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vocab-bloom-hub

Typed Python client for the public read-only API of a Vocab Bloom Hub instance — an English dictionary with IPA, CEFR levels, sense-level definitions, examples, translations (Russian, Spanish, French, German, Portuguese, Chinese, Arabic) and inflected forms, served under /api/v1.

Documentation, the API reference and a playground: vocab-bloom-hub.com.

  • Sync (VocabBloomClient) and async (AsyncVocabBloomClient) on httpx; one method per endpoint.
  • pydantic models generated from the server's OpenAPI document — the types cannot drift from the API.
  • Typed exceptions, cursor iteration, optional ETag cache, words_dataframe() for notebooks.
  • Python 3.10+; dependencies: httpx, pydantic (pandas optional).

Install

pip install vocab-bloom-hub
# with pandas support
pip install "vocab-bloom-hub[pandas]"

pip skips prereleases by default (1.1.0b1, PEP 440 for 1.1.0-beta.1); add --pre to try one.

Quick start

from vocab_bloom_hub import NotFoundError, VocabBloomClient

client = VocabBloomClient("https://dict.example.com")

# search: relevance tiers, typo tolerance
result = client.search("definately")
print(result.meta.fuzzy, result.data[0].word)  # True definitely

# a headword with every part of speech, forms, meanings and translations
try:
    run = client.word("run")
    print(run.data[0].meanings[0].definition)
except NotFoundError:
    print("no such word")

# walk the whole dictionary, page after page
for word in client.iter_words(word_level=["A1", "A2"], with_meanings=True):
    print(word.word, len(word.meanings))

# a notebook: the filtered list as a DataFrame (pip install "vocab-bloom-hub[pandas]")
frame = client.words_dataframe(part_of_speech=["noun"], category=["IT"])

Async, the same methods awaited:

from vocab_bloom_hub import AsyncVocabBloomClient

async with AsyncVocabBloomClient("https://dict.example.com") as client:
    meta = await client.meta()
    async for word in client.iter_words(limit=100):
        ...

Standalone command-line example

The SDK includes a runnable lookup example without adding an installed command. It requires Python 3.10+ and uses only the standard library and the SDK dependencies. Install the SDK, then run this from the Python SDK directory:

python -m pip install vocab-bloom-hub
python examples/lookup_word.py --base-url https://dict.example.com run

See the complete lookup example. Its output includes dataset license and attribution details and marks entries modified on the instance.

API

Method Endpoint Answer
search(search, *, type, limit) GET /search SearchResponse
search_detailed(search, *, ...) GET /search/detailed DetailedSearchResponse
word(headword) GET /words/{word} HeadwordResponse
words_batch(words) POST /words/batch WordsBatchResponse — up to 50 headwords, one rate-limit unit; misses under meta.not_found
word_by_id(id) GET /words/id/{id} WordResponse
meanings(headword) GET /words/{word}/meanings MeaningsResponse
translations(headword, *, language) GET /words/{word}/translations TranslationsResponse
forms(headword) GET /words/{word}/forms FormsResponse
synonyms(headword) GET /words/{word}/synonyms LinksResponse — the linked headwords per meaning
antonyms(headword) GET /words/{word}/antonyms LinksResponse
history(headword) GET /words/{word}/history HistoryResponse — what was changed on the instance, with the values before and after
word_datasets(headword) GET /words/{word}/datasets WordDatasetsResponse — the headword in every dataset of the instance, a group per dataset with its terms
dataset_history(headword, dataset) GET /words/{word}/datasets/{dataset}/history HistoryResponse — the edits of the headword in one dataset
words(**filters, cursor, limit, with_...) GET /words WordsResponse (one page)
iter_words(**filters, ...) GET /words, following the cursor Iterator[Word]
iter_search_detailed(search, *, ...) GET /search/detailed, page after page Iterator[Word] — stops at the server's page cap (DETAILED_SEARCH_MAX_PAGE, 20)
random(**filters) GET /random WordResponse
meta() GET /meta MetaResponse
openapi() GET /openapi.json dict — the OpenAPI document
suggest(headword, ...) POST /suggestions SuggestionCreatedResponse — files a reader report (or an edit proposal) into the instance's moderation queue
words_dataframe(**filters, ...) GET /words, every page pandas.DataFrame (sync and async clients)

Every response is the { data, meta } envelope the API answers with, as a pydantic model. Filters (part_of_speech, word_level, language_register, category, area_variant, form_of_word) take lists of strings or of the exported enums (PartOfSpeech, WordLevel, ...); values of one filter are OR-ed, different filters are AND-ed. The contract itself — tiers, filters, cursor pagination, caching — is documented in the server's docs/api.md.

