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main.py
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main.py
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# -*- coding: utf-8 -*-
# ---------------------------------------- Imports FLASK and some utilities -----------------------------------------------------
from flask import request, Flask, redirect, url_for, render_template, session, Response
from flask_login import LoginManager
from flask_login import login_user, login_required, logout_user, UserMixin
from passlib.hash import sha256_crypt
import datetime
from datetime import date
from pytz import timezone
import gspread
from googleapiclient.discovery import build
from googleapiclient.http import MediaIoBaseDownload
#from google.cloud import tasks_v2
from google.oauth2 import service_account
from google.cloud import ndb
import requests
import json
import mailjet_rest
#MAILJET_API_KEY = os.environ['MAILJET_API_KEY']
#MAILJET_API_SECRET = os.environ['MAILJET_API_SECRET']
#MAILJET_SENDER = os.environ['MAILJET_SENDER']
MAILJET_API_KEY = "no"
MAILJET_API_SECRET = "3"
MAILJET_SENDER = "to"
# spreadsheet credentials
skey_location = "online-library-app-43816975ead2.json"
scredentials = service_account.Credentials.from_service_account_file(skey_location)
# build a cloud datastore client using those spreadsheet credentials
ndbclient = ndb.Client(project="online-library-app", credentials=scredentials)
# set the scopes for the spreadsheet interactions, and create a spreadsheet client
sheetscopes = ['https://www.googleapis.com/auth/spreadsheets', 'https://www.googleapis.com/auth/drive']
spreadsheet_credentials = service_account.Credentials.from_service_account_file(
skey_location,
scopes = sheetscopes
)
spreadsheet_client = gspread.authorize(spreadsheet_credentials)
# build a task Client for cloud tasks (currently unused)
#task_client = tasks_v2.CloudTasksClient()
# set the key location and scopes for drive interactions, and create a drive client
dkey_location = "online-library-app-ff559ec5ab97.json"
dcredentials = service_account.Credentials.from_service_account_file(dkey_location)
drivescopes = ['https://www.googleapis.com/auth/spreadsheets.readonly', 'https://www.googleapis.com/auth/drive']
drive_credentials = service_account.Credentials.from_service_account_file(
dkey_location,
scopes = drivescopes
)
drive = build('drive', 'v3', credentials=drive_credentials)
# ---------------------------------------- Flask setup ---------------------------------------------------------------
app = Flask(__name__, static_folder='static')
app.secret_key = b'_5#y2L"F4Q8z\n\xec]/'
login_manager = LoginManager()
login_manager.login_view = 'index'
login_manager.init_app(app)
@login_manager.user_loader
def load_user(user_id):
# since the user_id is just the primary key of our user table, use it in the query for the user
with ndbclient.context():
try:
query = secureAccount.query().filter(ndb.IntegerProperty("id") == int(user_id))
for key in query.iter(keys_only=True):
entity = key.get()
return entity
except:
pass
# ----------------- General variables ------------------------------------------------
months = ["January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"]
oBragaExpected = 44805
# ----------------- google datastore storage-related functions and classes ------------------------
class secureAccount(UserMixin, ndb.Model):
id = ndb.IntegerProperty()
username = ndb.StringProperty()
password = ndb.StringProperty()
client = ndb.StringProperty()
def create_secure_account(username, password, c):
one = secureAccount(
username = username,
password = sha256_crypt.encrypt(password),
client = c)
one.put()
class ranchReportPreferences(ndb.Model):
email = ndb.StringProperty()
asked = ndb.BooleanProperty()
currentPastLost = ndb.BooleanProperty()
lossTrend = ndb.BooleanProperty()
fiveBestPerforming = ndb.BooleanProperty()
fiveWorstPerforming = ndb.BooleanProperty()
