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96 lines
3.5 KiB
Python
96 lines
3.5 KiB
Python
5 years ago
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from __future__ import print_function
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from __future__ import unicode_literals
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from builtins import str, bytes, dict, int
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import os
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import sys
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
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from pattern.server import App
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from pattern.server import MINUTE, HOUR, DAY
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from pattern.text import language
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app = App("api")
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# The language() function in pattern.text guesses the language of a given string.
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# For example: language("In French, goodbye is au revoir.") returns ("en", 0.83).
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# It can handle "en", "es", "de", "fr", "nl", "it" with reasonable accuracy.
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# To create a web service like Google Translate with pattern.server is easy.
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# Normally, URL handlers return a string with the contents of that web page.
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# If we return a dictionary instead, it will be formatted as a JSON-string,
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# the data interchange format used by many popular web services.
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# So clients (e.g., a user's Python script) can query the web service URL
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# and catch the JSON reply.
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# There is only one tricky part: rate limiting.
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# Note the "limit", "time" and "key" parameters in @app.route() below.
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# We'll explain them in more detail.
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# First, run the script and visit:
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# http://127.0.0.1:8080/language?q=in+french+goodbye+is+au+revoir
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# You should see some JSON-output:
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# {"language": "en", "confidence": 0.83}
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@app.route("/language", limit=100, time=HOUR)
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def predict_language(q=""):
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#print(q)
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iso, confidence = language(q) # (takes some time to load the first time)
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return {
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"language": iso,
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"confidence": round(confidence, 2)
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}
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# When you set up a web service, expect high traffic peaks.
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# For example, a user may have 10,000 sentences
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# and send them all at once in a for-loop to our web service:
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# import urrlib
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# import json
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# for s in sentences[:10000]:
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# url = "http://127.0.0.1:8080/language?q=" + s.replace(" ", "-")
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# data = urllib.urlopen(url).read()
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# data = json.loads(data)
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# Rate limiting caps the number of allowed requests for a user.
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# In this example, limit=100 and time=HOUR means up to a 100 requests/hour.
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# After that, the user will get a HTTP 429 Too Many Requests error.
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# The example below demonstrates how rates can be set up per user.
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# In this case, only the user with key=1234 is allowed access.
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# All other requests will generate a HTTP 403 Forbidden error.
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# A user can pass his personal key as a query parameter, e.g.,
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# http://127.0.0.1:8080/language/paid?q=hello&key=1234
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# Check personal keys instead of IP-address:
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@app.route("/language/paid", limit=True, key=lambda data: data.get("key"))
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def predict_language_paid(q="", key=None):
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return {"language": language(q)[0]}
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# Create an account for user with key=1234 (do once).
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# You can generate fairly safe keys with app.rate.key().
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if not app.rate.get(key="1234", path="/language/paid"):
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app.rate.set(key="1234", path="/language/paid", limit=10000, time=DAY)
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# Try it out with the key and without the key:
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# http://127.0.0.1:8080/language/paid?q=hello&key=1234
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# http://127.0.0.1:8080/language/paid?q=hello (403 error)
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# A rate.db SQLite database was created in the current folder.
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# If you want to give it another name, use App(rate="xxx.db").
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# To view the contents of the database,we use the free
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# SQLite Database Browser (http://sqlitebrowser.sourceforge.net).
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# If the web service is heavily used,
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# we may want to use more threads for concurrent requests
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# (default is 30 threads with max 20 queueing):
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app.run("127.0.0.1", port=8080, threads=100, queue=50)
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