perf: fast rest api by using meinheld

Crazy-LittleBoy · Mar 8, 2023 · c6914f5 · c6914f5
1 parent 25bf509
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diff --git a/docker/Dockerfiles/yake-server/Dockerfile b/docker/Dockerfiles/yake-server/Dockerfile
@@ -24,7 +24,7 @@ RUN pip install -r requirements.txt
 
 # install yake via pip
 #RUN pip install git+https://github.com/liaad/yake.git
-RUN pip install git+https://github.com/Crazy-LittleBoy/yake.git
+RUN pip install git+https://github.moeyy.xyz/https://github.com/Crazy-LittleBoy/yake.git
 
 # Copy server startup script
 COPY ./yake-rest-api.py /temp

diff --git a/docker/Dockerfiles/yake-server/yake-rest-api-old.py b/docker/Dockerfiles/yake-server/yake-rest-api-old.py
@@ -0,0 +1,145 @@
+"""
+Credits @arianpasquali
+https://gist.githubusercontent.com/arianpasquali/16b2b0ab2095ee35dbede4dd2f4f8520/raw/ba4ea7da0d958fc4b1b2e694f45f17cc71d8238d/yake_rest_api.py
+
+The simple example serving YAKE as a rest api.
+
+instructions:
+
+ pip install flasgger
+ pip install git+https://github.com/LIAAD/yake
+
+ python yake_rest_api.py
+
+open http://127.0.0.1:5000/apidocs/
+"""
+
+from flasgger import Swagger
+from flask import Flask, jsonify, request
+
+try:
+    import simplejson as json
+except ImportError:
+    import json
+try:
+    from http import HTTPStatus
+except ImportError:
+    import httplib as HTTPStatus
+
+import yake
+
+app = Flask(__name__)
+app.config['SWAGGER'] = {
+    'title': 'Yake API Explorer',
+    'uiversion': 3
+}
+swagger = Swagger(app)
+
+
+@swagger.validate('content')
+@app.route('/yake/', methods=['POST'])
+def handle_yake():
+    """Example endpoint return a list of keywords using YAKE
+    ---
+    consumes:
+      - application/json
+    produces:
+      - application/json
+    parameters:
+        - name: content
+          in: body
+          description: content object
+          required: true
+          schema:
+            $ref: '#/definitions/content'
+
+    requestBody:
+        description: Optional description in *Markdown*
+        required: true
+        content:
+          application/json:
+            schema:
+              id: content
+              type: object
+
+
+    responses:
+      200:
+        description: Extract keywords from input text
+        schema:
+            $ref: '#/definitions/result'
+
+    definitions:
+      content:
+        description: content object
+        properties:
+          text:
+            type: string
+          language:
+            type: string
+          max_ngram_size:
+            type: integer
+            minimum: 1
+          number_of_keywords:
+            type: integer
+            minimum: 1
+        required:
+          - text
+          - language
+          - max_ngram_size
+          - number_of_keywords
+        example:   # Sample object
+            text: Sources tell us that Google is acquiring Kaggle, a platform that hosts data science and machine learning   competitions. Details about the transaction remain somewhat vague , but given that Google is hosting   its Cloud Next conference in San Francisco this week, the official announcement could come as early   as tomorrow.  Reached by phone, Kaggle co-founder CEO Anthony Goldbloom declined to deny that the   acquisition is happening. Google itself declined 'to comment on rumors'.   Kaggle, which has about half a million data scientists on its platform, was founded by Goldbloom   and Ben Hamner in 2010. The service got an early start and even though it has a few competitors   like DrivenData, TopCoder and HackerRank, it has managed to stay well ahead of them by focusing on its   specific niche. The service is basically the de facto home for running data science  and machine learning   competitions.  With Kaggle, Google is buying one of the largest and most active communities for   data scientists - and with that, it will get increased mindshare in this community, too   (though it already has plenty of that thanks to Tensorflow and other projects).   Kaggle has a bit of a history with Google, too, but that's pretty recent. Earlier this month,   Google and Kaggle teamed up to host a $100,000 machine learning competition around classifying   YouTube videos. That competition had some deep integrations with the Google Cloud Platform, too.   Our understanding is that Google will keep the service running - likely under its current name.   While the acquisition is probably more about Kaggle's community than technology, Kaggle did build   some interesting tools for hosting its competition and 'kernels', too. On Kaggle, kernels are   basically the source code for analyzing data sets and developers can share this code on the   platform (the company previously called them 'scripts').  Like similar competition centric sites,   Kaggle also runs a job board, too. It's unclear what Google will do with that part of the service.   According to Crunchbase, Kaggle raised $12.5 million (though PitchBook says it's $12.75) since its   launch in 2010. Investors in Kaggle include Index Ventures, SV Angel, Max Levchin, Naval Ravikant,   Google chief economist Hal Varian, Khosla Ventures and Yuri Milner
+            language: en
+            max_ngram_size: 3
+            number_of_keywords: 10
+      result:
+        type: array
+        items:
+          minItems: 0
+          type: object
+          required:
+            - name
+            - value
+          properties:
+            ngram:
+              type: string
+            score:
+              type: number
+    """
+
+    try:
+        assert request.json["text"], "Invalid text"
+        assert len(request.json["language"]) == 2, "Invalid language code"
+        assert int(request.json["max_ngram_size"]), "Invalid max_ngram_size, Suggested max_ngram_size setting of 1 or 2 or 3"
+        assert int(request.json["number_of_keywords"]), "Invalid number_of_keywords"
+        assert int(request.json["windows_size"]), "Invalid windows_size, Suggested windows_size setting of 1 or 2"
+
+        text = request.json["text"]
+        language = request.json["language"]
+        max_ngram_size = int(request.json["max_ngram_size"])
+        number_of_keywords = int(request.json["number_of_keywords"])
+        windows_size = int(request.json["windows_size"])
+
+        my_yake = yake.KeywordExtractor(lan=language,
+                                        n=max_ngram_size,
+                                        top=number_of_keywords,
+                                        dedupLim=-1,
+                                        windowsSize=windows_size
+                                        )
+
+        keywords = my_yake.extract_keywords(text)
+        result = [{"keyword": x[0], "score": x[1]} for x in keywords]
+
+        return jsonify(result), HTTPStatus.OK
+    except IOError as e:
+        return jsonify("Language not supported"), HTTPStatus.BAD_REQUEST
+    except Exception as e:
+        return jsonify(str(e)), HTTPStatus.BAD_REQUEST
+
+
+
+
+
+if __name__ == "__main__":
+    app.run(host='0.0.0.0', debug=True)
diff --git a/docker/Dockerfiles/yake-server/yake-rest-api.py b/docker/Dockerfiles/yake-server/yake-rest-api.py
@@ -13,7 +13,7 @@
 
