Using the parser¶
Requires Python 3.11+. pip install nameparser
Parse a name¶
>>> from nameparser import parse
>>> name = parse("Dr. Juan Q. Xavier de la Vega III")
>>> name.given, name.family
('Juan', 'de la Vega')
>>> name.title, name.middle, name.suffix
('Dr.', 'Q. Xavier', 'III')
A parsed name has seven fields: title, given, middle,
family, suffix, nickname, and maiden. Parsing never
raises; unparseable input yields a ParsedName with
empty fields plus any ambiguities the parser noticed along the way
(see When the parser had to guess below, and How the parser works for why
they exist). A name with no fields set is falsy, which is how you tell
“nothing parsed” from “parsed to something”:
>>> bool(parse("")), bool(parse(" ")), bool(parse("John"))
(False, False, True)
Input shapes¶
Three arrangements are understood, and every piece of each is optional:
Title Given "Nickname" Middle Middle Family SuffixFamily [Suffix], Title Given (Nickname) Middle Middle[,] Suffix [, Suffix]Title Given Middle Family [Suffix], Suffix [, Suffix]
The last two differ in what the comma is doing. In form 2 it separates the family name from the rest, so the family name comes first; in form 3 it only sets off suffixes, and the name before it is still given-then-family:
>>> parse("de la Vega, Juan Q. Xavier III").family # form 2
'de la Vega'
>>> parse("Doe Jr., John").suffix # form 2, suffix before the comma
'Jr.'
>>> parse("John Doe, Jr.").family # form 3
'Doe'
Two more arrangements apply only when name_order declares
family-first input — common outside Europe; see Customizing the parser:
Title Family Given Middle Middle [Particle] [, Suffix](FAMILY_FIRST)Title Family Middle Middle Given [, Suffix](FAMILY_FIRST_GIVEN_LAST)
A trailing particle earns a slot in form 4 alone because it is displaced from the family name it belongs to; form 5’s trailing word is the given name by the caller’s declaration, so there is nothing there to reinterpret.
Two more arrangements are native East Asian forms and need no
name_order at all — the script itself carries the reading:
Family Given [Honorific]Given[·Given]·Family / katakana transcription (source order)
Form 6 is the native family-first arrangement written in Han or
Hangul — spaced or unspaced, with the honorific spaced or glued and
landing in suffix. It has no title slot and no comma, because
native CJK writing has neither convention. Form 7 is a transcription
listing — Han divided by the 间隔号, or katakana joined by the
nakaguro — kept in the order it was written and never segmented.
A comma or a Latin wrapper around a CJK name — a listing comma, a Latin honorific or credential set beside it — is tolerated input: parsed best-effort, its handling changeable without notice.
Forms 6 and 7, and how a Latin wrapper around either is handled, are covered in full under East Asian names below.
Words that attach to their neighbors¶
Input shapes tell you where the fields sit. This tells you which words merge into one field instead of standing alone — between them, that is most of what decides a parse.
Most words stand alone. A few pull in a neighbor, and each kind pulls into one particular field — so this table is also a map of which fields get built by attachment rather than by position. Titles and suffixes attach only to adjacent words of their own kind (a run of titles chains into one, but a title never swallows a plain name); the rest reach forward to pull in the next word, whatever it is. Follow a row’s name to its full vocabulary set:
Words |
Attach to |
Field |
Example |
|---|---|---|---|
adjacent titles |
|
|
|
adjacent suffixes |
|
|
|
the following word |
|
|
|
the following surname |
|
|
|
the following name |
|
|
|
the words on both sides |
any |
|
Conjunctions are the exception the last row names: they take the field
of whatever sits on both sides, so the same and pulls two given
names together as easily as two surnames:
>>> parse("John and Jane Smith").given
'John and Jane'
>>> parse("Juan de la Vega y Rodriguez").family
'de la Vega y Rodriguez'
Position matters in exactly one place: a particle standing on its own
at the start of a name. It has no surname to attach to yet, so what
decides the reading is whether it is one that can double as a given
name: the particle either becomes the given name or turns the whole
name into a surname. Only the first of those is name_order’s
question — see Customizing the parser, and read the given name below as the
default given-first order’s — since a particle that can never be a
given name is the surname whatever order you declare:
>>> parse("van Gogh").given # 'van' can be a given name
'van'
>>> parse("de Mesnil").given # 'de' cannot
''
>>> parse("de Mesnil").family
'de Mesnil'
A comma gets there first. It names the surname outright, so a particle opening that surname has nothing left to decide and the part after the comma is the given name:
>>> parse("de Mesnil, Juan").given
'Juan'
Customizing the parser covers how to change which words are in each of these
sets, including which particles may double as given names. One shipped
vocabulary works the other way round and so is not in the table above:
surnames splits a word instead of
merging two, and is covered next.
