data (dict) – A dictionary in the shape of CustomFormModel.

CustomFormModel

CustomFormModel

Returns a dict representation of CustomFormModel.

dict

dict

List of any training errors.

The unique identifier of this model.

Optional user defined model name.

Optional model properties.

Status indicating the model’s readiness for use, CustomFormModelStatus. Possible values include: ‘creating’, ‘ready’, ‘invalid’.

A list of submodels that are part of this model, each of which can recognize and extract fields from a different type of form.

Date and time (UTC) when model training completed.

Metadata about each of the documents used to train the model.

The date and time (UTC) when model training was started.

A field that the model will extract from forms it analyzes.

New in version v2.1: Support for to_dict and from_dict methods

Converts a dict in the shape of a CustomFormModelField to the model itself.

data (dict) – A dictionary in the shape of CustomFormModelField.

CustomFormModelField

CustomFormModelField

Returns a dict representation of CustomFormModelField.

dict

dict

The estimated recognition accuracy for this field.

The form fields label on the form.

Canonical name; uniquely identifies a field within the form.

Custom model information.

New in version v2.1: The model_name and properties properties, support for to_dict and from_dict methods

Converts a dict in the shape of a CustomFormModelInfo to the model itself.

data (dict) – A dictionary in the shape of CustomFormModelInfo.

CustomFormModelInfo

CustomFormModelInfo

Returns a dict representation of CustomFormModelInfo.

dict

dict

The unique identifier of the model.

Optional user defined model name.

Optional model properties.

The status of the model, CustomFormModelStatus. Possible values include: ‘creating’, ‘ready’, ‘invalid’.

Date and time (UTC) when model training completed.

Date and time (UTC) when model training was started.

Optional model properties.

New in version v2.1: Support for to_dict and from_dict methods

Converts a dict in the shape of a CustomFormModelProperties to the model itself.

data (dict) – A dictionary in the shape of CustomFormModelProperties.

CustomFormModelProperties

CustomFormModelProperties

Returns a dict representation of CustomFormModelProperties.

dict

dict

false).

Is this model composed? (default

Status indicating the model’s readiness for use.

Return a capitalized version of the string.

More specifically, make the first character have upper case and the rest lower case.

Return a version of the string suitable for caseless comparisons.

Return a centered string of length width.

Padding is done using the specified fill character (default is a space).

Return the number of non-overlapping occurrences of substring sub in string S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Encode the string using the codec registered for encoding.

The encoding in which to encode the string.

The error handling scheme to use for encoding errors. The default is ‘strict’ meaning that encoding errors raise a UnicodeEncodeError. Other possible values are ‘ignore’, ‘replace’ and ‘xmlcharrefreplace’ as well as any other name registered with codecs.register_error that can handle UnicodeEncodeErrors.

Return True if S ends with the specified suffix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. suffix can also be a tuple of strings to try.

Return a copy where all tab characters are expanded using spaces.

If tabsize is not given, a tab size of 8 characters is assumed.

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

Return a formatted version of S, using substitutions from args and kwargs. The substitutions are identified by braces (‘{’ and ‘}’).

Return a formatted version of S, using substitutions from mapping. The substitutions are identified by braces (‘{’ and ‘}’).

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

Return True if the string is an alpha-numeric string, False otherwise.

A string is alpha-numeric if all characters in the string are alpha-numeric and there is at least one character in the string.

Return True if the string is an alphabetic string, False otherwise.

A string is alphabetic if all characters in the string are alphabetic and there is at least one character in the string.

Return True if all characters in the string are ASCII, False otherwise.

ASCII characters have code points in the range U+0000-U+007F. Empty string is ASCII too.

Return True if the string is a decimal string, False otherwise.

A string is a decimal string if all characters in the string are decimal and there is at least one character in the string.

Return True if the string is a digit string, False otherwise.

A string is a digit string if all characters in the string are digits and there is at least one character in the string.

Return True if the string is a valid Python identifier, False otherwise.

Call keyword.iskeyword(s) to test whether string s is a reserved identifier, such as “def” or “class”.

Return True if the string is a lowercase string, False otherwise.

A string is lowercase if all cased characters in the string are lowercase and there is at least one cased character in the string.

Return True if the string is a numeric string, False otherwise.

A string is numeric if all characters in the string are numeric and there is at least one character in the string.

Return True if the string is printable, False otherwise.

