brightbean 1.0.0

Official Python SDK for the BrightBean API — YouTube packaging scoring.

brightbean — Python SDK

Official Python SDK for the BrightBean API. YouTube creator analytics: score titles and thumbnails for click-through-rate, analyze video hooks, benchmark channels and videos against their niche, and surface ranked content opportunities.

Install

pip install brightbean

Requires Python 3.10+.

Quickstart

from brightbean import BrightBean

with BrightBean(api_key="bb_...") as client:
    result = client.score(
        title="10 Tips to Boost Your Coding Productivity",
        thumbnail_url="https://i.ytimg.com/vi/abc123/maxresdefault.jpg",
    )
    print(f"score={result.score:.2f} percentile={result.percentile}")

Async

import asyncio
from brightbean import AsyncBrightBean

async def main():
    async with AsyncBrightBean(api_key="bb_...") as client:
        return await client.score(title="My epic video")

asyncio.run(main())

Every method documented below has the same signature on AsyncBrightBean; just await the call.

---

API reference

Response objects are typed dataclasses. Field names match the wire format (snake_case). Nullable fields are explicitly annotated … | None.

client.score(...) — packaging CTR

Score a YouTube packaging (title and/or thumbnail) for predicted click-through rate. The server auto-detects the mode from your inputs and charges credits accordingly.

result = client.score(
    title="10 Tips to Boost Your Coding Productivity",
    thumbnail_url="https://i.ytimg.com/vi/abc123/maxresdefault.jpg",
)
print(result.score, result.percentile, result.niche_label)

Parameters

Name	Type	Required	Default	Description
title	str | None	conditional*	None	Max 250 chars.
thumbnail_url	str | None	conditional*	None	Public URL. Max 1024 chars. Mutually exclusive with thumbnail_base64.
thumbnail_base64	str | None	conditional*	None	Base64-encoded image. Max 12.5 MB encoded. Mutually exclusive with thumbnail_url.
channel_url	str | None	no	None	Reserved — currently accepted but not consumed by the model.

* At least one of title, thumbnail_url, or thumbnail_base64 is required.

Returns PackagingScoreResponse

Field	Type	Description
score_id	UUID	Opaque identifier for this scoring call.
score	float (0–1)	Calibrated CTR percentile rank.
percentile	int (0–100)	round(score * 100).
raw_score	float | None	Continuous pre-calibration sigmoid output. Useful for fine-grained comparisons that the percentile-ranked score would round into the same plateau.
mode	"title" | "thumbnail" | "combined"	Server-detected scoring mode.
niche_slug	str	Canonical niche slug. Same taxonomy as /v1/research/* and /v1/benchmark/*.
niche_label	str	Human-readable niche name.
niche_confidence	float	Confidence (cosine similarity) of the niche assignment.

Cost: 1 credit for title-only, 2 credits for thumbnail-only, 3 credits for combined (the combined mode captures interaction effects the single-input modes miss).

---

client.video_hook(...) — hook quality of the first ~6 s

Score the first ~6 seconds of a YouTube video for hook quality. Returns a structured analysis with archetype classification, five dimension scores, and actionable strengths / weaknesses / suggestions.

result = client.video_hook(
    youtube_url="https://www.youtube.com/watch?v=dQw4w9WgXcQ",
)
print(result.primary_archetype, result.overall_score)
print(result.scores.clarity, result.scores.tension)

Parameters

Name	Type	Required	Default	Description
youtube_url	str	yes	—	Public YouTube URL, max 1024 chars. Accepts youtube.com/watch?v=…, youtu.be/…, youtube.com/shorts/…, youtube.com/embed/….

Returns VideoHookScoreResponse

Field	Type	Description
score_id	UUID	Opaque identifier for this scoring call.
primary_archetype	str	One of 13 archetypes (curiosity_gap, direct_question, bold_claim, in_medias_res, stakes_statement, promise, pattern_interrupt, authority, demonstration, empathy, negative_framing, cold_open, greetings).
secondary_archetype	str | None	Optional second archetype if the hook blends two.
scores	Scores (nested)	Five 0–10 dimension scores. See below.
overall_score	int (0–100)	Holistic hook-quality score.
transcript	str	First-6-seconds transcript. May be blank for music-only or visual-only openings.
visual_summary	str	Short description of the visual content.
strengths	list[str] (2–4 items)	What the hook does well.
weaknesses	list[str] (2–4 items)	What the hook does poorly.
suggestions	list[str] (2–4 items)	Concrete edits the creator could make.
delta_vs_niche_top	int	Difference between this hook's overall_score and the niche's top performers.
key_differences_vs_top	list[str] (1–3 items)	Specific ways this hook differs from niche-top hooks.

Nested scores:

Field	Type	Description
clarity	int (0–10)	How quickly the viewer understands the topic.
specificity	int (0–10)	How concrete the promise is.
tension	int (0–10)	Stakes / curiosity gap.
visual_energy	int (0–10)	Movement, cuts, visual contrast.
pace	int (0–10)	Words / cuts per second.

Cost: 10 credits per call.