East Asian names¶
A Chinese, Japanese, or Korean name written in its own script puts the family name first: 毛泽东 is MAO Zedong, 山田太郎 is YAMADA Taro, 김민준 is KIM Minjun. The family name is short — one Han character or one hangul syllable, occasionally two — and comes from a small closed set, while given names are open-ended. And in native writing the parts are usually not separated at all: the whole name is one unbroken run of characters. A parser therefore has two distinct jobs here: assign family and given to the right fields, and, when the name arrives as a single token, find the boundary inside it.
Field assignment is automatic. A name written wholly in Han characters or hangul is assigned family-first, because every language written in those scripts orders names that way — Chinese and Japanese share little else, but they agree on this — so the assignment requires no knowledge of which language the name is in:
>>> parse("毛 泽东").family
'毛'
>>> parse("山田 太郎").family
'山田'
Splitting an unspaced name is also automatic, but only for Korean. Hangul is written by exactly one language, and Korean family names are limited to a small closed set: the census surname list is part of the default vocabulary, and the longest listed surname at the start of an unspaced hangul token becomes the family name:
>>> minjun = parse("김민준")
>>> minjun.family, minjun.given
('김', '민준')
The same split is not automatic for Han text, because there the script
does not identify the language: 高橋一郎 is a Japanese name whose
family name is 高橋, but 高 alone is a common Chinese surname, so a
Chinese surname list would split it in the wrong place. Declaring the
language is up to you. When you know the data is Chinese, apply the
zh locale pack, which carries the surname list the split needs:
>>> from nameparser import locales, parser_for
>>> parser_for(locales.ZH).parse("毛泽东").family
'毛'
Chinese also has a transcription convention, and it is written in the
punctuation: a foreign name transcribed into Han characters keeps its
source order and divides its parts with the 间隔号, the interpunct
· (U+00B7) — 威廉·莎士比亚 is William Shakespeare, given name
first. The dot itself is the marker, so nameparser reads U+00B7 as a
token separator when it sits between classified-script characters
(each side judged on its own — a hangul character beside a Han one
qualifies), and a dot anywhere in the name reads the whole name as a
transcription listing: it keeps the order it was written in and is
never segmented — the role pure katakana plays for Japanese
transcriptions, played here by the divider instead of the script.
Because only classified characters on both sides make it a divider,
the same codepoint interior to a Latin-script name — the Catalan punt
volat in Gal·la — is untouched, and a dot with a classified
character on just one side (王·Smith) stays part of the word
undivided. The Japanese middle dot ・ (covered next) is a different
mark carrying a different convention, and keeps its own reading.
Japanese¶
Japanese writes a name in three scripts at once. Family names and most given names are kanji — the same characters Chinese uses — but a given name is often written in one of the two kana syllabaries instead: hiragana (高橋みなみ) or katakana (山田エミ). The two syllabaries carry different information about whose name it is. Hiragana never transcribes a foreign name, so a name that mixes kanji and kana is a Japanese person’s name, written in Japanese order. Katakana is ambiguous: native given names use it, but katakana is also how Japanese text writes a foreign name — マイケル・ジャクソン is Michael Jackson — and a transcription keeps the source language’s order, given name first, its parts divided by the middle dot ・ (the nakaguro, U+30FB) rather than by a space.