A string is printable if all of its characters are considered printable in repr() or if it is empty.

Return True if the string is a whitespace string, False otherwise.

A string is whitespace if all characters in the string are whitespace and there is at least one character in the string.

Return True if the string is a title-cased string, False otherwise.

In a title-cased string, upper- and title-case characters may only follow uncased characters and lowercase characters only cased ones.

Return True if the string is an uppercase string, False otherwise.

A string is uppercase if all cased characters in the string are uppercase and there is at least one cased character in the string.

Concatenate any number of strings.

The string whose method is called is inserted in between each given string. The result is returned as a new string.

Example: ‘.’.join([‘ab’, ‘pq’, ‘rs’]) -> ‘ab.pq.rs’

Return a left-justified string of length width.

Padding is done using the specified fill character (default is a space).

Return a copy of the string converted to lowercase.

Return a copy of the string with leading whitespace removed.

If chars is given and not None, remove characters in chars instead.

Return a translation table usable for str.translate().

If there is only one argument, it must be a dictionary mapping Unicode ordinals (integers) or characters to Unicode ordinals, strings or None. Character keys will be then converted to ordinals. If there are two arguments, they must be strings of equal length, and in the resulting dictionary, each character in x will be mapped to the character at the same position in y. If there is a third argument, it must be a string, whose characters will be mapped to None in the result.

Partition the string into three parts using the given separator.

This will search for the separator in the string. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing the original string and two empty strings.

Return a str with the given prefix string removed if present.

If the string starts with the prefix string, return string[len(prefix):]. Otherwise, return a copy of the original string.

Return a str with the given suffix string removed if present.

If the string ends with the suffix string and that suffix is not empty, return string[:-len(suffix)]. Otherwise, return a copy of the original string.

Return a copy with all occurrences of substring old replaced by new.

Maximum number of occurrences to replace. -1 (the default value) means replace all occurrences.

If the optional argument count is given, only the first count occurrences are replaced.

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

Return a right-justified string of length width.

Padding is done using the specified fill character (default is a space).

Partition the string into three parts using the given separator.

This will search for the separator in the string, starting at the end. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing two empty strings and the original string.

Return a list of the substrings in the string, using sep as the separator string.

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the end of the string and works to the front.

Return a copy of the string with trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

Return a list of the substrings in the string, using sep as the separator string.

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the front of the string and works to the end.

Note, str.split() is mainly useful for data that has been intentionally delimited. With natural text that includes punctuation, consider using the regular expression module.

Return a list of the lines in the string, breaking at line boundaries.

Line breaks are not included in the resulting list unless keepends is given and true.

Return True if S starts with the specified prefix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. prefix can also be a tuple of strings to try.

Return a copy of the string with leading and trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

Convert uppercase characters to lowercase and lowercase characters to uppercase.

Return a version of the string where each word is titlecased.

More specifically, words start with uppercased characters and all remaining cased characters have lower case.

Replace each character in the string using the given translation table.

Translation table, which must be a mapping of Unicode ordinals to Unicode ordinals, strings, or None.

The table must implement lookup/indexing via __getitem__, for instance a dictionary or list. If this operation raises LookupError, the character is left untouched. Characters mapped to None are deleted.

Return a copy of the string converted to uppercase.

Pad a numeric string with zeros on the left, to fill a field of the given width.

The string is never truncated.

Represents a submodel that extracts fields from a specific type of form.

New in version v2.1: The model_id property, support for to_dict and from_dict methods

Converts a dict in the shape of a CustomFormSubmodel to the model itself.

data (dict) – A dictionary in the shape of CustomFormSubmodel.

CustomFormSubmodel

CustomFormSubmodel

Returns a dict representation of CustomFormSubmodel.

dict

dict

The mean of the model’s field accuracies.

A dictionary of the fields that this submodel will recognize from the input document. The fields dictionary keys are the name of the field. For models trained with labels, this is the training-time label of the field. For models trained without labels, a unique name is generated for each field.

Type of form this submodel recognizes.

Model identifier of the submodel.

Form Recognizer API versions supported by DocumentAnalysisClient and DocumentModelAdministrationClient.

Return a capitalized version of the string.

More specifically, make the first character have upper case and the rest lower case.

Return a version of the string suitable for caseless comparisons.

Return a centered string of length width.