---

client.benchmark_channel(...) — channel vs. niche

Benchmark a YouTube channel against its niche distribution. Fetches the channel's recent videos, classifies the niche, and percentile-ranks engagement and title patterns.

result = client.benchmark_channel(
    url="https://www.youtube.com/@MarquesBrownlee",
)
print(result.niche.slug, result.niche.match_strength)
print(result.channel.engagement_percentiles.overall)

Parameters

Name	Type	Required	Default	Description
url	str	yes	—	Channel URL or @handle, max 1024 chars. Accepts youtube.com/@handle, /channel/UC…, /c/<name>, /user/<legacy>.

Returns BenchmarkChannelResponse — two top-level objects, channel and niche.

channel

Field	Type	Description
channel_id	str	YouTube channel ID (UC…).
title	str	Channel display name.
subscriber_count	int	Public subscriber count at fetch time.
video_count	int	Total public videos.
engagement	object	Raw ratios. view_to_sub_ratio, like_to_view_ratio, comment_to_view_ratio — each float | None.
engagement_percentiles	object	The same three ratios plus overall, each ranked into int (0–100) | None against the niche distribution.
sample_window_days	int	Date span (in days) of the fetched sample, so callers can weight the signal against the channel's posting cadence.
title_patterns	object	Aggregate stats: mean_length_chars, mean_length_words, share_with_question_mark, share_with_number, median_uppercase_ratio, share_with_emoji. Each float | None (or int | None for the length fields).

niche

Field	Type	Description
slug	str	Canonical niche slug.
name	str	Human-readable niche name.
match_score	float	Cosine similarity of the channel to the niche centroid.
match_strength	"strong" | "moderate" | "weak"	Categorized confidence.
engagement	object	Three ratio-keyed distribution objects (view_to_sub_ratio, like_to_view_ratio, comment_to_view_ratio). Each carries p10, p25, p50, p75, p90, p95 — float | None.
title_patterns	object	Same fields as channel.title_patterns plus common_niche_phrases: list of {phrase: str, frequency: float | None, used_by_channel: bool}.
exemplar_channels	list (up to 5)	{title: str | None, subscriber_count: int | None}.

Cost: 5 credits per call.

---

client.benchmark_video(...) — single video vs. niche

Benchmark one YouTube video against its niche distribution.

result = client.benchmark_video(
    url="https://www.youtube.com/watch?v=dQw4w9WgXcQ",
)
print(result.video.engagement_percentiles.overall)
print(result.video.title_patterns.fits_niche_patterns)

Parameters

Name	Type	Required	Default	Description
url	str	yes	—	YouTube video URL, max 1024 chars. Accepts youtube.com/watch?v=…, youtu.be/…, youtube.com/shorts/…, youtube.com/embed/….

Returns BenchmarkVideoResponse — two top-level objects, video and niche.

video

Field	Type	Description
video_id	str	11-character YouTube video ID.
title	str	Video title. May be blank.
channel_title	str	Owning channel's display name. May be blank.
published_at	datetime	UTC publish timestamp.
view_count	int	Public view count at fetch time.
like_count	int | None	None when likes are hidden on the video.
comment_count	int | None	None when comments are disabled.
engagement	object	view_to_sub_ratio, like_to_view_ratio, comment_to_view_ratio — each float | None.
engagement_percentiles	object	Same three ratios plus overall, each int (0–100) | None.
title_patterns	object	length_chars (int | None), has_question (bool), has_number (bool), has_emoji (bool), fits_niche_patterns (bool).

niche

Same shape as benchmark_channel's niche — slug, name, match_score, match_strength, ratio-keyed engagement distributions, title_patterns with common_niche_phrases. The used_by_channel flag on each common phrase here means "did this single video's title use the phrase"; the serializer field name stays the same across both benchmark endpoints.

Cost: 3 credits per call.

---

client.niches() — list catalogued niches

List every catalogued YouTube niche for the active research run. Use the slug values as the niche argument to client.content_gaps(...).

result = client.niches()
for n in result.niches:
    print(n.slug, n.gap_count)

Parameters: none.

Returns NicheListResponse

Field	Type	Description
niches	list[NicheSummary]	Flat array of catalogued niches.

Each NicheSummary:

Field	Type	Description
slug	str	Canonical niche slug.
name	str	Human-readable name.
gap_count	int	Number of content gaps catalogued for that niche in the active run, for the default gap types. 0 means the niche exists in the taxonomy but no gaps have been ranked yet.

Cost: 1 credit per call.

---

client.content_gaps(...) — ranked content opportunities

Return ranked content opportunities (gaps) for a YouTube niche.

result = client.content_gaps(
    niche="python_programming_tutorials",
    gap_type=["underserved", "stale"],   # or just "underserved"
    limit=10,
    min_score=60,
)
for gap in result.gaps:
    print(gap.opportunity_score, gap.canonical_title)

Parameters

Name	Type	Required	Default	Description
niche	str	yes	—	Slug from client.niches(), max 100 chars.
gap_type	str | list[str] | None	no	None (server defaults to ["underserved", "stale"])	One of "underserved", "stale", "competitive", or a list of those. "competitive" is opt-in (omit from the list to exclude it).
limit	int | None	no	None (server default: 20)	1–50.
min_score	int | None	no	None (server default: 0)	Minimum opportunity_score (0–100) to include.