Two behaviors follow from that without any configuration. A name whose characters stay within kanji and kana and carry at least one kana is assigned family-first, like any other native-script East Asian name: it cannot be Chinese, and it is not a transcription, because a transcription would have been kana alone.
>>> minami = parse("高橋 みなみ")
>>> minami.family, minami.given
('高橋', 'みなみ')
>>> parse("山田 エミ").family
'山田'
And the middle dot separates tokens the way a space does, so a transcribed foreign name divides into its parts — which, being wholly katakana, keep the order they were written in:
>>> michael = parse("マイケル・ジャクソン")
>>> michael.given, michael.family
('マイケル', 'ジャクソン')
Dividing an unspaced Japanese name is a separate matter, and one no
surname list can settle: family and given names draw on the same
kanji, both sides run one to four characters, and the reading rather
than the spelling decides most divisions. nameparser therefore takes a
segmenter — a callable from token text to a division — and ships a
factory wrapping namedivider-python, an optional
dependency installed with the ja extra:
$ pip install "nameparser[ja]"
from nameparser import locales, parser_for
parser = parser_for(locales.JA, segmenter=locales.ja_segmenter())
parser.parse("山田太郎").family # '山田'
Both halves are required, and they do different jobs: the ja pack
activates division for Japanese text, and the segmenter performs it.
ja_segmenter() wraps namedivider’s BasicNameDivider, which
reads data bundled in the installed package;
ja_segmenter(gbdt=True) selects its gradient-boosted divider
instead, which is more accurate and downloads its model and surname
files from the network on first use, worth knowing before deploying it
somewhere sandboxed or air-gapped.
Forgetting the segmenter is loud: building the parser emits a
UserWarning naming the scripts that could never divide and the
call to pass, because the misconfigured parser would otherwise behave
exactly like a working one minus the feature. The same check guards
any configuration whose activated scripts nothing can serve. A
from-scratch lexicon with no hangul surnames warns under the default
policy, and Policy(segment_scripts=frozenset()) is the deactivation the
message offers.
Decomposed text¶
Korean and Japanese text is sometimes stored decomposed, with a
syllable held as its separate jamo rather than as one codepoint. macOS
filenames are the common source. Everything above works on decomposed
input: script classification normalizes to NFC before deciding, so a
decomposed name gets the same order rule as its composed twin.
Vocabulary lookup does the same before matching a word against
titles, honorifics and the rest, so a decomposed Señor or née
— macOS-origin data again — is recognized as readily as its composed
spelling.
Splitting is the exception. An unspaced decomposed hangul name is ordered correctly but not split, because surname matching runs against the text as given and a decomposed name matches no entry in the census list. That is the deliberate choice: being unsplit is recoverable, whereas splitting in the wrong place is not.
One consequence is worth stating outright, because it looks like a bug. Parse output preserves the encoding it was given, so a field from a decomposed name is decomposed too, and comparing it against a composed literal fails even where the parse was correct:
decomposed = unicodedata.normalize("NFD", "김 민준")
parse(decomposed).family == "김" # False
unicodedata.normalize("NFC", parse(decomposed).family) # '김'
Normalize both sides before comparing across encodings.
Boundaries¶
Several boundaries apply to all of the above.
When the script rules don’t apply¶
Romanized names (“Kim Min-jun”, “Yamada Taro”) are Latin script and follow the ordinary positional rules. Order genuinely varies in romanized data, so nothing script-based applies. A name written wholly in katakana stays positional for the reason given above, pack or no pack: it is predominantly a transcription, and a transcription is already in the order it should be read in.
