X-Git-Url: https://git.toastfreeware.priv.at/chrisu/seepark.git/blobdiff_plain/62f9135200a07a7c45dd0e966a9477da7c8486ea..d8ba29c8d3efb308ca8631970b3228bb1dd91858:/web/seepark_web.py diff --git a/web/seepark_web.py b/web/seepark_web.py index 890e681..a75acbf 100644 --- a/web/seepark_web.py +++ b/web/seepark_web.py @@ -1,23 +1,23 @@ -import collections +import configparser import datetime +import io import itertools -import time -import configparser import os -import sys from collections import defaultdict -import io -import numpy as np + import matplotlib -matplotlib.use('pdf') +import numpy as np + 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 flask_sqlalchemy import SQLAlchemy from sqlalchemy import func +matplotlib.use('pdf') + + MONTH_DE = [ 'Jänner', 'Februar', @@ -42,21 +42,6 @@ DAY_OF_WEEK_DE = [ 'Sonntag'] -# https://stackoverflow.com/a/37350445 -def sqlalchemy_model_to_dict(model): - return {c.key: getattr(model, c.key) - for c in inspect(model).mapper.column_attrs} - - -class JSONEncoder(flask.json.JSONEncoder): - def default(self, object): - if isinstance(object, datetime.datetime): - return object.isoformat() - elif isinstance(object, db.Model): - return sqlalchemy_model_to_dict(object) - return super().default(object) - - def parse_datetime(date_str): return datetime.datetime.strptime(date_str, '%Y-%m-%dT%H:%M:%S') @@ -81,11 +66,11 @@ cityid = config.get('openweathermap', 'cityid') mainsensor = config.get('webapp', 'mainsensor') app = Flask(__name__) -app.json_encoder = JSONEncoder app.config['SQLALCHEMY_DATABASE_URI'] = get_sqlalchemy_database_uri(config) app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False db = SQLAlchemy(app) -db.reflect(app=app) +with app.app_context(): + db.reflect() class Sensors(db.Model): @@ -192,32 +177,6 @@ def select_openweatherdata_grouped(cityid, begin, end): 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: @@ -291,8 +250,15 @@ def currentwatertemperature(sensorid): return result.value, result.timestamp -def add_month(date): - return (date + datetime.timedelta(days=42)).replace(day=1) +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//sensors/') @@ -307,10 +273,11 @@ def sensorid(version, sensor_id): """Return all data for a specific sensor URL parameters: - begin=, optional, format like "2018-05-19T21:07:53" - end=, optional, format like "2018-05-19T21:07:53" - mode=, optional. return all rows (default) or with lower resolution (for charts) - format=, optional. return result as returned by sqlalchemy (default) or formatted for c3.js + + * ``begin=``, optional, format like ``2018-05-19T21:07:53`` + * ``end=``, optional, format like ``2018-05-19T21:07:53`` + * ``mode=``, optional. return all rows (default) or with lower resolution (for charts) + * ``format=``, optional. return result as returned by sqlalchemy (default) or formatted for c3.js """ result = sensordata(sensor_id=sensor_id) return jsonify(result) @@ -321,10 +288,11 @@ def sensortype(version, sensor_type): """Return all data for a specific sensor type URL parameters: - begin=, optional, format like "2018-05-19T21:07:53" - end=, optional, format like "2018-05-19T21:07:53" - mode=, optional. return all rows (default) or with lower resolution (for charts) - format=, optional. return result as returned by sqlalchemy (default) or formatted for c3.js + + * ``begin=``, optional, format like ``2018-05-19T21:07:53`` + * ``end=``, optional, format like ``2018-05-19T21:07:53`` + * ``mode=``, optional. return all rows (default) or with lower resolution (for charts) + * ``format=``, optional. return result as returned by sqlalchemy (default) or formatted for c3.js """ result = sensordata(sensor_type=sensor_type) return jsonify(result) @@ -356,18 +324,17 @@ def currentwater(version): return jsonify({"value": value, "timestamp": timestamp}) -@app.route('/report//') +@app.route('/report//') def report(year, month): - """Report for given year and month + """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 = add_month(begin) + 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} @@ -404,8 +371,6 @@ def report(year, month): 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: @@ -413,26 +378,17 @@ def report(year, month): 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): + if len(x) == 0: cell = 'N/A' else: - value = y[closest_index] - cell = '{:.1f}'.format(value) + 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) @@ -458,6 +414,8 @@ def report(year, month): 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', @@ -466,4 +424,6 @@ def index(): watertime=watertime, airvalue=airvalue, airtime=airtime, + this_month=this_month, + last_month=last_month )