stressHealthData = ndb.BooleanProperty()
activitiesData = ndb.BooleanProperty()
anythingElse = ndb.StringProperty()
def create_ranch_report_preferences(e):
one = ranchReportPreferences(
id = e,
email = e,
asked = True,
currentPastLost = True,
lossTrend = True,
fiveBestPerforming = False,
fiveWorstPerforming = False,
stressHealthData = False,
activitiesData = False,
anythingElse = "")
one.put()
class lossTrend(ndb.Model):
loss_trend = ndb.StringProperty()
class viewPreferences(ndb.Model):
expectedCountW = ndb.BooleanProperty()
actualCountW = ndb.BooleanProperty()
totalCurrentLossW = ndb.BooleanProperty()
flyoverNotesW = ndb.BooleanProperty()
lossTrendW = ndb.BooleanProperty()
lossOverTimeW = ndb.BooleanProperty()
topFiveW = ndb.BooleanProperty()
contributingActivitiesW = ndb.BooleanProperty()
contributingActivitiesChartW = ndb.BooleanProperty()
eventsPieChartW = ndb.BooleanProperty()
eventsChartW = ndb.BooleanProperty()
eventsOverTimeW = ndb.BooleanProperty()
ndviAverageW = ndb.BooleanProperty()
ndviAverageByEventW = ndb.BooleanProperty()
ndviAveragePerDateW = ndb.BooleanProperty()
ndviChangeW = ndb.BooleanProperty()
ndviOverTimeW = ndb.BooleanProperty()
def create_view_preferences(e):
one = viewPreferences(
id = e,
expectedCountW = False,
actualCountW = False,
totalCurrentLossW = True,
flyoverNotesW = False,
lossTrendW = True,
lossOverTimeW = True,
topFiveW = False,
contributingActivitiesW = False,
contributingActivitiesChartW = False,
eventsPieChartW = True,
eventsChartW = True,
eventsOverTimeW = False,
ndviAverageW = False,
ndviAverageByEventW = True,
ndviAveragePerDateW = True,
ndviChangeW = False,
ndviOverTimeW = False)
one.put()
class secureAdminAccount(UserMixin, ndb.Model):
id = ndb.IntegerProperty()
username = ndb.StringProperty()
password = ndb.StringProperty()
def create_secure_admin_account(username, password):
one = secureAdminAccount(
username = username,
password = sha256_crypt.encrypt(password))
one.put()
class chartImages(ndb.Model):
client = ndb.StringProperty()
eventsPieChart = ndb.TextProperty(indexed=False)
class comparisonCard(ndb.Model):
client = ndb.StringProperty()
title = ndb.StringProperty()
text = ndb.StringProperty()
def create_new_comparison_card(client, title, text):
one = comparisonCard(
id = client + text,
client = client,
title = title,
text = text)
one.put()
class customerData(ndb.Model):
Customer = ndb.StringProperty()
DateFlown = ndb.DateProperty()
RanchBlock = ndb.StringProperty()
Sublot = ndb.StringProperty()
BlockSublotConcat = ndb.StringProperty()
LotSize = ndb.FloatProperty()
Crop = ndb.StringProperty()
AcresFlown = ndb.FloatProperty()
PlantingMethod = ndb.StringProperty()
WetDate = ndb.DateProperty()
HarvestDate = ndb.DateProperty()
Test = ndb.StringProperty()
Event = ndb.StringProperty()
NDVIScore = ndb.FloatProperty()
NDVIChange = ndb.FloatProperty()
NDVIPercentChange = ndb.FloatProperty()
Count = ndb.IntegerProperty()
LossToDate = ndb.IntegerProperty()
CropLossSinceLastCount = ndb.IntegerProperty()
LossAsPercent = ndb.FloatProperty()
GbsProcessed = ndb.FloatProperty()
Notes = ndb.StringProperty()
def create_customer_data(cu, df, rb, sl, bsc, ls, cr, af, pm, wd, hd, te, ev, ns, nc, np, co, ltd, clsl, lap, gb, no):
one = customerData(
id = cu + bsc + te + str(ns) + str(co),
Customer = cu,
DateFlown = df,
RanchBlock = rb,
Sublot = sl,
BlockSublotConcat = bsc,
LotSize = ls,
Crop = cr,
AcresFlown = af,
PlantingMethod = pm,
WetDate = wd,
HarvestDate = hd,
Test = te,
Event = ev,
NDVIScore = ns,
NDVIChange = nc,
NDVIPercentChange = np,
Count = co,
LossToDate = ltd,
CropLossSinceLastCount = clsl,
LossAsPercent = lap,
GbsProcessed = gb,
Notes = no)
one.put()
class userDefinedEvent(ndb.Model):
client = ndb.StringProperty()
event = ndb.StringProperty()
percent = ndb.FloatProperty()
def create_user_defined_event(c, e, p):
one = userDefinedEvent(
id = c + e + str(p),
client = c,
event = e,
percent = float(p))
one.put()