A Han transcription written with a space instead of the 间隔号 (威廉 莎士比亚) carries nothing to distinguish it from a native two-token name, and keeps the family-first reading. The dot is the marker, and without it there is no signal. The same holds for a transcription typed with the Japanese middle dot (威廉・莎士比亚): each dot carries its own script’s convention, the nakaguro’s is Japanese roster formatting rather than transcription, so only the Chinese dot rescues the source order.
Honorifics come off first¶
Honorifics and degrees follow a CJK name, and both the spaced and the glued forms are recognized as suffixes:
>>> parse("王小明 先生").suffix
'先生'
>>> glued = parse("김민준씨")
>>> glued.family, glued.given, glued.suffix
('김', '민준', '씨')
The honorific is split off the end of the last token of the name
before the name is split or ordered, so those rules see the name
without it. That is why 김민준씨 still divides into family 김 and
given 민준, and why a configured Japanese segmenter is handed 山田太郎
rather than 山田太郎様.
The stop can be any width: the fullwidth . a Japanese or
Chinese input method produces by default, the ideographic 。 and
the halfwidth 。 all reach the honorific vocabulary as an ASCII
period does, so 김민준 씨. gives suffix 씨., family 김, given
민준. A period glued to an ordinary name word, not an honorific, is
likewise left where it was written rather than breaking the
segmentation that follows it:
>>> parse("양. 지훈").family, parse("양. 지훈").given
('양.', '지훈')
Commas and Latin wrappers around a CJK name¶
A comma or a Latin credential set wrapped around a CJK name is
tolerated input rather than contract: no native CJK writing uses
either convention, so nameparser reads it best-effort and the
handling can change without notice. Today a comma still names the
family and stops the split — 남궁민수, 지훈 reads family
남궁민수 whole, where the bare 남궁민수 alone would split into
family 남궁 and given 민수 — and a glued honorific still peels
off before the comma when what follows it is nothing but suffix
words, as in 田中さん, PhD (suffix さん, PhD), but stays glued
when the comma is followed by a title or another name word, as in
田中さん, Dr. (family 田中さん). Credentials after the comma are
read the same best-effort way, landing in given or suffix by
spelling: 田中さん, V. and 田中さん, Ph. D. give up さん exactly
as 田中さん, PhD does.
Spacing, and where the name divides¶
Where a segmenter divides the name, the two spellings part company. A
spaced honorific is a token boundary the writer typed, and the
segmenter is asked only where an undivided name divides, so anything
standing beside the name calls it off, honorific or not. Under the
Japanese pack 佐藤 氏 keeps family 佐藤, where bare 佐藤 would
have been divided 佐 + 藤.
That is a conservative reading rather than a principled one. A spaced
honorific cannot be told apart from a spaced given name by position,
and treating it as one keeps four real surnames whole (佐藤 氏,
田中 様, 鈴木 先生, 中村 教授) at the price of one division
it declines to make (山田太郎 様). A glued honorific carries no
boundary at all, its writer having drawn none anywhere, so 田中さん
divides the way bare 田中 does, into family 田 and given 中, with
さん in suffix. Writing the honorific spaced is therefore also how
you ask for a family name to be kept whole on this path, short of
declining the pack.
Where the VOCABULARY divides the name the two spellings never part company, because the peel hands the same remainder to the same surname match either way:
>>> parse("김민준 씨").family, parse("김민준씨").family
('김', '김')
Under the Chinese pack 王小明 先生 and 王小明先生 both give
family 王, given 小明 and suffix 先生 for the same reason. Spacing the
honorific is no lever there, and for Korean data there is no pack to
decline either, hangul segmentation being on by default.
Which honorifics peel when glued¶
The glued reading is deliberately narrower than the spaced one. A spaced honorific sits behind a boundary its writer drew; a glued one has only itself to go on, so a word peels off the end of a name only if it could never BE the end of a name.
