stock-tracker

2026-07-04 00:17:11 +08:00
commit 6087341a48
6463 changed files with 1929869 additions and 0 deletions
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+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+"""
+Date: 2020/3/1 0:02
+Desc:
+"""
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+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+"""
+Date: 2024/7/6 14:02
+Desc: ownthink-knowledge graph
+https://ownthink.com/
+https://www.ownthink.com/docs/kg/
+"""
+
+import pandas as pd
+import requests
+
+
+def nlp_ownthink(word: str = "人工智能", indicator: str = "entity") -> pd.DataFrame:
+    """
+    Knowledge Graph interface for financial research
+    https://ownthink.com/
+    :param word: word in chinese
+    :type word: str
+    :param indicator: entity or desc or avp or tag
+    :type indicator: str
+    :return: indicator data
+    :rtype: list or dict or pandas.DataFrame
+    """
+    url = "https://api.ownthink.com/kg/knowledge"
+    payload = {
+        "entity": word,
+    }
+    r = requests.post(url, data=payload)
+    if not r.json()["data"]:
+        print("Can not find the resource, please type into the correct word")
+        return pd.DataFrame()
+    if indicator == "entity":
+        return r.json()["data"]["entity"]
+    if indicator == "desc":
+        return r.json()["data"]["desc"]
+    if indicator == "avp":
+        return pd.DataFrame(r.json()["data"]["avp"], columns=["字段", "值"])
+    if indicator == "tag":
+        return r.json()["data"]["tag"]
+
+
+def nlp_answer(question: str = "人工智能") -> str:
+    """
+    智能问答
+    https://ownthink.com/robot.html
+    :param question: word in chinese
+    :type question: str
+    :return: indicator data
+    :rtype: list or dict or pandas.DataFrame
+    """
+    url = "https://api.ownthink.com/bot"
+    params = {"spoken": question}
+    r = requests.get(url, params=params)
+    json_data = r.json()
+    answer = json_data["data"]["info"]["text"]
+    return answer
+
+
+if __name__ == "__main__":
+    nlp_ownthink_df = nlp_ownthink(word="人工智能", indicator="entity")
+    print(nlp_ownthink_df)
+
+    nlp_answer_df = nlp_answer(question="姚明的身高")
+    print(nlp_answer_df)