class emailNotification(ndb.Model):
client = ndb.StringProperty()
email = ndb.StringProperty()
ranches = ndb.StringProperty()
def create_email_notification(c, e, r):
one = emailNotification(
id = c + e + r,
client = c,
email = e,
ranches = r)
one.put()
class emailAlert(ndb.Model):
client = ndb.StringProperty()
email = ndb.StringProperty()
ranches = ndb.StringProperty()
conditions = ndb.StringProperty()
sent = ndb.StringProperty(repeated=True)
def create_email_alert(c, e, r, co):
one = emailAlert(
id = c + e + r,
client = c,
email = e,
ranches = r,
conditions = co)
one.put()
class lastUpdated(ndb.Model):
date = ndb.StringProperty()
def create_last_updated(client, date):
one = lastUpdated(
id = client,
date = date)
one.put()
class cropsSaved(ndb.Model):
saved = ndb.IntegerProperty()
class acresFlown(ndb.Model):
acres_flown = ndb.FloatProperty()
class linkedInPost(ndb.Model):
content = ndb.StringProperty()
def create_linkedin_post(c):
one = linkedInPost(
id = "rcole",
content = c)
one.put()
class targetLossPercent(ndb.Model):
client = ndb.StringProperty()
event = ndb.StringProperty()
target_percent = ndb.FloatProperty()
def create_target_loss_percent(c, e, t):
one = targetLossPercent(
id = c + e,
client = c,
event = e,
target_percent = t)
one.put()
class loginRecord(ndb.Model):
login_record = ndb.StringProperty(repeated=True)
def create_login_record(login_info):
one = loginRecord(
id = "login",
login_record = login_info)
one.put()
# ----------------- Mailjet function --------------------------------------------
def send_email(name, email, organization, role_title, size, location, checks):
client = mailjet_rest.Client(
auth=(MAILJET_API_KEY, MAILJET_API_SECRET), version='v3.1')
checksList = ""
for c in range(0, len(checks)):
checksList += checks[c] + ", "
checksList = checksList[0:len(checksList)-2]
body = "<p>" + name + ", with the email address " + email + " who works for " + organization + " (a company with " + size + " acres in " + location + ") in the role of " + role_title + " sent an inquiry from the Agxactly website. They are interested in monitoring the following items:<br><br>" + checksList
data = {
'Messages': [{
"From": {
"Email": MAILJET_SENDER,
"Name": name
},
"To": [
{
"Email": "r"
},
{
"Email": "tg"
}
],
"Subject": "Inquiry from Agxactly website",
"TextPart": body,
"HTMLPart": body
}]
}
client.send.create(data=data)
# Now, we send an email to the person who inquired, saying 'Your email has been sent!'
body_two = "<p>Thank you for your request! A team member will reach out to you within 24hrs to set up an introductory call and to get you started!</p>"
data_two = {
'Messages': [{
"From": {
"Email": MAILJET_SENDER,
"Name": "Agxactly auto-reply"
},
"To": [
{
"Email": email
}
],
"Subject": "Contact request from the Agxactly website received!",
"TextPart": body_two,
"HTMLPart": body_two
}]
}
client.send.create(data=data_two)
def send_ranch_report_customization_request(username, checks, additional):
client = mailjet_rest.Client(
auth=(MAILJET_API_KEY, MAILJET_API_SECRET), version='v3.1')
checksList = ""
for c in range(0, len(checks)):
checksList += checks[c] + ", "
checksList = checksList[0:len(checksList)-2]
body = "<p>" + username + " has asked that their ranch report be customized. They now want to include:<br><br>" + checksList + "<br>Additional requests:<br>" + additional
data = {
'Messages': [{
"From": {
"Email": MAILJET_SENDER,
"Name": "RanchReportCustomizationAlert"
},
"To": [
{
"Email": "r"
},
{
"Email": "t"
}
],
"Subject": "Ranch Report Customization Request",
"TextPart": body,
"HTMLPart": body
}]
}
client.send.create(data=data)
def send_entry(guess, email, details):
client = mailjet_rest.Client(
auth=(MAILJET_API_KEY, MAILJET_API_SECRET), version='v3.1')
if (details == ""):
body = "<p>Someone (not in the ag industry), with the email address " + email + " just tried to guess the number of crops in the video. \
<p>Their guess is <b>" + str(guess) + "</b>."