씨, 님, 박사, 박사님, 선생님, 교수님, さん, さま, くん, ちゃん, 様, 先生, 教授, 女士 and 小姐 qualify. 양, 군, 氏, 博士 and 殿 do not, because 김지양 is a given name, 田中博士 is Tanaka Hiroshi as readily as Doctor Tanaka, and some ninety Japanese surnames end in 殿 (鵜殿, 真殿). Those stay recognized in their spaced form, where position settles what the glued form leaves ambiguous. 君 is recognized in neither form, since 王君 is a complete Chinese name, though its kana spelling くん peels.
Exactly one honorific peels off a token, and the entries are whole
honorifics rather than parts: 김민준박사님 gives up 박사님 entire,
not 님 with 박사 left behind.
When a division was a judgment call¶
A division the parser had to choose is reported rather than hidden.
When an unspaced name has more than one vocabulary-supported split,
the longest surname wins and the parse records the decision as an
AmbiguityKind.SEGMENTATION, described under When the parser had
to guess. 남궁민수 is 남궁 + 민수 by the two-syllable surname but
남 + 궁민수 by the single-syllable one:
>>> parse("남궁민수").ambiguities
(Ambiguity('segmentation': '남궁'/'민수'),)
A name with only one possible split reports nothing.
A segmenter’s answer is reported on the same kind whenever its
confidence falls below the stage’s floor, naming the division and the
score in the report’s detail:
"'山田太郎' splits as '山田' + '太郎' on a segmenter answer scoring 0.44, under the 0.9 confidence floor"
With namedivider that line separates its two kinds of answer. A division it states as a rule, such as the kanji-to-kana boundary in 高橋みなみ, scores 1.0 and reports nothing; a division read off kanji statistics scores far below the floor and always reports. Read the report as a statement about the kind of answer, not as a measure of how likely this particular one is to be wrong.
A lone two-character kanji name divides one character to each side, on namedivider’s rule for that length. A name that short carries no evidence of where its own boundary falls, and one character each way is the presumption Japanese practice makes. That is an accepted presumption rather than a measurement, so a two-character token is the shape to check first if a division looks wrong.
When a segmenter misbehaves¶
A segmenter that answers outside the token it was given, with a cut at
or past the end of the text, has violated the protocol, and the parse
says so rather than hiding it. It raises ValueError naming the
offending offset and the token’s length, the way an answer of the
wrong type raises TypeError. Declining silently would leave an
off-by-one segmenter invisible: every answer it gave would vanish and
the name would merely look undivided.
The shipped ja_segmenter() does decline, returning None and
leaving the token whole, for the cases that are not protocol
violations: text outside the Japanese repertoire, text too short to
divide, an answer that fails to reconstruct its input, and a score
outside [0, 1].
Exceptions are the one thing that does not stay inside the parse: a segmenter is your code, so its errors propagate rather than being absorbed as content errors.
The command line takes the pack but not the segmenter: python -m
nameparser --locale ja has no way to attach one, so it activates
nothing by itself. Customizing the parser covers turning any of these
behaviors off.
Aggregate views¶
>>> name.given_names # given + middle
'Juan Q. Xavier'
>>> name.family_base, name.family_particles # family, split apart
('Vega', 'de la')
surnames (middle + family) is the mirror-image aggregate.
The plural is the tell: given and family are single fields,
while given_names and surnames roll several fields together —
the same sense in which a passport form asks for your “given names” as
one blank that can hold more than one word.
family_base is the one to sort on. Dutch and Belgian directories
file a name under the base surname and ignore the tussenvoegsel — the
van, de or van der in front of it — and the same convention
applies wherever particles are common:
>>> names = [parse(s) for s in
... ["Vincent van Gogh", "Juan de la Vega", "John Smith"]]
>>> [n.family_base for n in sorted(names, key=lambda n: n.family_base.lower())]
['Gogh', 'Smith', 'Vega']
Sorting on family instead files those under “d”, “S” and “v”, which
is the problem the split exists to solve:
>>> [n.family for n in sorted(names, key=lambda n: n.family.lower())]
['de la Vega', 'Smith', 'van Gogh']
Dicts and strings¶
>>> name.as_dict(include_empty=False)
{'title': 'Dr.', 'given': 'Juan', 'middle': 'Q. Xavier', 'family': 'de la Vega', 'suffix': 'III'}
>>> str(name)
'Dr. Juan Q. Xavier de la Vega III'
>>> name.render("{family}, {given}")
'de la Vega, Juan'
>>> name.initials()
'J. Q. X. V.'