Options

VocabBloomClient(
    "https://dict.example.com",  # origin of the instance; /api/v1 is appended
    headers={"X-App": "my-app"},  # sent with every request
    timeout=10.0,  # seconds, or an httpx.Timeout
    cache=True,  # ETag revalidation (below); or your own ResponseCache
    retry={
        "attempts": 3,
        "backoff": 0.5,
        "max_delay": 60.0,
    },  # opt-in: retry the GET reads on 429 / 5xx (below)
    transport=...,  # a custom httpx transport (tests, instrumentation)
)

Use the client as a context manager (with / async with) to close the connection pool.

Errors

Exception When Fields
NotFoundError 404 status, code (word_doesnt_found), body
RateLimitError 429 — the public rate limit retry_after (seconds, from Retry-After)
NetworkError no answer: DNS, connection, TLS, timeout status == 0, code == "network_error"
VocabBloomError everything else status, code, body

code is the machine-readable error of the API (invalid_cursor, too_many_requests, ...), or http_error when the answer was not JSON (a proxy page, for instance).

Without the retry option the client never retries on its own: a RateLimitError carries retry_after (seconds) and backoff is the caller's decision.

Per-request options

Every method takes options= — a RequestOptions dict with headers (merged over the client's for that call) and timeout (seconds or an httpx.Timeout, replacing the client's) — the counterpart of the Node client's last argument:

client.word("run", options={"headers": {"X-Request-Id": "abc"}, "timeout": 2.0})

Every request carries User-Agent: vocab-bloom-hub-python/<version> (vocab_bloom_hub.USER_AGENT) so an operator can tell SDK traffic apart in the log; pass your own User-Agent in headers to replace it.

Retry

Off by default — the client documents exact request counts against the rate limit, so the loop is opt-in. With retry={} (or explicit attempts / backoff) a GET answered 429 or 5xx is sent again: after Retry-After when the server sent it, otherwise after backoff, then twice that, and so on, up to attempts tries in total (the first one included; 3 and 0.5 s by default); no single wait exceeds max_delay seconds (60 by default), whatever Retry-After says. POST requests (the batch lookup, a suggestion), 4xx answers and network errors are never retried.

ETag cache

With cache=True every GET answer is kept in memory per URL together with its ETag; the next read of the same URL sends If-None-Match and, on 304 Not Modified, returns the kept body — the round trip stays, the payload does not. MemoryCache holds 500 entries (least recently used out); pass any object with get(url) / set(url, entry) for a store of your own. Off by default.

Development

cd packages/python-sdk
uv sync                                           # Python 3.12 + dependencies into .venv
uv run python scripts/generate_models.py          # models from apps/server/openapi/public-v1.json
uv run python scripts/generate_models.py --check  # fail when the generated models are stale (CI)
uv run ruff check . && uv run ruff format --check . && uv run mypy
uv run pytest                                     # unit tests + the client against the real server

src/vocab_bloom_hub/_generated/models.py is produced by datamodel-code-generator from the committed public spec and committed itself: a contract change on the server shows up as a diff here, and tests/test_contract.py fails until every operation of the spec has a client method. The live tests start the server through yarn workspace server fixture:public-api (Node.js and the monorepo's dependencies installed), on an in-memory SQLite database.

License

MIT for the client. The dictionary data comes under the license of the dataset the instance serves — CC BY 4.0 for the project's own, the license of the source for another, the one its owner chose for a dataset of the instance's own: read license, attribution and license_text from meta() and show them with the data (title names the dataset). An entry the owner of the instance changed carries modified: true, and client.history(headword) says what was changed: say next to such an entry that it was changed. word_datasets(headword) answers from every dataset of the instance: each group carries the terms of its own dataset, and entries taken from several groups are bound by each of them.

A word may have several origins, contributions and licenses. Each license's origin_id refers to its source or contribution snapshot: preserve the name, version, links, attribution and notices, and respect license_relation (all or any). For example, OpenGloss words marked as derived from WordNet retain both sets of terms. An unchanged fork keeps the original terms; actual edits add the fork's captured contribution terms. The primary license from meta() does not replace these word-specific licenses. These fields are optional when reading older v1 servers. See the API source fields.

What the licenses ask for: DATA_LICENSE.md.

Metadata

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