else:
body = "<p>A person who is in the ag industry, with the email address " + email + " just tried to guess the number of crops in the video. \
<p>Their guess is <b>" + str(guess) + "</b>, and here are their job details. \
<p>" + details
data = {
'Messages': [{
"From": {
"Email": MAILJET_SENDER,
"Name": "Contest Guess"
},
"To": [
{
"Email": "r"
},
{
"Email": "t"
}
],
"Subject": "Count the crops contest guess",
"TextPart": body,
"HTMLPart": body
}]
}
client.send.create(data=data)
def send_notification(email, name, subject, body):
client = mailjet_rest.Client(
auth=(MAILJET_API_KEY, MAILJET_API_SECRET), version='v3.1')
data = "{\"Messages\": [{ \"From\": {\"Email\": \"" + MAILJET_SENDER + "\", \"Name\": \"" + name + "\"},\"To\": [ "
for m in range(0, len(email)-1):
thisEmail = "{\"Email\": \"" + email[m] + "\"},"
#If this is a ranch report email (which it might not be, hence the try-catch statement)
#we have to set the "ask" boolean to true in the ranchReportPreferences entity in the database,
#so that next time the user logs in, they will be asked if the report suited their preferences
with ndbclient.context():
try:
entity = ndb.Key(ranchReportPreferences, email[m]).get()
entity.asked = False
entity.put()
except:
pass
data = data + thisEmail
data = data[0:len(data)-1]
data = data + " ], \"Subject\": \"" + subject + "\",\"TextPart\": \"" + body + "\",\"HTMLPart\": \"" + body + "\" }] }"
client.send.create(data=json.loads(data))
return json.loads(data)
@app.route("/emailComparison", methods=['GET', 'POST'])
def emailComparison():
# We're actually just going to create a good email body here, then send it
# to the function above (send_notification) to actually be sent
if request.method == "POST":
event = request.form['event']
details = request.form['details']
date = request.form['date']
lossOrGain = request.form['lossOrGain']
address = request.form['address']
posOrNeg = request.form['posOrNeg']
if posOrNeg == "positive":
fluffyBody = "<h2>A method was changed, and a change in crop loss resulted</h2> \
<p>Regarding " + event + ", a change in methodology was enacted on " + date + ", which resulted \
in a <span style='color:green'><b>" + lossOrGain + "% decrease in crop loss</b></span>. The details of the change are below. \
<p>" + details
else:
fluffyBody = "<h2>A method was changed, and a change in crop loss resulted</h2> \
<p>Regarding " + event + ", a change in methodology was enacted on " + date + ", which resulted \
in a <span style='color:red'><b>" + lossOrGain + "% increase in crop loss</b></span>. The details of the change are below. \
<p>" + details
addresses = []
addresses.append(address)
addresses.append("this needs to be appended because usually the email string contains a dash at the end -")
email = send_notification(addresses, "Agxactly Comparison Forwarding Service", "A method-change comparison result from Agxactly", fluffyBody)
return email#('', 204)
# ----------------- general functions for working with data ------------------------
def toDateTime(dmyyyy):
chunks = dmyyyy.split("/")
return datetime.date(int(chunks[2]), int(chunks[0]), int(chunks[1]))
def fromDateTime(dt):
return "new Date(" + str(dt.year) + "," + str(dt.month-1) + "," + str(dt.day) + ")"
def dateTimeToString(dt):
return str(dt.month) + "/" + str(dt.day) + "/" + str(dt.year)
def trimFinalChar(string):
if len(string) == 0:
return string
if string[len(string)-1] == ",":
return string[0:len(string)-1]
else:
return string
def weird_division(n, d):
return n / d if d else 0
def updateDictionaryByAddition(value, dictionary, value_to_add):
v = 0
if value in dictionary:
v = dictionary[value]
v = v + value_to_add
dictionary.update({value: v})
else:
dictionary.update({value: value_to_add})
return dictionary
def getUserDefinedEventNames(client):
usersEvents = []
with ndbclient.context():
# Here we get all the user-defined events
query = userDefinedEvent.query().filter(ndb.StringProperty("client") == client)
for key in query.iter(keys_only=True):
entity = key.get()
usersEvents.append(entity.event)
return usersEvents
def getUserDefinedEventPercent(client, event):
with ndbclient.context():
# Here we get all the user-defined events
query = userDefinedEvent.query().filter(ndb.StringProperty("client") == client).filter(ndb.StringProperty("event") == event)
for key in query.iter(keys_only=True):
entity = key.get()
return entity.percent
def adjustForFictitiousEvents(client, _TotalCropsLostForPerEventCalculation, eventTotals, events):