Padding is done using the specified fill character (default is a space).

Return the number of non-overlapping occurrences of substring sub in string S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Encode the string using the codec registered for encoding.

The encoding in which to encode the string.

The error handling scheme to use for encoding errors. The default is ‘strict’ meaning that encoding errors raise a UnicodeEncodeError. Other possible values are ‘ignore’, ‘replace’ and ‘xmlcharrefreplace’ as well as any other name registered with codecs.register_error that can handle UnicodeEncodeErrors.

Return True if S ends with the specified suffix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. suffix can also be a tuple of strings to try.

Return a copy where all tab characters are expanded using spaces.

If tabsize is not given, a tab size of 8 characters is assumed.

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

Return a formatted version of S, using substitutions from args and kwargs. The substitutions are identified by braces (‘{’ and ‘}’).

Return a formatted version of S, using substitutions from mapping. The substitutions are identified by braces (‘{’ and ‘}’).

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

Return True if the string is an alpha-numeric string, False otherwise.

A string is alpha-numeric if all characters in the string are alpha-numeric and there is at least one character in the string.

Return True if the string is an alphabetic string, False otherwise.

A string is alphabetic if all characters in the string are alphabetic and there is at least one character in the string.

Return True if all characters in the string are ASCII, False otherwise.

ASCII characters have code points in the range U+0000-U+007F. Empty string is ASCII too.

Return True if the string is a decimal string, False otherwise.

A string is a decimal string if all characters in the string are decimal and there is at least one character in the string.

Return True if the string is a digit string, False otherwise.

A string is a digit string if all characters in the string are digits and there is at least one character in the string.

Return True if the string is a valid Python identifier, False otherwise.

Call keyword.iskeyword(s) to test whether string s is a reserved identifier, such as “def” or “class”.

Return True if the string is a lowercase string, False otherwise.

A string is lowercase if all cased characters in the string are lowercase and there is at least one cased character in the string.

Return True if the string is a numeric string, False otherwise.

A string is numeric if all characters in the string are numeric and there is at least one character in the string.

Return True if the string is printable, False otherwise.

A string is printable if all of its characters are considered printable in repr() or if it is empty.

Return True if the string is a whitespace string, False otherwise.

A string is whitespace if all characters in the string are whitespace and there is at least one character in the string.

Return True if the string is a title-cased string, False otherwise.

In a title-cased string, upper- and title-case characters may only follow uncased characters and lowercase characters only cased ones.

Return True if the string is an uppercase string, False otherwise.

A string is uppercase if all cased characters in the string are uppercase and there is at least one cased character in the string.

Concatenate any number of strings.

The string whose method is called is inserted in between each given string. The result is returned as a new string.

Example: ‘.’.join([‘ab’, ‘pq’, ‘rs’]) -> ‘ab.pq.rs’

Return a left-justified string of length width.

Padding is done using the specified fill character (default is a space).

Return a copy of the string converted to lowercase.

Return a copy of the string with leading whitespace removed.

If chars is given and not None, remove characters in chars instead.

Return a translation table usable for str.translate().

If there is only one argument, it must be a dictionary mapping Unicode ordinals (integers) or characters to Unicode ordinals, strings or None. Character keys will be then converted to ordinals. If there are two arguments, they must be strings of equal length, and in the resulting dictionary, each character in x will be mapped to the character at the same position in y. If there is a third argument, it must be a string, whose characters will be mapped to None in the result.

Partition the string into three parts using the given separator.

This will search for the separator in the string. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing the original string and two empty strings.

Return a str with the given prefix string removed if present.

If the string starts with the prefix string, return string[len(prefix):]. Otherwise, return a copy of the original string.

Return a str with the given suffix string removed if present.

If the string ends with the suffix string and that suffix is not empty, return string[:-len(suffix)]. Otherwise, return a copy of the original string.

Return a copy with all occurrences of substring old replaced by new.

Maximum number of occurrences to replace. -1 (the default value) means replace all occurrences.

If the optional argument count is given, only the first count occurrences are replaced.

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

Return a right-justified string of length width.

Padding is done using the specified fill character (default is a space).

Partition the string into three parts using the given separator.

This will search for the separator in the string, starting at the end. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing two empty strings and the original string.

Return a list of the substrings in the string, using sep as the separator string.

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the end of the string and works to the front.

Return a copy of the string with trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

Return a list of the substrings in the string, using sep as the separator string.

