Add link to current and previous month's report.

[chrisu/seepark.git] / web / seepark_web.py

diff --git a/web/seepark_web.py b/web/seepark_web.py
index acec9c55c4db9aa3a4dd659ef3d8042e19d20585..c6ceffb8614b6f049317983f6372bcc217e12048 100644 (file)
--- a/web/seepark_web.py
+++ b/web/seepark_web.py
@@ -1,14 +1,46 @@
+import collections

 import datetime
 import datetime

+import itertools

 import time
 import configparser
 import os
 import sys
 from collections import defaultdict
 import time
 import configparser
 import os
 import sys
 from collections import defaultdict

+import io
+import numpy as np
+import matplotlib
+matplotlib.use('pdf')
+import matplotlib.pyplot as plt
+from matplotlib.backends.backend_pdf import PdfPages
+

 from flask import Flask, render_template, jsonify, request, abort, Response, make_response
 import flask.json
 from flask_sqlalchemy import SQLAlchemy, inspect
 from sqlalchemy import func
 
 from flask import Flask, render_template, jsonify, request, abort, Response, make_response
 import flask.json
 from flask_sqlalchemy import SQLAlchemy, inspect
 from sqlalchemy import func
 

+MONTH_DE = [
+    'Jänner',
+    'Februar',
+    'März',
+    'April',
+    'Mai',
+    'Juni',
+    'Juli',
+    'August',
+    'September',
+    'Oktober',
+    'November',
+    'Dezember']
+
+DAY_OF_WEEK_DE = [
+    'Montag',
+    'Dienstag',
+    'Mittwoch',
+    'Donnerstag',
+    'Freitag',
+    'Samstag',
+    'Sonntag']
+

 
 # https://stackoverflow.com/a/37350445
 def sqlalchemy_model_to_dict(model):
 
 # https://stackoverflow.com/a/37350445
 def sqlalchemy_model_to_dict(model):


@@ -29,6 +61,11 @@ def parse_datetime(date_str):
     return datetime.datetime.strptime(date_str, '%Y-%m-%dT%H:%M:%S')
 
 
     return datetime.datetime.strptime(date_str, '%Y-%m-%dT%H:%M:%S')
 
 

+def ntimes(it, n):
+    for v in it:
+        yield from itertools.repeat(v, n)
+
+

 def get_sqlalchemy_database_uri(config):
     user = config.get('database', 'user')
     pwd = config.get('database', 'password')
 def get_sqlalchemy_database_uri(config):
     user = config.get('database', 'user')
     pwd = config.get('database', 'password')


@@ -95,6 +132,13 @@ def select_sensordata(sensor_id, sensor_type, begin, end):
     return query.all()
 
 
     return query.all()
 
 

+def sensordata_to_xy(sensordata):
+    sensordata = list(sensordata)
+    x = np.array([d.timestamp for d in sensordata])
+    y = np.array([d.value for d in sensordata])
+    return x, y
+
+

 def select_sensordata_grouped(sensor_id, sensor_type, begin, end):
     # determine resolution (interval in seconds for data points)
     resolution = calc_grouping_resolution(begin, end)
 def select_sensordata_grouped(sensor_id, sensor_type, begin, end):
     # determine resolution (interval in seconds for data points)
     resolution = calc_grouping_resolution(begin, end)


@@ -124,6 +168,13 @@ def select_openweatherdata(cityid, begin, end):
     return query.all()
 
 
     return query.all()
 
 

+def openweatherdata_to_xy(openweatherdata):
+    openweatherdata = list(openweatherdata)
+    x = np.array([d.datetime for d in openweatherdata])
+    y = np.array([d.temp for d in openweatherdata])
+    return x, y
+
+

 def select_openweatherdata_grouped(cityid, begin, end):
     # determine resolution (interval in seconds for data points)
     resolution = calc_grouping_resolution(begin, end)
 def select_openweatherdata_grouped(cityid, begin, end):
     # determine resolution (interval in seconds for data points)
     resolution = calc_grouping_resolution(begin, end)


@@ -141,6 +192,32 @@ def select_openweatherdata_grouped(cityid, begin, end):
     return query.all()
 
 
     return query.all()
 
 

+def estimate_swimmer_count(date):
+    return date.day
+
+
+def select_swimmerdata(begin, end):
+    def report_times(begin, end):
+        d = begin
+        while d < end:
+            for t in [10, 15]:
+                a = datetime.datetime.combine(d.date(), datetime.time(t))
+                if a >= d:
+                    yield a
+            d += datetime.timedelta(days=1)
+    SwimmerData = collections.namedtuple('SwimmerData', ['datetime', 'count'])
+    for d in report_times(begin, end):
+        count = estimate_swimmer_count(d)
+        yield SwimmerData(d, count)
+
+
+def swimmerdata_to_xy(swimmerdata):
+    swimmerdata = list(swimmerdata)
+    x = np.array([d.datetime for d in swimmerdata])
+    y = np.array([d.count for d in swimmerdata])
+    return x, y
+
+

 def convert_to_c3(result, id, field_x, field_y):
     c3result = defaultdict(list)
     for row in result:
 def convert_to_c3(result, id, field_x, field_y):
     c3result = defaultdict(list)
     for row in result:


@@ -214,6 +291,17 @@ def currentwatertemperature(sensorid):
     return result.value, result.timestamp
 
 
     return result.value, result.timestamp
 
 

+def first_of_month(date, month):
+    date = date.replace(day=1)
+    if month == 0:
+        return date
+    if month == 1:
+        return (date + datetime.timedelta(days=42)).replace(day=1)
+    if month == -1:
+        return (date - datetime.timedelta(days=1)).replace(day=1)
+    assert False
+
+

 @app.route('/api/<version>/sensors/')
 def sensors(version):
     """List all sensors found in the database"""
 @app.route('/api/<version>/sensors/')
 def sensors(version):
     """List all sensors found in the database"""


@@ -226,10 +314,11 @@ def sensorid(version, sensor_id):
     """Return all data for a specific sensor
 
     URL parameters:
     """Return all data for a specific sensor
 
     URL parameters:

-    begin=<datetime>, optional, format like "2018-05-19T21:07:53"
-    end=<datetime>, optional, format like "2018-05-19T21:07:53"
-    mode=<full|consolidated>, optional. return all rows (default) or with lower resolution (for charts)
-    format=<default|c3>, optional. return result as returned by sqlalchemy (default) or formatted for c3.js
+
+    * ``begin=<datetime>``, optional, format like ``2018-05-19T21:07:53``
+    * ``end=<datetime>``, optional, format like ``2018-05-19T21:07:53``
+    * ``mode=<full|consolidated>``, optional. return all rows (default) or with lower resolution (for charts)
+    * ``format=<default|c3>``, optional. return result as returned by sqlalchemy (default) or formatted for c3.js

     """
     result = sensordata(sensor_id=sensor_id)
     return jsonify(result)
     """
     result = sensordata(sensor_id=sensor_id)
     return jsonify(result)


@@ -240,10 +329,11 @@ def sensortype(version, sensor_type):
     """Return all data for a specific sensor type
 
     URL parameters:
     """Return all data for a specific sensor type
 
     URL parameters:

-    begin=<datetime>, optional, format like "2018-05-19T21:07:53"
-    end=<datetime>, optional, format like "2018-05-19T21:07:53"
-    mode=<full|consolidated>, optional. return all rows (default) or with lower resolution (for charts)
-    format=<default|c3>, optional. return result as returned by sqlalchemy (default) or formatted for c3.js
+
+    * ``begin=<datetime>``, optional, format like ``2018-05-19T21:07:53``
+    * ``end=<datetime>``, optional, format like ``2018-05-19T21:07:53``
+    * ``mode=<full|consolidated>``, optional. return all rows (default) or with lower resolution (for charts)
+    * ``format=<default|c3>``, optional. return result as returned by sqlalchemy (default) or formatted for c3.js

     """
     result = sensordata(sensor_type=sensor_type)
     return jsonify(result)
     """
     result = sensordata(sensor_type=sensor_type)
     return jsonify(result)


@@ -275,21 +365,98 @@ def currentwater(version):
     return jsonify({"value": value, "timestamp": timestamp})
 
 
     return jsonify({"value": value, "timestamp": timestamp})
 
 

-@app.route('/report/<int:year>-<int:month>')
+@app.route('/report/<int(fixed_digits=4):year>/<int(fixed_digits=2):month>')

 def report(year, month):
 def report(year, month):

-    import io
-    import numpy as np
-    import matplotlib.pyplot as plt
-    from matplotlib.backends.backend_pdf import PdfPages
+    """Report for given year (4 digits) and month (2 digits)
+    """
+    paper_size = (29.7 / 2.54, 21. / 2.54)  # A4
+
+    begin = datetime.datetime(year, month, 1)
+    end = first_of_month(begin, 1)
+
+    water_data = sensordata_to_xy(select_sensordata(mainsensor, 'Wassertemperatur', begin, end))
+    air_data = openweatherdata_to_xy(select_openweatherdata(cityid, begin, end))
+    swimmer_data = swimmerdata_to_xy(select_swimmerdata(begin, end))
+
+    report_times = [datetime.time(10), datetime.time(15)]
+    report_data = {'Wasser': water_data, 'Luft': air_data}
+
+    days_datetime = []
+    d = begin
+    while d < end:
+        days_datetime.append(d)
+        d = d + datetime.timedelta(1)

 
     binary_pdf = io.BytesIO()
     with PdfPages(binary_pdf) as pdf:
 
     binary_pdf = io.BytesIO()
     with PdfPages(binary_pdf) as pdf:

-        a4 = (21./2.54, 29.7/2.54)
-        plt.figure(figsize=a4)
-        x = np.arange(100)
-        y = np.sin(x/4)
-        plt.plot(x, y)
+        title = 'Seepark Obsteig {} {}'.format(MONTH_DE[begin.month-1], begin.year)
+
+        # graphic
+        plt.figure(figsize=paper_size)
+        report_colors = []
+        for label, data in sorted(report_data.items(), reverse=True):
+            x, y = data
+            lines = plt.plot(x, y, label=label)
+            report_colors.append(lines[0].get_color())
+        plt.xticks(days_datetime, [''] * len(days_datetime))
+        plt.ylabel('Temperatur in °C')
+        plt.axis(xmin=begin, xmax=end)
+        plt.legend()
+        plt.grid()
+        plt.title(title)
+
+        # table
+        columns = []
+        for d in days_datetime:
+            columns.append('{}.'.format(d.day))
+        rows = []
+        for label in sorted(report_data.keys(), reverse=True):
+            for t in report_times:
+                rows.append('{:02d}:{:02d} {} °C'.format(t.hour, t.minute, label))
+        for t in report_times:
+            rows.append('{:02d}:{:02d} Badende'.format(t.hour, t.minute))
+        cells = []
+        for label, data in sorted(report_data.items(), reverse=True):
+            for t in report_times:
+                row_cells = []
+                x, y = data
+                for d in days_datetime:
+                    report_datetime = datetime.datetime.combine(d.date(), t)
+                    closest_index = np.argmin(np.abs(x - report_datetime))
+                    if abs(x[closest_index] - report_datetime) > datetime.timedelta(hours=1):
+                        cell = 'N/A'
+                    else:
+                        value = y[closest_index]
+                        cell = '{:.1f}'.format(value)
+                    row_cells.append(cell)
+                cells.append(row_cells)
+        for t in report_times:
+            row_cells = []
+            x, y = swimmer_data
+            for d in days_datetime:
+                report_datetime = datetime.datetime.combine(d.date(), t)
+                closest_index = np.argmin(np.abs(x - report_datetime))
+                if abs(x[closest_index] - report_datetime) > datetime.timedelta(hours=1):
+                    cell = 'N/A'
+                else:
+                    cell = y[closest_index]
+                row_cells.append(cell)
+            cells.append(row_cells)
+        row_colors = list(ntimes(report_colors + ['w'], len(report_times)))
+        table = plt.table(cellText=cells, colLabels=columns, rowLabels=rows, rowColours=row_colors, loc='bottom')
+        table.scale(xscale=1, yscale=2)
+        plt.title(title)
+        plt.subplots_adjust(left=0.15, right=0.97, bottom=0.3)  # do not cut row labels

         pdf.savefig()
         pdf.savefig()

+
+        pdf_info = pdf.infodict()
+        pdf_info['Title'] = title
+        pdf_info['Author'] = 'Chrisu Jähnl'
+        pdf_info['Subject'] = 'Temperaturen'
+        pdf_info['Keywords'] = 'Seepark Obsteig'
+        pdf_info['CreationDate'] = datetime.datetime.now()
+        pdf_info['ModDate'] = datetime.datetime.today()
+

     response = make_response(binary_pdf.getvalue())
     response.headers['Content-Type'] = 'application/pdf'
     response.headers['Content-Disposition'] = 'attachment; filename=seepark_{:04d}-{:02d}.pdf'.format(year, month)
     response = make_response(binary_pdf.getvalue())
     response.headers['Content-Type'] = 'application/pdf'
     response.headers['Content-Disposition'] = 'attachment; filename=seepark_{:04d}-{:02d}.pdf'.format(year, month)


@@ -300,6 +467,8 @@ def report(year, month):
 def index():
     airvalue, airtime     = currentairtemperature(cityid)
     watervalue, watertime = currentwatertemperature(mainsensor)
 def index():
     airvalue, airtime     = currentairtemperature(cityid)
     watervalue, watertime = currentwatertemperature(mainsensor)

+    this_month = first_of_month(datetime.date.today(), 0)
+    last_month = first_of_month(this_month, -1)

 
     return render_template(
         'seepark_web.html',
 
     return render_template(
         'seepark_web.html',


@@ -308,4 +477,6 @@ def index():
         watertime=watertime,
         airvalue=airvalue,
         airtime=airtime,
         watertime=watertime,
         airvalue=airvalue,
         airtime=airtime,

+        this_month=this_month,
+        last_month=last_month

     )
     )