# We have to loop through all the custom events that the customer wants to assign,
# and get the percent loss associated with each fictitious event.
fictitiousEvents = getUserDefinedEventNames(client)
totalToSubtractFromRealEvents = 0
for fe in fictitiousEvents:
# we get the fictitious loss associated with that event
thisFictitiousLossPercent = getUserDefinedEventPercent(client, fe)
# then turn it into a concrete number, based on the total crops lost
thisFictitiousLossNumber = int((thisFictitiousLossPercent/100) * _TotalCropsLostForPerEventCalculation)
# we put that number into the event totals list
eventTotals[events.index(fe)] = thisFictitiousLossNumber
# and add it to a variable which will keep track of the total number of crops
# fictitiously lost, which we can then divide and subtract equally from each true loss
totalToSubtractFromRealEvents += thisFictitiousLossNumber
# Then, we take that total number from each real event, in a distributed fashion
totalTaken = 0
while totalTaken < totalToSubtractFromRealEvents:
for realEvent in range(0, 7):
if eventTotals[realEvent] > 0:
eventTotals[realEvent] -= 1
totalTaken += 1
return eventTotals, events
def sentAlready(thisString, alreadySent):
if (thisString in alreadySent):
return True
return False
def buildRateOfLineChart(dictionary):
rateOfLossChartData = ""
for line in dictionary.items():
rbs = line[0]
dataPointNumbers = line[1]
# First, we'll construct everything before the dataPoints field
rateOfLossChartData = rateOfLossChartData + \
"{ \
type: 'line', \
axisYType: 'secondary', \
name: '" + rbs + "', \
showInLegend: true, \
markerSize: 0, \
yValueFormatString: '##.##', \
dataPoints: ["
# Now, let's construct the datapoints
theseDataPoints = ""
for x in range(0, len(dataPointNumbers)):
theseDataPoints = theseDataPoints + \
"{ x: " + str(x) + ", y: " + str(dataPointNumbers[x]) + "},"
theseDataPoints = trimFinalChar(theseDataPoints) + "]"
# And add the datapoints to the chart data
rateOfLossChartData = rateOfLossChartData + theseDataPoints
# And finally put a cap on the chunk
rateOfLossChartData = rateOfLossChartData + "},"
return trimFinalChar(rateOfLossChartData)
def swapRanchNames(name):
Braga = ["Braga", "Ryan", "Eade", "Brandt", "Moranda", "Gularte", "Martin", "Manzoni", "Vinyard", "Sargenti", "Grisetti", "Vineyard", "Home"]
Betterworld = ["Brottler", "Riana", "Eadeson", "Brandon", "Morranetti", "Guliani", "Martinson", "Manfield", "Vinson", "Southfield", "Gillasetti", "Voorhies", "Homefield"]
for b in range(0, len(Braga)):
if Braga[b] in name:
return name.replace(Braga[b], Betterworld[b])
return name
# ----------------- Here are all the functions which get and process the data for the dashboard ---------
def getEntitiesAndRanchesToView(client, startDate, endDate, ranchesToView, whichOrder, historicalDataChecked):
# Variables for the UI
_Ranches = []
# We're going to make a list of dictionaries,
# each dictionary being an entity.
# Here is the list we'll be putting them into
allEntities = []
with ndbclient.context():
# Here we get all the data from the entities
# If 'onlyShowCurrentlyPlanted' is set to True, we skip entites where the harvest date is before today
if historicalDataChecked == False:
query = customerData.query().filter(ndb.DateProperty("HarvestDate") >= date.today())
else:
query = customerData.query().filter(ndb.DateProperty("DateFlown") >= startDate).filter(ndb.DateProperty("DateFlown") <= endDate)
if whichOrder == "DateFlown":
query.order(customerData.DateFlown)
else:
query.order(customerData.WetDate)
for key in query.iter(keys_only=True):
entity = key.get()
if entity.Customer != client:
continue
if entity.DateFlown <= startDate or entity.DateFlown >= endDate:
continue
# # If 'onlyShowCurrentlyPlanted' is set to True, we skip entites where the harvest date is before today
# if onlyShowCurrentlyPlanted == True:
# if entity.HarvestDate < date.today():
# continue
# Get the ranches for the dropdown in the UI
if entity.BlockSublotConcat not in _Ranches:
_Ranches.append(entity.BlockSublotConcat)
if "All" not in ranchesToView:
if entity.BlockSublotConcat not in ranchesToView:
continue
# Let's put all the bits of data into a dictionary, to make it all easier to keep track of
entityDict = dict({})
entityDict.update({'DateFlown': entity.DateFlown})
entityDict.update({'RanchBlock': entity.RanchBlock})
entityDict.update({'Sublot': entity.Sublot})
entityDict.update({'BlockSublotConcat': entity.BlockSublotConcat})
entityDict.update({'LotSize': entity.LotSize})
entityDict.update({'Crop': entity.Crop})
entityDict.update({'AcresFlown': entity.AcresFlown})
entityDict.update({'PlantingMethod': entity.PlantingMethod})
entityDict.update({'WetDate': entity.WetDate})
entityDict.update({'HarvestDate': entity.HarvestDate})
entityDict.update({'Test': entity.Test})
entityDict.update({'Event': entity.Event})
entityDict.update({'NDVIScore': entity.NDVIScore})
entityDict.update({'NDVIChange': entity.NDVIChange})
entityDict.update({'NDVIPercentChange': entity.NDVIPercentChange})
entityDict.update({'Count': entity.Count})
entityDict.update({'LossToDate': entity.LossToDate})
entityDict.update({'CropLossSinceLastCount': entity.CropLossSinceLastCount})
entityDict.update({'LossAsPercent': entity.LossAsPercent})
entityDict.update({'GbsProcessed': entity.GbsProcessed})
entityDict.update({'Notes': entity.Notes})
allEntities.append(entityDict)
_Ranches.sort()
return allEntities, _Ranches
def getNotes(allEntities, client):
notes = ""
for entity in allEntities:
try:
if len(entity['Notes']) > 0:
notes = notes + "<b>Note regarding " + entity['RanchBlock'] + " " + entity['Sublot'] + " on " + dateTimeToString(entity['DateFlown']) + "</b><br>" + entity['Notes'] + "<br><br>"
except:
print("no note")
return notes
def getCountData(allEntities, client):
# Variables for the 'Count' Tab
_LandAcres = 0.0
_AcresFlown = 0.0
_AlreadyInAcresCount = []
_LatestCropCount = 0
CropCounts = dict([])
_CropsLost = 0
_TotalCropsLostForPerEventCalculation = 0
_PercentMissing = 0.0
_CountTabMainTablePackage = []
_PackagedEventPercents = []
events = ["Cultivation", "Planting", "Roboweeder", "Sidedress", "Weather", "Disease", "Weeding"]
eventTotals = [0, 0, 0, 0, 0, 0, 0]
_CropsLostPerDateFlownAndEvent = ["", "", "", "", "", "", ""]
chartEvents = ["Cultivation", "Planting", "Roboweeder", "Sidedress", "Weather", "Disease", "Weeding"]
# The user can now enter custom events and assign percents loss to those events
# Here, we have to check if they have any custom events registered, and
# alter the length / contents of the events lists accordingly
for ce in getUserDefinedEventNames(client):
events.append(ce)
eventTotals.append(0)
for event in range(0, len(_CropsLostPerDateFlownAndEvent)):
_CropsLostPerDateFlownAndEvent[event] = _CropsLostPerDateFlownAndEvent[event] + "{type: 'stackedColumn',name:'" + chartEvents[event] + "',showInLegend: true,dataPoints: ["
_TopFiveRanchCropsLost = ""
_TopFiveRanchCropsLostAsPercentOfTotal = ""
_BottomFiveRanchCropsLost = ""
_BottomFiveRanchCropsLostAsPercentOfTotal = ""
topFives = dict([])
topFivesAsPercent = dict([])
alreadySeenThisSublot = []
for entity in allEntities:
if entity['Test'] == "Count" and entity['Count'] > 0:
# Here we get all the data that will go into the 'Count' Tab main table
_CountTabMainTablePackage.append(entity['DateFlown'])
_CountTabMainTablePackage.append(entity['RanchBlock'])
_CountTabMainTablePackage.append(entity['Sublot'])
_CountTabMainTablePackage.append(entity['LotSize'])
_CountTabMainTablePackage.append(entity['WetDate'])
_CountTabMainTablePackage.append(entity['HarvestDate'])
_CountTabMainTablePackage.append(entity['Event'])
_CountTabMainTablePackage.append('{:,}'.format(entity['Count']))
_CountTabMainTablePackage.append('{:,}'.format(entity['LossToDate']))
_CountTabMainTablePackage.append('{:,}'.format(entity['CropLossSinceLastCount']))
_CountTabMainTablePackage.append(entity['LossAsPercent'])
_TotalCropsLostForPerEventCalculation += entity['CropLossSinceLastCount']
