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|
#!/usr/bin/python3
import csv
import functools
from flask import (
Flask,
render_template,
send_from_directory,
jsonify
)
app = Flask(__name__)
# decision tree
class Node(object):
def __init__(self, name="", count=0):
self.children = []
self.name = name
self.count = count
def child(self, name, count):
c = Node(name, count)
self.children.append(c)
return c
def get(self, name):
return [c for c in self.children if c.name == name][0]
def traverse(self, path):
cur = self
for child in path:
cur = cur.get(child)
return cur
def predict(self, *path):
par = self.traverse(list(path))
return [{
"name": p.name,
"probability": p.count/par.count
} for p in par.children]
tree = Node()
def load():
def deeper(depth=1, parent=tree, max=8):
for depth in range(max):
with open("data/" + str(depth + 2) + ".csv") as f:
fr = csv.reader(f, delimiter=",", quotechar="\"")
for row in fr:
path = row[:-2]
name = row[-2]
c = int(row[-1])
parn = parent.traverse(path)
parn.child(name, c)
deeper()
tree.count += sum(c.count for c in tree.children)
@app.route("/")
def index():
return render_template("index.html")
@app.route("/assets/<path:path>")
def assets(path):
return send_from_directory("assets", path)
@app.route("/api/builds")
@app.route("/api/builds/<path:path>")
def api(path=None):
if path == None:
els = []
else:
els = path.split("/")
return jsonify(tree.predict(*els))
if __name__ == "__main__":
load()
app.run(debug=True)
|