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the front of the string and works to the end.

Note, str.split() is mainly useful for data that has been intentionally delimited. With natural text that includes punctuation, consider using the regular expression module.

Return a list of the lines in the string, breaking at line boundaries.

Line breaks are not included in the resulting list unless keepends is given and true.

Return True if S starts with the specified prefix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. prefix can also be a tuple of strings to try.

Return a copy of the string with leading and trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

Convert uppercase characters to lowercase and lowercase characters to uppercase.

Return a version of the string where each word is titlecased.

More specifically, words start with uppercased characters and all remaining cased characters have lower case.

Replace each character in the string using the given translation table.

Translation table, which must be a mapping of Unicode ordinals to Unicode ordinals, strings, or None.

The table must implement lookup/indexing via __getitem__, for instance a dictionary or list. If this operation raises LookupError, the character is left untouched. Characters mapped to None are deleted.

Return a copy of the string converted to uppercase.

Pad a numeric string with zeros on the left, to fill a field of the given width.

The string is never truncated.

This is the default version

DocumentAnalysisClient analyzes information from documents and images, and classifies documents. It is the interface to use for analyzing with prebuilt models (receipts, business cards, invoices, identity documents, among others), analyzing layout from documents, analyzing general document types, and analyzing custom documents with built models (to see a full list of models supported by the service, see: https://aka.ms/azsdk/formrecognizer/models). It provides different methods based on inputs from a URL and inputs from a stream.

Note

DocumentAnalysisClient should be used with API versions 2022-08-31 and up. To use API versions <=v2.1, instantiate a FormRecognizerClient.

api_version (str or DocumentAnalysisApiVersion) – The API version of the service to use for requests. It defaults to the latest service version. Setting to an older version may result in reduced feature compatibility. To use API versions <=v2.1, instantiate a FormRecognizerClient.

New in version 2022-08-31: The DocumentAnalysisClient and its client methods.

Example:

from azure.core.credentials import AzureKeyCredential from azure.ai.formrecognizer import DocumentAnalysisClient endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] document_analysis_client = DocumentAnalysisClient(endpoint, AzureKeyCredential(key)) 

"""DefaultAzureCredential will use the values from these environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET """ from azure.ai.formrecognizer import DocumentAnalysisClient from azure.identity import DefaultAzureCredential endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] credential = DefaultAzureCredential() document_analysis_client = DocumentAnalysisClient(endpoint, credential) 

Analyze field text and semantic values from a given document.

• pages (str) – Custom page numbers for multi-page documents(PDF/TIFF). Input the page numbers and/or ranges of pages you want to get in the result. For a range of pages, use a hyphen, like pages=”1-3, 5-6”. Separate each page number or range with a comma.

• locale (str) – Locale hint of the input document. See supported locales here: https://aka.ms/azsdk/formrecognizer/supportedlocales.

• features (list[str]) – Document analysis features to enable.

An instance of an LROPoller. Call result() on the poller object to return a AnalyzeResult.

LROPoller[AnalyzeResult]

HttpResponseError –

New in version 2023-07-31: The features keyword argument.

Example:

from azure.core.credentials import AzureKeyCredential from azure.ai.formrecognizer import DocumentAnalysisClient endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] document_analysis_client = DocumentAnalysisClient( endpoint=endpoint, credential=AzureKeyCredential(key) ) with open(path_to_sample_documents, "rb") as f: poller = document_analysis_client.begin_analyze_document( "prebuilt-invoice", document=f, locale="en-US" ) invoices = poller.result() for idx, invoice in enumerate(invoices.documents): print(f"--------Analyzing invoice #{idx + 1}--------") vendor_name = invoice.fields.get("VendorName") if vendor_name: print( f"Vendor Name: {vendor_name.value} has confidence: {vendor_name.confidence}" ) vendor_address = invoice.fields.get("VendorAddress") if vendor_address: print( f"Vendor Address: {vendor_address.value} has confidence: {vendor_address.confidence}" ) vendor_address_recipient = invoice.fields.get("VendorAddressRecipient") if vendor_address_recipient: print( f"Vendor Address Recipient: {vendor_address_recipient.value} has confidence: {vendor_address_recipient.confidence}" ) customer_name = invoice.fields.get("CustomerName") if customer_name: print( f"Customer Name: {customer_name.value} has confidence: {customer_name.confidence}" ) customer_id = invoice.fields.get("CustomerId") if customer_id: print( f"Customer Id: {customer_id.value} has confidence: {customer_id.confidence}" ) customer_address = invoice.fields.get("CustomerAddress") if customer_address: print( f"Customer Address: {customer_address.value} has confidence: {customer_address.confidence}" ) customer_address_recipient = invoice.fields.get("CustomerAddressRecipient") if customer_address_recipient: print( f"Customer Address Recipient: {customer_address_recipient.value} has confidence: {customer_address_recipient.confidence}" ) invoice_id = invoice.fields.get("InvoiceId") if invoice_id: print( f"Invoice Id: {invoice_id.value} has confidence: {invoice_id.confidence}" ) invoice_date = invoice.fields.get("InvoiceDate") if invoice_date: print( f"Invoice Date: {invoice_date.value} has confidence: {invoice_date.confidence}" ) invoice_total = invoice.fields.get("InvoiceTotal") if invoice_total: print( f"Invoice Total: {invoice_total.value} has confidence: {invoice_total.confidence}" ) due_date = invoice.fields.get("DueDate") if due_date: print(f"Due Date: {due_date.value} has confidence: {due_date.confidence}") purchase_order = invoice.fields.get("PurchaseOrder") if purchase_order: print( f"Purchase Order: {purchase_order.value} has confidence: {purchase_order.confidence}" ) billing_address = invoice.fields.get("BillingAddress") if billing_address: print( f"Billing Address: {billing_address.value} has confidence: {billing_address.confidence}" ) billing_address_recipient = invoice.fields.get("BillingAddressRecipient") if billing_address_recipient: print( f"Billing Address Recipient: {billing_address_recipient.value} has confidence: {billing_address_recipient.confidence}" ) shipping_address = invoice.fields.get("ShippingAddress") if shipping_address: print( f"Shipping Address: {shipping_address.value} has confidence: {shipping_address.confidence}" ) shipping_address_recipient = invoice.fields.get("ShippingAddressRecipient") if shipping_address_recipient: print( f"Shipping Address Recipient: {shipping_address_recipient.value} has confidence: {shipping_address_recipient.confidence}" ) print("Invoice items:") for idx, item in enumerate(invoice.fields.get("Items").value): print(f"...Item #{idx + 1}") item_description = item.value.get("Description") if item_description: print( f"......Description: {item_description.value} has confidence: {item_description.confidence}" ) item_quantity = item.value.get("Quantity") if item_quantity: print( f"......Quantity: {item_quantity.value} has confidence: {item_quantity.confidence}" ) unit = item.value.get("Unit") if unit: print(f"......Unit: {unit.value} has confidence: {unit.confidence}") unit_price = item.value.get("UnitPrice") if unit_price: unit_price_code = unit_price.value.code if unit_price.value.code else "" print( f"......Unit Price: {unit_price.value}{unit_price_code} has confidence: {unit_price.confidence}" ) product_code = item.value.get("ProductCode") if product_code: print( f"......Product Code: {product_code.value} has confidence: {product_code.confidence}" ) item_date = item.value.get("Date") if item_date: print( f"......Date: {item_date.value} has confidence: {item_date.confidence}" ) tax = item.value.get("Tax") if tax: print(f"......Tax: {tax.value} has confidence: {tax.confidence}") amount = item.value.get("Amount") if amount: print( f"......Amount: {amount.value} has confidence: {amount.confidence}" ) subtotal = invoice.fields.get("SubTotal") if subtotal: print(f"Subtotal: {subtotal.value} has confidence: {subtotal.confidence}") total_tax = invoice.fields.get("TotalTax") if total_tax: print( f"Total Tax: {total_tax.value} has confidence: {total_tax.confidence}" ) previous_unpaid_balance = invoice.fields.get("PreviousUnpaidBalance") if previous_unpaid_balance: print( f"Previous Unpaid Balance: {previous_unpaid_balance.value} has confidence: {previous_unpaid_balance.confidence}" ) amount_due = invoice.fields.get("AmountDue") if amount_due: print( f"Amount Due: {amount_due.value} has confidence: {amount_due.confidence}" ) service_start_date = invoice.fields.get("ServiceStartDate") if service_start_date: print( f"Service Start Date: {service_start_date.value} has confidence: {service_start_date.confidence}" ) service_end_date = invoice.fields.get("ServiceEndDate") if service_end_date: print( f"Service End Date: {service_end_date.value} has confidence: {service_end_date.confidence}" ) service_address = invoice.fields.get("ServiceAddress") if service_address: print( f"Service Address: {service_address.value} has confidence: {service_address.confidence}" ) service_address_recipient = invoice.fields.get("ServiceAddressRecipient") if service_address_recipient: print( f"Service Address Recipient: {service_address_recipient.value} has confidence: {service_address_recipient.confidence}" ) remittance_address = invoice.fields.get("RemittanceAddress") if remittance_address: print( f"Remittance Address: {remittance_address.value} has confidence: {remittance_address.confidence}" ) remittance_address_recipient = invoice.fields.get("RemittanceAddressRecipient") if remittance_address_recipient: print( f"Remittance Address Recipient: {remittance_address_recipient.value} has confidence: {remittance_address_recipient.confidence}" ) 

