Best Free Stock Screener API
Filters, Limits & Python最佳免费股票筛选 API
字段、限额与 Python 接入

Best free stock screener API: choose by workload免费股票筛选 API：按实际任务选择

There is no universal winner. A stock-screener API must provide a programmable way to filter an eligible universe—not merely fetch one ticker’s quote. The best fit exposes the required fundamental or technical filters, covers the target exchanges, returns a stable schema, and permits the intended use.

股票筛选 API 必须能够按程序化条件过滤一个定义清楚的证券池，而不只是查询单只股票价格。应先确认接口能否直接执行所需筛选，再比较覆盖市场、字段口径、数据延迟、调用频率与许可。

Choose by workload before choosing by brand. A server-side fundamental screen needs expressive conditions and reliable fiscal-period semantics; a live technical scanner needs broad quote coverage and synchronized timestamps; a small research notebook may work better with bulk data and local filtering; a historical strategy test requires point-in-time fundamentals, old universes, and delisted securities. One free plan rarely leads all four categories.

应先按任务选型，再比较品牌。服务端基本面筛选需要丰富条件和可靠的财务期间口径；实时技术扫描需要广泛行情覆盖与同步时间戳；小型研究脚本可能更适合批量取数后本地过滤；历史策略检验则必须具备时点基本面、历史证券池和退市股票。一种免费套餐通常无法同时在四类任务中领先。

Stock screener API filters and limits to compare股票筛选 API 应比较的字段与限制

Filters, exchange coverage, freshness, pagination, rate limits, authentication, and licensing are separate pass/fail requirements. Confirm every one before comparing SDK convenience or response speed.

字段、交易所覆盖、时效、分页、限流、鉴权与许可都是独立的准入条件。应先逐项确认，再比较 SDK 是否方便或响应速度是否更快。

Use a fixed four-stock fixture to verify filter semantics用四只合成股票验证筛选语义

Define the universe before the rules: US primary-listed common stocks, excluding ETFs and ADRs, observed at the June 30 close. Use only fundamentals that were publicly available by that cutoff. Apply market_cap_usd >= 1,000m, ttm_revenue_growth > 10%, and avg_dollar_volume_20d_usd >= 5m. Exclude a security when a required field is null rather than treating null as zero.

应先定义证券池，再定义筛选条件：以 6 月 30 日收盘为截至时点，选择美国主要上市的普通股，排除 ETF 与 ADR，并且只使用该时点前已经公开的基本面数据。条件设为 market_cap_usd >= 1,000m、ttm_revenue_growth > 10%、avg_dollar_volume_20d_usd >= 5m。必需字段为空时排除该证券，不能把空值当成零。

The API should return the same two matches and an explainable reason for each exclusion. Record whether market cap uses the closing price or a later quote, which four fiscal quarters form TTM revenue, how non-USD values are converted, and whether the threshold operators are inclusive. Without those details, two syntactically identical screens can implement different decisions.

接口应稳定返回两只符合条件的股票，并能解释每一项排除原因。同时记录市值采用收盘价还是更晚的行情、TTM 收入由哪四个财季组成、非美元数值如何换算，以及阈值是否包含边界。缺少这些信息时，两个写法相同的筛选条件仍可能执行不同决策。

Free stock screener API options to verify需要核验的免费股票筛选 API 选项

This is a verification shortlist, not a permanent ranking. “Best” depends on whether you need server-side screening or raw data for client-side filtering. Build a scorecard before testing: assign pass/fail gates for market, security type, required fields, freshness, historical behavior, license, and budget; score convenience only after every gate passes. This prevents an attractive SDK or generous headline quota from masking a missing core capability.

这是核验清单，不是永久排名。“最佳”取决于你需要服务端直接筛选，还是获取原始数据后在本地筛选。测试前应先建立评分表：把市场、证券类型、必需字段、时效、历史能力、许可和预算设为通过/不通过门槛，全部满足后再评价接入便利性。这样可以避免好看的 SDK 或醒目的高额度掩盖核心能力缺失。

Free stock screener API Python test workflow免费股票筛选 API 的 Python 验证流程

from decimal import Decimal, InvalidOperation
import requests


FILTERS = {
    "as_of": "2026-06-30",
    "security_type": "common_stock",
    "country": "US",
    "filters": [
        {"field": "market_cap_usd", "op": "gte", "value": 1_000_000_000},
        {"field": "ttm_revenue_growth", "op": "gt", "value": 0.10},
        {"field": "avg_dollar_volume_20d_usd", "op": "gte", "value": 5_000_000},
    ],
    "sort": ["market_cap_usd:desc", "security_id:asc"],
    "limit": 100,
}


def as_decimal(row, field):
    value = row.get(field)
    if value is None:
        return None
    try:
        return Decimal(str(value))
    except InvalidOperation as exc:
        raise ValueError(f"{field} is not numeric: {value!r}") from exc


def fetch_screen(endpoint, api_key):
    cursor = None
    snapshot = None
    seen = set()
    matches = []

    with requests.Session() as session:
        while True:
            body = {**FILTERS, "cursor": cursor}
            response = session.post(
                endpoint,
                headers={"Authorization": f"Bearer {api_key}"},
                json=body,
                timeout=(5, 30),
            )
            response.raise_for_status()
            payload = response.json()

            page_snapshot = payload.get("snapshot")
            snapshot = snapshot or page_snapshot
            if page_snapshot != snapshot:
                raise RuntimeError("Provider snapshot changed during pagination")

            for row in payload.get("results", []):
                identity = (row.get("security_id"), row.get("exchange"))
                if not all(identity):
                    raise ValueError("Stable security_id and exchange are required")
                if identity in seen:
                    raise ValueError(f"Duplicate security across pages: {identity}")
                seen.add(identity)

                cap = as_decimal(row, "market_cap_usd")
                growth = as_decimal(row, "ttm_revenue_growth")
                liquidity = as_decimal(row, "avg_dollar_volume_20d_usd")
                if None in (cap, growth, liquidity):
                    continue
                if cap >= 1_000_000_000 and growth > Decimal("0.10") \
                        and liquidity >= 5_000_000:
                    matches.append(row)

            cursor = payload.get("next_cursor")
            if not cursor:
                return matches

How QVeris helps connect stock screening toolsQVeris 如何连接股票筛选能力

• Open the QVeris provider details for stock screening and financial-data capabilities.
• Inspect provider documentation, authentication, operators, units, response shape, pagination, timestamp behavior, and known limitations before connecting.
• Give an agent explicit requirements for market, universe, filter logic, as-of date, null policy, sorting, result cap, and freshness instead of asking it for a vague “best screener.”
• Keep provider attribution, retrieval time, query version, and license notes with every result; capability access is not investment advice.

• 使用 QVeris 服务商详情搜索股票筛选与金融数据能力。
• 连接前检查供应商文档、鉴权、操作符、单位、返回结构、分页、时间戳行为和已知限制。
• 向 Agent 明确提供市场、证券池、筛选逻辑、截至日期、空值规则、排序、结果上限和时效要求，不要只笼统地询问“最佳选股器”。
• 为结果保留供应商、获取时间、查询版本与许可说明；能力连接不构成投资建议。

Best free stock screener API FAQ免费股票筛选 API 常见问题

Authoritative references and related guides权威参考与相关指南