# Just realized as of mid-October that the "Latest Crop Count" and "Crops Lost" boxes
# on the Count tab need to tally ONLY the data from the most recent flyovers--in essence
# ignoring all but the most recent flyover data. This next few lines attempts to do just that.
# We put each entity Count and CropLossSinceLastCount in a dictionary.
# These dictionaries will automatically be updated with the latest data as we go through the loop
# here. Later on, we will sum the values in the dictionaries to ge the totals.
CropCounts.update({entity['BlockSublotConcat']: entity['Count']})
_AcresFlown += entity['AcresFlown']
# And the data that will go into the 'Count' tab stat cards
if (entity['BlockSublotConcat'] not in _AlreadyInAcresCount):
_LandAcres += entity['LotSize']
_AlreadyInAcresCount.append(entity['BlockSublotConcat'])
# We also have to which events led to how much crop loss each, so we
# associate the crop losses with certain events here
if entity['Event'] in events:
eventTotals[events.index(entity['Event'])] += entity['CropLossSinceLastCount']
# This is for the 'Crops lost per date flown and event' line chart at the bottom of
# the 'Count' Tab. It makes line coordinate data to be used in the line chart
for event in range(0, len(_CropsLostPerDateFlownAndEvent)):
if entity['Event'] == chartEvents[event]:
_CropsLostPerDateFlownAndEvent[event] = _CropsLostPerDateFlownAndEvent[event] + "{x: " + fromDateTime(entity['DateFlown']) + ", y: " + str(entity['CropLossSinceLastCount']) + "},"
else:
_CropsLostPerDateFlownAndEvent[event] = _CropsLostPerDateFlownAndEvent[event] + "{x: " + fromDateTime(entity['DateFlown']) + ", y: 0},"
# This is for the 'Top 5 Ranch crops lost' table in the 'Count' Tab.
# It associates crop loss numbers with particular ranches and sublots.
topFives = updateDictionaryByAddition(entity['RanchBlock'], topFives, entity['CropLossSinceLastCount'])
# This is for the 'Top 5 Ranch crops lost as percent of total' table in the "Count" Tab.
# It tracks how many crops should be in each ranch/block
# Here, we remove the suffix A, B, C, D or E from the Ranch/block sublot
# UPDATE! -- The sublots now sometimes have _(1) on the end, or something, to denote re-plants
# so this part of the program had to be re-written (2020/12/29)
if ("_(" in entity['BlockSublotConcat']):
rbs = entity['BlockSublotConcat'][0:len(entity['BlockSublotConcat'])-5]
else:
rbs = entity['BlockSublotConcat'][0:len(entity['BlockSublotConcat'])-1]
if entity['BlockSublotConcat'] not in alreadySeenThisSublot:
topFivesAsPercent = updateDictionaryByAddition(rbs, topFivesAsPercent, (entity['LotSize'] * oBragaExpected))
alreadySeenThisSublot.append(entity['BlockSublotConcat'])
# Now, the entity-reading loop is over, so we just sort and
# package the data that we now have...
# Let's get the latest crop count and crop losses from those dictionaries we made
for k, v in CropCounts.items():
_LatestCropCount += v
_ExpectedCrops = int(oBragaExpected * _LandAcres)
_CropsLost = _ExpectedCrops - _LatestCropCount
# In our "topFivesAsPercent" dictionary, we currently have {ranchblock: total crops that should be there} for
# all existing ranch blocks. Here, we have to make a dictionary of percent losses, using this
# dictionary as well as the topFives dictionary (which contains the total number of crops lost for each ranchblock)
topFivesPercentized = dict({})
for r, c in topFivesAsPercent.items():
topFivesPercentized.update({r: (weird_division(topFives[r] ,c))*100})
