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Author SHA1 Message Date
Patrick McDonagh
74019e4889 Completes #1. 
Updates README-local.md to include instructions and configuration for running locally
 2018-04-05 18:07:13 -05:00
Patrick McDonagh
a462070cf9 use packaged Meshify 2018-03-26 09:34:53 -05:00
Patrick McDonagh
fd68d4067f use meshify package, fix build function, add more device channel files 2018-03-23 18:51:10 -05:00
Patrick McDonagh
c388fa1f61 Local packages were missing 2018-03-14 17:16:00 -05:00
Patrick McDonagh
acf614f6c2 Adds LICENSE and reformats README.md 2018-03-14 17:07:31 -05:00
Patrick McDonagh
bf202dae5c Updates README.md and creates README-local.md 2018-03-14 17:02:14 -05:00
10 changed files with 492 additions and 350 deletions
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# POCloud Local Report Generators
Developed by Patrick McDonagh @patrickjmcd, Henry pump
## Setup
System variables must be set up for the script to run. Add the following lines to /etc/environment
```Shell
MESHIFY_USERNAME="<yourMeshifyUsername>"
MESHIFY_PASSWORD="<yourMeshifyPassword>"
```
### Setup a Virtual Environment and Install Python Modules
```Shell
python3 -m venv env # Creates the virtual environment in a folder ./env
source env/bin/activate # activates the virtual environment
pip install xlsxwriter requests tzlocal meshify # installs the python modules
```
### Preparing an S3 Bucket
This section will show you how to configure the S3 Bucket within AWS. It assumes a strong knowledge of AWS platforms.
1. Sign in to your AWS Console and open the S3 dashboard.
2. Create a bucket named "pocloud-email-reports". You may choose to name your bucket differently, but you must update the variable BUCKET_NAME within reports_s3_xlsx.py
3. Open the newly-created bucket and create 3 folders. These names cannot be changed without doing some serious hacking of the reports_s3_xlsx.py file.
- channel_config
- created_reports
- to_files
### Populating Channel Configs
Populating channel config files tells the Lambda function which devices to prepare reports for and which channels to include data from. **Devices will not be recognized unless they have both a Channel Config file and a To file.**
1. Prepare a file named devicetype_channels.json where "devicetype" is the Meshify name for the devicetype.
```touch <devicetype>_channels.json```
2. In the text editor of your choice, develop a JSON **list of objects** that contains properties "meshify_name" and "vanity_name".
```JSON
[
{
"meshify_name": "<channel name in meshify>",
"vanity_name": "<vanity name for report header>"
},
{
"meshify_name": "<another channel name in meshify>",
"vanity_name": "<another vanity name for report header>"
},
]
```
3. Upload this file to the "channel_config" folder in the S3 Bucket.
### Populating To Files
Populating To files tells the Lambda function which devices to prepare reports for and whom to send the reports for each company. **Devices will not be recognized unless they have both a Channel Config file and a To file.**
1. Prepare a file named devicetype_to.json where "devicetype" is the Meshify name for the devicetype.
```touch <devicetype>_to.json```
2. In the text editor of your choice, develop a JSON **object** that contains properties of the format below. CompanyA and CompanyB should be replaced by the full name of the company as recorded in Meshify.
```JSON
{
"CompanyA": [
"person@email.com",
"place@email.com"
],
"CompanyB": [
"person@email.com",
"thing@email.com"
]
}
```
3. Upload this file to the "to_files" folder in the S3 Bucket.
## Running the Script
As long as everything has been setup correctly, all it takes is running:
```Shell
python local_test.py
```
This performs a "dry-run" where it will generate the reports and print to the console the list of recipients, but it will not actually send the reports. The script can trigger the sending of reports by running:
```Shell
python local_test.py --send
```