Returns ContentGapsResponse

Field	Type	Description
niche	object	{slug: str, name: str}.
gaps	list[ContentGapsItem]	Ranked gaps (see below).

Each gap (ContentGapsItem):

Field	Type	Description
canonical_title	str	Suggested canonical title for the gap.
opportunity_score	int (0–100)	Composite ranking score.
gap_type	"underserved" | "stale" | "competitive"	Which category the gap falls into.
components	object	{demand: float, supply: float, recency: float} — the three signals that make up opportunity_score.
explanation	str	Short rationale for why this gap exists. May be blank.
suggested_angles	list[str]	Concrete video angles the creator could take.
evidence	object	Supporting signals. See below.

Nested evidence:

Field	Type	Description
newest_quality_video_age_days	int | None	Age (in days) of the newest high-quality video in this gap; None if no qualifying video exists.
trends_appearance_count	int	How many times this topic appeared in trends signals.
autocomplete_rank	int | None	YouTube autocomplete rank, if observed.
residual_outlier_count	int	Number of outlier signals contributing to the score.
top_competitors	list (up to 5)	{title: str, channel_title: str, subscriber_count: int | None, view_count: int, age_days: int, published_at: datetime}.
related_queries	list[str] (up to 5)	Adjacent search queries.

Cost: 5 credits per call.

---

client.me() — account info

Return account info and plan details for the authenticated API key. Free to call.

me = client.me()
print(me.email, me.plan.name, me.credits_remaining)

Parameters: none.

Returns MeResponse

Field	Type	Description
email	str	Account email.
full_name	str	May be blank if the user hasn't set it.
plan	Plan (nested)	{name: str, slug: str, monthly_credits: int, rate_limit_per_minute: int}.
credits_remaining	int	Credits left in the current billing period.
period_end	datetime	When the current billing period ends and credits reset.

Cost: free (no credits deducted).

---

client.usage() — credit balance + recent activity

Return the credit balance and recent API activity for the authenticated API key. Free to call.

usage = client.usage()
print(usage.credits_remaining, "/", usage.credits_total)
for entry in usage.recent_activity:
    print(entry.created_at, entry.endpoint, entry.delta)

Parameters: none.

Returns UsageResponse

Field	Type	Description
credits_remaining	int	Credits left in the current billing period.
credits_total	int	Total credits for the current plan (resets at period_end).
period_end	datetime	When the current billing period ends.
recent_activity	list[CreditLedgerEntry]	Up to 20 most-recent credit-ledger entries.

Each CreditLedgerEntry:

Field	Type	Description
delta	int	Signed change. Negative for API charges.
balance_after	int	Credit balance immediately after this entry.
reason	str	Free-form reason (e.g. "api_call", "monthly_reset").
endpoint	str	API endpoint path that triggered the entry. May be blank for non-API entries.
created_at	datetime	UTC timestamp.

Cost: free (no credits deducted).

---

Errors

The SDK raises typed exceptions for each documented status code:

Status	Exception	Notes
400	BadRequestError	Validation failed.
401	AuthenticationError	Missing, invalid, or expired API key.
402	InsufficientCreditsError	Account is out of credits.
429	RateLimitError	Too many requests. retry_after (int seconds).
503	ServiceUnavailableError	Scoring service down. retry_after (int seconds).
5xx	ServerError	Other server-side failure.
network	NetworkError	DNS, connection refused, TLS, timeout.

All API errors inherit BrightBeanAPIError. Network failures raise NetworkError. Both inherit BrightBeanError for catch-all handling.

Retries

Idempotent GETs (me(), usage()) retry automatically on 5xx and network errors with exponential backoff + jitter. Tune via max_retries:

client = BrightBean(api_key="bb_...", max_retries=5)

POST endpoints and paid GETs are never auto-retried because the server may have charged credits before the network response was lost. Catch RateLimitError or ServiceUnavailableError and back off using retry_after if you need retry semantics.

Configuration

BrightBean(
    api_key="bb_...",                   # required
    base_url="https://api.brightbean.xyz",
    timeout=30.0,                       # seconds, or httpx.Timeout(...)
    max_retries=3,                      # idempotent GETs only
    user_agent=None,                    # override the default UA string
)

base_url defaults to https://api.brightbean.xyz. Override for staging or local testing.

Development

pip install -e .[dev]
openapi-python-client generate \
    --path ../../openapi.yaml \
    --config generator.yaml \
    --meta=none \
    --output-path ./brightbean/_generated \
    --overwrite
pytest && ruff check . && mypy brightbean

The brightbean/_generated/ directory is regenerated from the upstream OpenAPI spec. The hand-written facade (brightbean/_client.py, brightbean/errors.py, brightbean/__init__.py) wraps it to give the ergonomic BrightBean import shape.