Fixing case¶
>>> str(parse("juan de la vega").capitalized())
'Juan de la Vega'
The no-argument form above uses the DEFAULT lexicon; for a name parsed
with a custom Parser, call
Parser.capitalized() so the
parser’s own vocabulary decides the exceptions.
Nicknames and maiden names¶
>>> parse("Jonathan 'Jack' Kennedy").nickname
'Jack'
>>> parse("Jane Smith née Jones").maiden
'Jones'
Both fields appear in the default str() rendering — the nickname
quoted after the given name, the maiden name parenthesized after the
family name:
>>> str(parse("Jane (Janie) Smith née Jones"))
'Jane "Janie" Smith (Jones)'
That default is built for display, and the two fields differ in what survives it. The quoted nickname reparses as a nickname; the parenthesized maiden name reparses as a nickname too, so a parse-render-reparse round trip silently loses it:
>>> parse('Jane "Janie" Smith (Jones)').maiden
''
>>> parse('Jane "Janie" Smith (Jones)').nickname
'Janie Jones'
If the rendered string has to survive a reparse — storing names as text and reading them back, for instance — render the marker explicitly instead of relying on the default:
>>> name = parse("Jane Smith née Jones")
>>> text = name.render("{given} {family} née {maiden}")
>>> text
'Jane Smith née Jones'
>>> parse(text).maiden
'Jones'
Delimited content is not always a nickname. If it opens with a marker word and has a word after it, the clause is a maiden name, whatever pair encloses it and with nothing configured — the clause has said which convention it means, so you do not have to:
>>> parse("Jane Smith (née Jones)").maiden
'Jones'
>>> parse('Jane Smith "née Jones"').maiden
'Jones'
>>> parse("Jane (née Jones) Smith").family
'Smith'
A marker with no name after it is just a word in brackets, and a clause
with no marker at all stays a nickname — the parenthesized birth surname
is a real convention, but nothing in the clause says so, and only you
can declare that with maiden_delimiters (see Customizing the parser):
>>> parse("Jane Smith (née)").nickname
'née'
>>> parse("Cherice J. (Johnson) Williams").nickname
'Johnson'
If what’s inside is a known suffix, or simply ends in a period, it is read as a suffix instead — that reading is taken before the maiden one, and parenthesized credentials and retired ranks are far more common than parenthesized nicknames that happen to be credentials:
>>> parse("Andrew Perkins (MBA)").suffix
'MBA'
>>> parse("Andrew Perkins (Ret.)").suffix
'Ret.'
The exception to that exception is an ambiguous acronym — one that is also a plausible name or set of initials. Standing alone inside delimiters, it keeps the nickname reading:
>>> parse("JEFFREY (JD) BRICKEN").nickname
'JD'
JD is in suffix_acronyms_ambiguous; see Customizing the parser for
what that field marks and how to add to it.
Titles you didn’t configure¶
A trailing period marks an abbreviation, and the parts of a name that get abbreviated are the ones standing outside it — titles and post-nominals. So a word ending in a period, in no vocabulary list at all, is read as a title when it stands where a title stands: at the front of the part that carries the given name. That is what lets unfamiliar ranks, honorifics and abbreviations work without configuring anything:
>>> parse("Insp. Jane Morse").title
'Insp.'
>>> parse("Det. Insp. Jane Morse").title # chains
'Det. Insp.'