from azure.core.credentials import AzureKeyCredential from azure.ai.formrecognizer import DocumentAnalysisClient endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] model_id = os.getenv("CUSTOM_BUILT_MODEL_ID", custom_model_id) document_analysis_client = DocumentAnalysisClient( endpoint=endpoint, credential=AzureKeyCredential(key) ) # Make sure your document's type is included in the list of document types the custom model can analyze with open(path_to_sample_documents, "rb") as f: poller = document_analysis_client.begin_analyze_document( model_id=model_id, document=f ) result = poller.result() for idx, document in enumerate(result.documents): print(f"--------Analyzing document #{idx + 1}--------") print(f"Document has type {document.doc_type}") print(f"Document has document type confidence {document.confidence}") print(f"Document was analyzed with model with ID {result.model_id}") for name, field in document.fields.items(): field_value = field.value if field.value else field.content print( f"......found field of type '{field.value_type}' with value '{field_value}' and with confidence {field.confidence}" ) # iterate over tables, lines, and selection marks on each page for page in result.pages: print(f"\nLines found on page {page.page_number}") for line in page.lines: print(f"...Line '{line.content}'") for word in page.words: print(f"...Word '{word.content}' has a confidence of {word.confidence}") if page.selection_marks: print(f"\nSelection marks found on page {page.page_number}") for selection_mark in page.selection_marks: print( f"...Selection mark is '{selection_mark.state}' and has a confidence of {selection_mark.confidence}" ) for i, table in enumerate(result.tables): print(f"\nTable {i + 1} can be found on page:") for region in table.bounding_regions: print(f"...{region.page_number}") for cell in table.cells: print( f"...Cell[{cell.row_index}][{cell.column_index}] has text '{cell.content}'" ) print("-----------------------------------") 

Analyze field text and semantic values from a given document. The input must be the location (URL) of the document to be analyzed.

• model_id (str) – A unique model identifier can be passed in as a string. Use this to specify the custom model ID or prebuilt model ID. Prebuilt model IDs supported can be found here: https://aka.ms/azsdk/formrecognizer/models

• document_url (str) – The URL of the document to analyze. The input must be a valid, properly encoded (i.e. encode special characters, such as empty spaces), and publicly accessible URL. For service supported file types, see: https://aka.ms/azsdk/formrecognizer/supportedfiles.

• pages (str) – Custom page numbers for multi-page documents(PDF/TIFF). Input the page numbers and/or ranges of pages you want to get in the result. For a range of pages, use a hyphen, like pages=”1-3, 5-6”. Separate each page number or range with a comma.

• locale (str) – Locale hint of the input document. See supported locales here: https://aka.ms/azsdk/formrecognizer/supportedlocales.

• features (list[str]) – Document analysis features to enable.

An instance of an LROPoller. Call result() on the poller object to return a AnalyzeResult.

LROPoller[AnalyzeResult]

HttpResponseError –

New in version 2023-07-31: The features keyword argument.