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# POCloud Report Generators
# POCloud Email Report Generator
Developed by Patrick McDonagh @patrickjmcd, Henry pump
Send daily reports of Meshify Data via AWS functions.
## Setup
## Using the Generator
System variables must be set up for the script to run. Add the following lines to /etc/environment
```
SMTP_EMAIL="<yourSMTPemailAddress>"
SMTP_PASSWORD="<yourSMTPpassword>"
MESHIFY_USERNAME="<yourMeshifyUsername>"
MESHIFY_PASSWORD="<yourMeshifyPassword>"
```
Reports will be generated on a schedule by AWS Lambda, a serverless, event-driven computing platform. Each report will contain all devices of a specified type that the user has been granted access to in Meshify. If a user has access to multiple device types and is configured to receive reports for multiple device types, the user will receive one report for each device type. The Lambda function will mark in red any data that is more than 24 hours old in order to denote devices that have not updated. Values reported are the latest values at the time of report generation (12:00 GMT / 07:00 CST by default).
Create a "files" in the script's directory.
If you would like to run the reports locally without the AWS Lambda Function, refer to [README-local.md](README-local.md)
### Install Python Modules
## Setting it up yourself
```
pip install xlsxwriter
```
### Prerequisites
## Configuration Files
- Amazon Web Services account
- Sufficient knowledge of S3, Lambda, and SES within Amazon Web Services
- Python 3
The script relies heavily on configuration files based on the Meshify devicetype. To configure a device, create a file
named <devicetype>_channels.json file. The file should hold a JSON list.
### Preparing an S3 Bucket
### Example Configuration File
This section will show you how to configure the S3 Bucket within AWS. It assumes a strong knowledge of AWS platforms.
```
# testdevice_channels.json
1. Sign in to your AWS Console and open the S3 dashboard.
2. Create a bucket named "pocloud-email-reports". You may choose to name your bucket differently, but you must update the variable BUCKET_NAME within reports_s3_xlsx.py
3. Open the newly-created bucket and create 3 folders. These names cannot be changed without doing some serious hacking of the reports_s3_xlsx.py file.
- channel_config
- created_reports
- to_files
[
### Populating Channel Configs
Populating channel config files tells the Lambda function which devices to prepare reports for and which channels to include data from. **Devices will not be recognized unless they have both a Channel Config file and a To file.**
1. Prepare a file named devicetype_channels.json where "devicetype" is the Meshify name for the devicetype.
```touch <devicetype>_channels.json```
2. In the text editor of your choice, develop a JSON **list of objects** that contains properties "meshify_name" and "vanity_name".
```JSON
[
{
"meshify_name": "yesterday_volume",
"vanity_name": "Yesteday Volume"
"meshify_name": "<channel name in meshify>",
"vanity_name": "<vanity name for report header>"
},
{
"meshify_name": "volume_flow",
"vanity_name": "Flow Rate"
"meshify_name": "<another channel name in meshify>",
"vanity_name": "<another vanity name for report header>"
},
...
]
```
## Recipients File
]
```
In order to send emails containing the reports, configure a recipients json file named <devicetype>_to.json. The
file should hold a JSON object.
3. Upload this file to the "channel_config" folder in the S3 Bucket.
### Example Recipients File
### Populating To Files
```
# testdevice_to.json
Populating To files tells the Lambda function which devices to prepare reports for and whom to send the reports for each company. **Devices will not be recognized unless they have both a Channel Config file and a To file.**
{
"Company 1 Name": [
"email1@company.com",
"email2@company.com"
1. Prepare a file named devicetype_to.json where "devicetype" is the Meshify name for the devicetype.
```touch <devicetype>_to.json```
2. In the text editor of your choice, develop a JSON **object** that contains properties of the format below. CompanyA and CompanyB should be replaced by the full name of the company as recorded in Meshify.
```JSON
{
"CompanyA": [
"person@email.com",
"place@email.com"
],
"Company 2 Name": [
"email3@company2.com",
"email4@company2.com"
],
...
}
```
"CompanyB": [
"person@email.com",
"thing@email.com"
]
}
```
## Running the script
3. Upload this file to the "to_files" folder in the S3 Bucket.
```
usage: reports_xlsx.py [-h] [-s] [-p CONFIG_PATH] [-o OUTPUT_PATH] deviceType
### Preparing the Lambda function
positional arguments:
deviceType Meshify device type
1. Clone this repository and open it
optional arguments:
-h, --help show this help message and exit
-s, --send Send emails to everyone in the _to.json file
-c CONFIG_PATH, --config-path CONFIG_PATH
The folder path that holds the configuration files
-o OUTPUT_PATH, --output-path OUTPUT_PATH
The folder path that holds the output files
```
```Shell
git clone https://github.com/Henry-Pump/POCloud-Email-Reports.git
cd POCloud-Email-Reports
```
## Configuring the script to be run via crontab
2. Setup a Python Virtual environment and activate the environment
Open the crontab file with `crontab -e`.
```Shell
python3 -m venv env
source env/bin/activate
```
Add the following contents:
```
00 07 * * * /usr/bin/python3 /home/ubuntu/POCloud-Scraper/reports_xlsx.py advvfdipp --send --config-path /home/ubuntu/POCloud-Scraper --output-path /home/ubuntu/POCloud-Scraper/files
01 07 * * * /usr/bin/python3 /home/ubuntu/POCloud-Scraper/reports_xlsx.py ipp --send --config-path /home/ubuntu/POCloud-Scraper --output-path /home/ubuntu/POCloud-Scraper/files
02 07 * * * /usr/bin/python3 /home/ubuntu/POCloud-Scraper/reports_xlsx.py abbflow --send --config-path /home/ubuntu/POCloud-Scraper --output-path /home/ubuntu/POCloud-Scraper/files
```
3. Install necessary python packages in the virtual environment.
```Shell
pip install requests tzlocal xlsxwriter
```
# POCloud-Scraper
Scrape production data from POCloud to push to accounting servers
4. Create a folder for deploying the lambda function
## Setup
System variables must be set up for the script to run. Add the following lines to /etc/environment
```
HP_SQL_USER="<yourSQLusername>"
HP_SQL_PASSWORD="<yourSQLpassword>"
HP_SQL_SERVER="<yourSQLserverAddress>"
MESHIFY_USERNAME="<yourMeshifyUsername>"
MESHIFY_PASSWORD="<yourMeshifyPassword>"
```
```Shell
mkdir -p deploy```
## Usage
It is useful to run the script and store the output in a log file.
5. To build the lambda file automatically, allow execution permissions on the build script and execute it. To build manually, examine the [build_lambda.sh](https://github.com/Henry-Pump/POCloud-Email-Reports/blob/master/build_lambda.sh) file and execute commands at your own peril.
## Test Mode
The script has a test mode which will only retrieve the data. Test mode will not write date to the database.
```Shell
chmod +x build_lambda.sh
./build_lambda.sh
```
To run the script in test mode:
```
python3 henryPetroleumMeshifyAPI.pt True >> output.log
```
You should now have a file named lambda.zip in the main directory of the repo. This is the file to upload into your Lambda function.
## Normal Mode
In normal mode, the data will be grabbed from the Meshify API and inserted into the Production database.
### Creating the Lambda Function in AWS
To run the script:
```
python3 henryPetroleumMeshifyAPI.pt >> output.log
```
This section will show you how to configure the Lambda function within AWS. It assumes a strong knowledge of AWS platforms.
1. Sign in to your AWS Console and open the Lambda dashboard.
2. Click "Create function".
3. Select "Author from scratch" and fill in the info
- Name: give your function a name
- Runtime: select Python 3.6
- Role: either choose an existing role with S3, SES, and Lambda permissions or create one.
- Existing role: select the existing or created role name.
4. Click "Create Function".
5. In the function code section, set the following:
- Code entry type: "Upload a .ZIP file"
- Runtime: Python 3.6
- Handler: reports_s3_xlsx.lambda_handler
- Function package: upload the created lambda.zip
6. In Environment Variables, two variables are needed:
- MESHIFY_PASSWORD: your meshify password
- MESHIFY_USERNAME: your meshify username
7. Drag a CloudWatch Events trigger in the Designer to the trigger section of your function.
8. Configure a new CloudWatch event with the schedule expression:
```cron(0 12 * * ? *)```
This will schedule the event to be triggered at 12:00 PM GMT (7:00 AM CST) every day of the week.
9. Save and test your function.
## Contributors
- [Patrick McDonagh](@patrickjmcd) - Owner