 open http://127.0.0.1:5000/apidocs/
 """
-
+import meinheld
 from flasgger import Swagger
 from flask import Flask, jsonify, request
 
@@ -139,4 +139,6 @@ def handle_yake():
 
 
 if __name__ == "__main__":
-    app.run(host='0.0.0.0', debug=True)
+    # app.run(host='0.0.0.0', debug=True)
+    meinheld.listen(("0.0.0.0", 5000))
+    meinheld.run(app)
diff --git a/docker/Dockerfiles/yake/Dockerfile b/docker/Dockerfiles/yake/Dockerfile
@@ -17,7 +17,7 @@ RUN apk update && apk upgrade && \
 # install yake via pip
 RUN python -m pip install --upgrade pip
 #RUN pip install git+https://github.com/liaad/yake.git
-RUN pip install git+https://github.com/Crazy-LittleBoy/yake.git
+RUN pip install git+https://github.moeyy.xyz/https://github.com/Crazy-LittleBoy/yake.git
 
 # set default command
 ENTRYPOINT ["yake"]
diff --git a/docker/build.sh b/docker/build.sh
@@ -14,6 +14,7 @@ source "$DIR/constants.sh"
 cd "$DIR/Dockerfiles/yake-server"
 docker build -t "$YAKE_SERVER_IMAGE:$TAG" .
 #docker run -d -p $YAKE_PORT:$YAKE_PORT "$YAKE_SERVER_IMAGE:$TAG"
+docker run -d -p 5000:5000 "multi-keywords/yake-server:fast"
 
 cd "$DIR/Dockerfiles/yake"
 docker build -t "$YAKE_IMAGE:$TAG" .

diff --git a/docker/constants.sh b/docker/constants.sh
@@ -3,4 +3,4 @@
 YAKE_PORT=5000
 YAKE_IMAGE="multi-keywords/yake"
 YAKE_SERVER_IMAGE="multi-keywords/yake-server"
-TAG="junbo"
+TAG="fast"
diff --git a/requirements.txt b/requirements.txt
@@ -5,4 +5,5 @@ segtok
 jellyfish
 networkx
 numpy
-click
+click
+meinheld