Example:

from azure.core.credentials import AzureKeyCredential from azure.ai.formrecognizer import DocumentAnalysisClient endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] document_analysis_client = DocumentAnalysisClient( endpoint=endpoint, credential=AzureKeyCredential(key) ) url = "https://raw.githubusercontent.com/Azure/azure-sdk-for-python/main/sdk/formrecognizer/azure-ai-formrecognizer/tests/sample_forms/receipt/contoso-receipt.png" poller = document_analysis_client.begin_analyze_document_from_url( "prebuilt-receipt", document_url=url ) receipts = poller.result() for idx, receipt in enumerate(receipts.documents): print(f"--------Analysis of receipt #{idx + 1}--------") print(f"Receipt type: {receipt.doc_type if receipt.doc_type else 'N/A'}") merchant_name = receipt.fields.get("MerchantName") if merchant_name: print( f"Merchant Name: {merchant_name.value} has confidence: " f"{merchant_name.confidence}" ) transaction_date = receipt.fields.get("TransactionDate") if transaction_date: print( f"Transaction Date: {transaction_date.value} has confidence: " f"{transaction_date.confidence}" ) if receipt.fields.get("Items"): print("Receipt items:") for idx, item in enumerate(receipt.fields.get("Items").value): print(f"...Item #{idx + 1}") item_description = item.value.get("Description") if item_description: print( f"......Item Description: {item_description.value} has confidence: " f"{item_description.confidence}" ) item_quantity = item.value.get("Quantity") if item_quantity: print( f"......Item Quantity: {item_quantity.value} has confidence: " f"{item_quantity.confidence}" ) item_price = item.value.get("Price") if item_price: print( f"......Individual Item Price: {item_price.value} has confidence: " f"{item_price.confidence}" ) item_total_price = item.value.get("TotalPrice") if item_total_price: print( f"......Total Item Price: {item_total_price.value} has confidence: " f"{item_total_price.confidence}" ) subtotal = receipt.fields.get("Subtotal") if subtotal: print(f"Subtotal: {subtotal.value} has confidence: {subtotal.confidence}") tax = receipt.fields.get("TotalTax") if tax: print(f"Total tax: {tax.value} has confidence: {tax.confidence}") tip = receipt.fields.get("Tip") if tip: print(f"Tip: {tip.value} has confidence: {tip.confidence}") total = receipt.fields.get("Total") if total: print(f"Total: {total.value} has confidence: {total.confidence}") print("--------------------------------------") 

Classify a document using a document classifier. For more information on how to build a custom classifier model, see https://aka.ms/azsdk/formrecognizer/buildclassifiermodel.

An instance of an LROPoller. Call result() on the poller object to return a AnalyzeResult.

LROPoller[AnalyzeResult]

HttpResponseError –

New in version 2023-07-31: The begin_classify_document client method.

Example:

from azure.core.credentials import AzureKeyCredential from azure.ai.formrecognizer import DocumentAnalysisClient endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] classifier_id = os.getenv("CLASSIFIER_ID", classifier_id) document_analysis_client = DocumentAnalysisClient( endpoint=endpoint, credential=AzureKeyCredential(key) ) with open(path_to_sample_documents, "rb") as f: poller = document_analysis_client.begin_classify_document( classifier_id, document=f ) result = poller.result() print("----Classified documents----") for doc in result.documents: print( f"Found document of type '{doc.doc_type or 'N/A'}' with a confidence of {doc.confidence} contained on " f"the following pages: {[region.page_number for region in doc.bounding_regions]}" ) 

Classify a given document with a document classifier. For more information on how to build a custom classifier model, see https://aka.ms/azsdk/formrecognizer/buildclassifiermodel. The input must be the location (URL) of the document to be classified.

• classifier_id (str) – A unique document classifier identifier can be passed in as a string.

• document_url (str) – The URL of the document to classify. The input must be a valid, properly encoded (i.e. encode special characters, such as empty spaces), and publicly accessible URL of one of the supported formats: https://aka.ms/azsdk/formrecognizer/supportedfiles.

An instance of an LROPoller. Call result() on the poller object to return a AnalyzeResult.

LROPoller[AnalyzeResult]

HttpResponseError –

New in version 2023-07-31: The begin_classify_document_from_url client method.

Example:

from azure.core.credentials import AzureKeyCredential from azure.ai.formrecognizer import DocumentAnalysisClient endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] classifier_id = os.getenv("CLASSIFIER_ID", classifier_id) document_analysis_client = DocumentAnalysisClient( endpoint=endpoint, credential=AzureKeyCredential(key) ) url = "https://raw.githubusercontent.com/Azure/azure-sdk-for-python/main/sdk/formrecognizer/azure-ai-formrecognizer/tests/sample_forms/forms/IRS-1040.pdf" poller = document_analysis_client.begin_classify_document_from_url( classifier_id, document_url=url ) result = poller.result() print("----Classified documents----") for doc in result.documents: print( f"Found document of type '{doc.doc_type or 'N/A'}' with a confidence of {doc.confidence} contained on " f"the following pages: {[region.page_number for region in doc.bounding_regions]}" ) 

Close the DocumentAnalysisClient session.