# The 'Count' Tab needs a bar chart of the
# top-five crop-losing ranches (and bottom five). This bit of the program makes the bar chart data
# for those bar charts.
realTops = [0, 0, 0, 0, 0]
realBottoms = [0, 0, 0, 0, 0]
for r, c in topFives.items():
realTops.append(c)
realBottoms.append(c)
realTops.sort(reverse=True)
realBottoms.sort(reverse=False)
realBottomsNoZeros = [i for i in realBottoms if i != 0]
realTopsForPercentized = [0, 0, 0, 0, 0]
realBottomsForPercentized = [0.0, 0.0, 0.0, 0.0, 0.0]
for r, c in topFivesPercentized.items():
realTopsForPercentized.append(c)
realBottomsForPercentized.append(c)
realTopsForPercentized.sort(reverse=True)
realBottomsForPercentized.sort(reverse=False)
realBottomsForPercentizedNoZeros = [i for i in realBottomsForPercentized if i != 0]
# The 'Count' Tab also needs a bar chart of the top-five (and bottom five)
# crop-losing ranches adjusted for size, where the crops lost are not shown as numbers,
# but as a percent of what should be there, based on the lot size
for r, c in topFives.items():
if c >= realTops[4] and c > 0:
_TopFiveRanchCropsLost = _TopFiveRanchCropsLost + "{y: " + str(c) + ", label: '" + r + "'},"
_TopFiveRanchCropsLost = trimFinalChar(_TopFiveRanchCropsLost)
realBottomForComparison = 0
if len(realBottomsNoZeros) >= 5:
realBottomForComparison = realBottomsNoZeros[4]
elif len(realBottomsNoZeros) > 0:
realBottomForComparison = realBottomsNoZeros[len(realBottomsNoZeros)-1]
for r, c in topFives.items():
if c <= realBottomForComparison and c > 0:
_BottomFiveRanchCropsLost = _BottomFiveRanchCropsLost + "{y: " + str(c) + ", label: '" + r + "'},"
_BottomFiveRanchCropsLost = trimFinalChar(_BottomFiveRanchCropsLost)
for r, c in topFivesPercentized.items():
if c >= realTopsForPercentized[4] and c > 0:
_TopFiveRanchCropsLostAsPercentOfTotal = _TopFiveRanchCropsLostAsPercentOfTotal + "{y: " + str(round(c, 2)) + ", label: '" + r + "'},"
_TopFiveRanchCropsLostAsPercentOfTotal = trimFinalChar(_TopFiveRanchCropsLostAsPercentOfTotal)
realBottomPercentizedForComparison = 0
if len(realBottomsForPercentizedNoZeros) >= 5:
realBottomPercentizedForComparison = realBottomsForPercentizedNoZeros[4]
elif len(realBottomsForPercentizedNoZeros) > 0:
realBottomPercentizedForComparison = realBottomsForPercentizedNoZeros[len(realBottomsForPercentizedNoZeros)-1]
for r, c in topFivesPercentized.items():
if c <= realBottomPercentizedForComparison and c > 0:
_BottomFiveRanchCropsLostAsPercentOfTotal = _BottomFiveRanchCropsLostAsPercentOfTotal + "{y: " + str(round(c, 2)) + ", label: '" + r + "'},"
_BottomFiveRanchCropsLostAsPercentOfTotal = trimFinalChar(_BottomFiveRanchCropsLostAsPercentOfTotal)
_PercentMissing = round((weird_division(float(_CropsLost), float(_ExpectedCrops)) * 100), 2)
for event in range(0, len(_CropsLostPerDateFlownAndEvent)):
if (event < len(_CropsLostPerDateFlownAndEvent)-1):
_CropsLostPerDateFlownAndEvent[event] = trimFinalChar(_CropsLostPerDateFlownAndEvent[event]) + "]},"
else:
_CropsLostPerDateFlownAndEvent[event] = trimFinalChar(_CropsLostPerDateFlownAndEvent[event]) + "]}"
CropsLostPerDateFlownAndEventString = ""
for event in range(0, len(_CropsLostPerDateFlownAndEvent)):
CropsLostPerDateFlownAndEventString = CropsLostPerDateFlownAndEventString + _CropsLostPerDateFlownAndEvent[event]
# Put fictitious data into the events and event totals lists
eventTotals, events = adjustForFictitiousEvents(client, _TotalCropsLostForPerEventCalculation, eventTotals, events)
# Then sort them
eventTotals, events = (list(x) for x in zip(*sorted(zip(eventTotals, events), reverse=True)))
for e in range(0, len(eventTotals)):
if _CropsLost == 0:
thisPercent = 0.0
else:
thisPercent = round((weird_division(float(eventTotals[e]), float(_TotalCropsLostForPerEventCalculation)) * 100), 2)
_PackagedEventPercents.append(events[e])
_PackagedEventPercents.append(thisPercent)
_LandAcres = round(_LandAcres, 2)
_AcresFlown = round(_AcresFlown, 2)
#'{:,}'.format(_AcresFlown), \
return '{:,}'.format(_LandAcres), \
_AcresFlown, \
'{:,}'.format(_ExpectedCrops), \
'{:,}'.format(_LatestCropCount), \
'{:,}'.format(_CropsLost), \
_PercentMissing, \
_PackagedEventPercents, \
_CountTabMainTablePackage, \
CropsLostPerDateFlownAndEventString, \
_TopFiveRanchCropsLost, \
_TopFiveRanchCropsLostAsPercentOfTotal, \
_BottomFiveRanchCropsLost, \
_BottomFiveRanchCropsLostAsPercentOfTotal, \
_CropsLost
def getRateOfChangeData(allEntities, client, whichChange):