Neither det nor insp is in the shipped vocabulary; the periods
are doing all the work.
The part that carries the given name is not always the front of the string. After a family comma it is the part after the comma, and the rule applies there in exactly the same way:
>>> parse("Morse, Det. Insp. Jane").title
'Det. Insp.'
The rule is bounded in four ways, so it doesn’t swallow ordinary
names. Single initials are left alone, so are abbreviations with
interior periods, it applies only to that leading run (the same
word after the given name is a middle name), and a period-marked
opening word carrying a Han, kana or hangul character is a name word
rather than a title, since those scripts write no abbreviation with a
period (田中. is the family name):
>>> parse("J. Smith").given
'J.'
>>> parse("E.T. Jones").given
'E.T.'
>>> parse("Jane Insp. Morse").middle
'Insp.'
Because this is structural rather than vocabulary-driven, emptying
titles does not switch it off; see Customizing the parser.
Only the leading slot INFERS. At the back of a name a period-marked word is read by vocabulary alone: a word the parser already knows as a post-nominal or as a title reads as one, and an unfamiliar abbreviation stays a name word.
>>> parse("John Smith Prof.").title
'Prof.'
>>> parse("John Smith Xyz.").family
'Xyz.'
That asymmetry is deliberate. The title vocabulary holds hundreds of
words that are ordinary surnames — king, judge, bishop —
so inferring a trailing title from the shape alone would cost real
names their family field. The period is what separates the two: a
trailing title word written without one is a name word, so
parse("Mary Jane King").family is 'King'.
Comparing names¶
== is strict value equality — two ParsedName
instances are equal only if every field matches exactly. For “is this
the same name, allowing for order and case?” use matches() or
comparison_key() instead. matches() parses a str argument with
the DEFAULT parser; to compare against a string using a custom
Parser’s vocabulary, call
Parser.matches().
>>> parse("de la Vega, Juan").matches("Juan de la Vega")
True
>>> parse("JUAN DE LA VEGA").comparison_key() == parse("Juan de la Vega").comparison_key()
True
When the parser had to guess¶
Some names have no single correct reading. A leading Van could be
a given name — it really is for the actor Van Johnson — or the start
of a family name, as it is for President Van Buren. Both are the same
shape, so no rule can tell them apart. 2.0 takes the more likely
reading and records the choice on ambiguities rather than
deciding silently:
>>> name = parse("Van Buren")
>>> name.given, name.family
('Van', 'Buren')
>>> for a in name.ambiguities:
... print(a.kind.value, "-", a.detail)
particle-or-given - leading 'Van' may be a family-name particle; read as a given name
AmbiguityKind members are their own string values,
so branching on a kind needs no import:
>>> name.ambiguities[0].kind == "particle-or-given"
True
>>> [t.text for t in name.ambiguities[0].tokens]
['Van']
The post-nominals that double as ordinary surnames report the same way.
MA after a full name is read as a credential, but after a single
given name it stays the surname — either way the choice is recorded:
>>> parse("John Smith MA").suffix
'MA'
>>> [a.kind.value for a in parse("John Smith MA").ambiguities]
['suffix-or-name']
>>> parse("Jack MA").family
'MA'
A reading the vocabulary settles on its own is not a guess and reports
nothing — periods make M.A. unambiguously a credential:
>>> parse("John Smith M.A.").ambiguities
()
Most names report none. A non-empty ambiguities is a useful signal
for routing a record to human review instead of trusting it silently.
Tokens and spans¶
The seven fields are the convenient view. Underneath, each one is backed by tokens carrying their exact offsets into the original string, so you can always get back to the text a field came from:
>>> name = parse("Juan de la Vega")
>>> for tok in name.tokens:
... print(f"{tok.text!r:8} {tok.role.value:8} {tuple(tok.span)}")
'Juan' given (0, 4)
'de' family (5, 7)
'la' family (8, 10)
'Vega' family (11, 15)
>>> tok = name.tokens[1]
>>> name.original[tok.span.start:tok.span.end]
'de'
tokens_for() narrows that to a single role:
>>> from nameparser import Role
>>> [t.text for t in name.tokens_for(Role.FAMILY)]
['de', 'la', 'Vega']
A role’s string name works too: name.tokens_for("family").