Runs a network request using the client’s existing pipeline.

The request URL can be relative to the base URL. The service API version used for the request is the same as the client’s unless otherwise specified. Overriding the client’s configured API version in relative URL is supported on client with API version 2022-08-31 and later. Overriding in absolute URL supported on client with any API version. This method does not raise if the response is an error; to raise an exception, call raise_for_status() on the returned response object. For more information about how to send custom requests with this method, see https://aka.ms/azsdk/dpcodegen/python/send_request.

request (HttpRequest) – The network request you want to make.

stream (bool) – Whether the response payload will be streamed. Defaults to False.

The response of your network call. Does not do error handling on your response.

HttpResponse

DocumentAnalysisError contains the details of the error returned by the service.

Converts a dict in the shape of a DocumentAnalysisError to the model itself.

data (dict) – A dictionary in the shape of DocumentAnalysisError.

DocumentAnalysisError

DocumentAnalysisError

Returns a dict representation of DocumentAnalysisError.

dict

dict

Error code.

List of detailed errors.

Detailed error.

Error message.

Target of the error.

Inner error details for the DocumentAnalysisError.

Converts a dict in the shape of a DocumentAnalysisInnerError to the model itself.

data (dict) – A dictionary in the shape of DocumentAnalysisInnerError.

DocumentAnalysisInnerError

DocumentAnalysisInnerError

Returns a dict representation of DocumentAnalysisInnerError.

dict

dict

Error code.

Detailed error.

Error message.

A barcode object.

Converts a dict in the shape of a DocumentBarcode to the model itself.

data (dict) – A dictionary in the shape of DocumentBarcode.

DocumentBarcode

DocumentBarcode

Returns a dict representation of DocumentBarcode.

Dict[str, Any]

Dict[str, Any]

Confidence of correctly extracting the barcode.

Barcode kind. Known values are “QRCode”, “PDF417”, “UPCA”, “UPCE”, “Code39”, “Code128”, “EAN8”, “EAN13”, “DataBar”, “Code93”, “Codabar”, “DataBarExpanded”, “ITF”, “MicroQRCode”, “Aztec”, “DataMatrix”, “MaxiCode”.

Bounding polygon of the barcode.

Location of the barcode in the reading order concatenated content.

Barcode value.

Document classifier information. Includes the doc types that the model can classify.

Converts a dict in the shape of a DocumentClassifierDetails to the model itself.

data (dict) – A dictionary in the shape of DocumentClassifierDetails.

DocumentClassifierDetails

DocumentClassifierDetails

Returns a dict representation of DocumentClassifierDetails.

Dict[str, Any]

Dict[str, Any]

API version used to create this document classifier.

Unique document classifier name.

Date and time (UTC) when the document classifier was created.

Document classifier description.

List of document types to classify against.

Date and time (UTC) when the document classifier will expire.

An object representing the content and location of a document field value.

New in version 2023-07-31: The boolean value_type and bool value

Converts a dict in the shape of a DocumentField to the model itself.

data (dict) – A dictionary in the shape of DocumentField.

DocumentField

DocumentField

Returns a dict representation of DocumentField.

dict

dict

Bounding regions covering the field.

The confidence of correctly extracting the field.

The field’s content.

Location of the field in the reading order concatenated content.

The value for the recognized field. Its semantic data type is described by value_type. If the value is extracted from the document, but cannot be normalized to its type, then access the content property for a textual representation of the value.

The type of value found on DocumentField. Possible types include: “string”, “date”, “time”, “phoneNumber”, “float”, “integer”, “selectionMark”, “countryRegion”, “signature”, “currency”, “address”, “boolean”, “list”, “dictionary”.

A formula object.

Converts a dict in the shape of a DocumentFormula to the model itself.

data (dict) – A dictionary in the shape of DocumentFormula.

DocumentFormula

DocumentFormula

Returns a dict representation of DocumentFormula.

Dict[str, Any]

Dict[str, Any]