get alco prediction and table working
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@ -8,3 +8,4 @@ bootstrap-flask
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waitress
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bokeh
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pandas
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duckdb
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@ -1,6 +1,7 @@
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from bokeh.core.enums import SpatialUnitsType
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import mongo.build_db as beer_database
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import mongo.query_db as beer_database_query
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from table import table_builder
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from flask import Flask, render_template, request, jsonify, redirect, session
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from flask_wtf import FlaskForm, CSRFProtect
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@ -14,6 +15,7 @@ from charts import BeerCharts
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from bokeh.io import output_file, show
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from bokeh.layouts import row
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app = Flask(__name__)
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app.secret_key = 'testsecret' #this value will change
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@ -62,11 +64,16 @@ def index():
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def updater():
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if 'logged_in' not in session:
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return redirect("/")
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#create_graphs()
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predicted_alc_table = table_builder.TableBuilder().table_build()
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tr_replace_string = '<tr align="center" style="border-bottom:1pt solid black;">'
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beer_html = predicted_alc_table.to_html(col_space='75px', index=False,
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justify='center', border=3).replace('<tr>', tr_replace_string)
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query_db = beer_database_query.pool_query()
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query = query_db.get_top(10, "sg")
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form = dataForm()
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if form.validate_on_submit():
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database = beer_database.beer_data()
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new_record = {
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@ -91,9 +98,11 @@ def updater():
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database.create_re_record(new_record["beer_run_id"], new_record["beer_type"], new_record["sg"],
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new_record["date"], final_run_value, new_record["comment"])
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return render_template("updater.html", list=query, form=form, success=True, updater_name = "Saucy Beer Maker")
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return render_template("updater.html", beer_data = beer_html
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, list=query, form=form, success=True, updater_name = "Saucy Beer Maker")
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else:
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return render_template("updater.html", list=query, form=form, sucess=False)
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return render_template("updater.html", beer_data = beer_html
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, list=query, form=form, sucess=False)
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# @app.route("/update_db", methods=["POST"])
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# def beer_data_update():
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@ -2,12 +2,13 @@ import sys
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from mongo.get_conn import db_conn
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import pandas as pd
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import duckdb
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class TableBuilder():
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def __init__(self) -> None:
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self.db = db_conn()
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def table_build(self, field, read_count=3, runs=5) -> pd.DataFrame:
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def table_build(self, limit=10) -> pd.DataFrame:
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data = self.db.beer_db
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data = data.find({}).sort("date", -1)
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df_dict = {}
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@ -21,9 +22,28 @@ class TableBuilder():
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df_dict["sg"].append(record["sg"])
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df_dict["date"].append(record["date"])
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df_dict["final_reading"].append(record["final_reading"])
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df = pd.DataFrame(data=df_dict)
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df_sum = df.groupby('beer_run_id').agg({'sg': ['max', 'min']})
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return df_sum
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sql = f"""
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SELECT x.beer_run_id as "Beer Run",
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max(sg) as "Max",
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min(sg) as "Min"
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FROM df x
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JOIN
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( SELECT DISTINCT beer_run_id
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FROM df
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WHERE final_reading = 'True'
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) y ON x.beer_run_id = y.beer_run_id
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GROUP BY x.beer_run_id
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ORDER BY x.beer_run_id desc
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LIMIT {limit}
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"""
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df_sum = duckdb.sql(sql).df()
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sql = f"""
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SELECT *,
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ROUND(((CAST (max AS INTEGER) - CAST(min AS INTEGER)) / 7.36) + 0.5, 2) AS "Alcohol Prediction"
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FROM df_sum
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"""
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df_calc = duckdb.sql(sql).df()
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return df_calc
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@ -46,18 +46,15 @@
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</div>
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</div>
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</td> -->
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<td>
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<div class="container">
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<div class= "col-xs-12 col-sm-12 col-md-12">
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<!--<iframe style="width: 100vw; height: 40vh;" src="static/data_plot.html" frameborder="0" allowfullscreen>
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<!--<iframe style="width: 100vw; height: 40vh;" src="static/data_plot.html" frameborder="0" allowfullscreen>
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<!--<iframe style="width: 100vw;height: 80vh;position: relative;" src="static/data_plot.html" frameborder="0" allowfullscreen>-->
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</iframe>
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</div>
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</div>
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</td>
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</tr>
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</table>
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</div>
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<div class="col-md-6">
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{{ beer_data | safe }}
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</div>
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</div>
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</div>
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</div>
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@ -2,4 +2,4 @@ import table.table_builder as table_builder
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test = table_builder.TableBuilder()
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print(test.table_build("sg"))
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print(test.table_build())
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