Correcting a parse¶
ParsedName is immutable, so a correction is a new
value: replace() returns a copy with the given fields changed.
Untouched fields keep their tokens (and original is preserved),
with one deliberate exception: an ambiguity that pointed into a
replaced field is dropped — correcting the field that was flagged
clears the flag, while correcting an unrelated field keeps it.
>>> name = parse("Juan de la Vega")
>>> corrected = name.replace(title="Dr.")
>>> str(corrected)
'Dr. Juan de la Vega'
>>> name.title
''
>>> flagged = parse("Van Buren")
>>> flagged.replace(given="Martin").ambiguities
()
>>> [a.kind.value for a in flagged.replace(family="Harrison").ambiguities]
['particle-or-given']
replace() splits values on whitespace into plain, untagged
tokens — the vocabulary knowledge a parse would have about the new
text is not there. The views that read those tags degrade: the parser
no longer knows de la are particles, so family_particles
empties and family_base takes the whole field.
A token the parse never saw carries no decision to honor, so a view
that is handed a vocabulary can fall back to it —
capitalized() is the one that is, and it
falls back for one question only: whether a word is a conjunction or
an initial, which a word answers on its own. Whether a particle is
acting as a particle is a fact about the whole part, and there is no
reading on any word of a spliced field to derive it from, so a family
set to de la stays lowercase where the same words parsed are
repaired to De La. initials() takes
no vocabulary at all, so it falls back on neither question and every
word of a spliced field contributes an initial. family_particles
and family_base are properties on the parsed name, which holds no
vocabulary of its own either.
>>> name.family_particles
'de la'
>>> replaced = name.replace(family="de la Vega Smith")
>>> replaced.family_particles
''
>>> replaced.family_base
'de la Vega Smith'
>>> replaced.initials()
'J. d. l. V. S.'
>>> name.replace(family="de la").capitalized(force=True).family
'de la'
Parser.revise() is the same
operation with each value classified by the parser’s vocabulary, so
the correction behaves like a fresh parse of the corrected name
(which also means delimiters and marker words in the value are
consumed as they would be in a parse):
>>> from nameparser import Parser
>>> parser = Parser()
>>> revised = parser.revise(name, family="de la Vega Smith")
>>> revised.family_particles
'de la'
>>> revised.initials()
'J. V. S.'
revise() has two siblings on Parser:
Parser.matches() and
Parser.capitalized(). Those
two matter when you have built a custom parser — the
ParsedName methods of the same names fall back
to the default configuration for str or omitted arguments.
Command line¶
python -m nameparser parses one name and prints what it found. It
is the quickest way to see how a particular string comes out — worth
reaching for when a name parsed unexpectedly and you want to check a
variation of it, or when trying a locale pack before wiring one into
code:
$ python -m nameparser "dr. juan de la vega iii"
Parsed:
<ParsedName: [
title: 'dr.'
given: 'juan'
family: 'de la vega'
suffix: 'iii'
]>
Capitalized:
<ParsedName: [
title: 'Dr.'
given: 'Juan'
family: 'de la Vega'
suffix: 'III'
]>
Initials: j. v.
--json prints the fields as a single line instead, which is the
form to pipe somewhere:
$ python -m nameparser --json "Doe, John"
{"title": "", "given": "John", "middle": "", "family": "Doe", "suffix": "", "nickname": "", "maiden": ""}
Add --locale to parse with a locale pack (for example --locale
ru); see Locale packs.
Where next¶
How the parser works — how the parser works
Customizing the parser — your own vocabulary and behavior
Locale packs — locale packs
Migrating from HumanName — coming from 1.x
HumanName