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!#/bin/bash
env/bin/pip install boto3 tzlocal meshify requests
rm -f lambda.zip
mkdir -p deploy
cp env/lib/python3.6/site-packages/* deploy
cp meshify.py deploy
cp -R env/lib/python3.6/site-packages/* deploy
cp reports_s3_xlsx.py deploy
cd deploy
zip -r ../lambda.zip ./*
cd ..
echo "Lambda zip file built to ./lambda.zip"

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[
{
"meshify_name": "run_status",
"vanity_name": "Run Status"
},
{
"meshify_name": "bbl_total_yesterday",
"vanity_name": "BBL Total Yesterday"
},
{
"meshify_name": "bpd_flow",
"vanity_name": "BPD Flow Rate"
},
{
"meshify_name": "bbl_total_thismonth",
"vanity_name": "BBL Total This Month"
}
]

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channel_config/pondlevel_channels.json Normal file
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[
{
"meshify_name": "pond_level",
"vanity_name": "Pond Level"
},
{
"meshify_name": "pond_volume",
"vanity_name": "Pond Volume"
}
]

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[
{
"meshify_name": "totalizer_1_yesterday",
"vanity_name": "Total Yesterday"
},
{
"meshify_name": "totalizer_1_units",
"vanity_name": "Totalizer Units"
},
{
"meshify_name": "volume_flow",
"vanity_name": "Flow Rate"
},
{
"meshify_name": "volume_flow_units",
"vanity_name": "Flow Rate Units"
}
]

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"""Run a test of the lambda function locally."""
import argparse
from reports_s3_xlsx import get_s3_device_types, read_s3_tofiles, read_s3_device_config, prep_emails, send_ses_email
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-s', '--send', action='store_true', help="Actually send the emails.")
args = parser.parse_args()
SEND_EMAIL = args.send
device_type_list = get_s3_device_types()
to_lists = list(map(lambda x: read_s3_tofiles(x), device_type_list))
channel_configs = list(map(lambda x: read_s3_device_config(x), device_type_list))
for i in range(0, len(device_type_list)):
emails = prep_emails(device_type_list[i], channel_configs[i], to_lists[i])
for email in emails:
if SEND_EMAIL:
send_ses_email(email)
print("Sent email for {} to {}".format(device_type_list[i], email['To']))
else:
print("Would have sent email for {} to {}".format(device_type_list[i], email['To']))

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"""Query Meshify for data."""
import requests
import json
from os import getenv
from sys import exit
MESHIFY_BASE_URL = "https://henrypump.meshify.com/api/v3/"
MESHIFY_USERNAME = getenv("MESHIFY_USERNAME")
MESHIFY_PASSWORD = getenv("MESHIFY_PASSWORD")
MESHIFY_AUTH = requests.auth.HTTPBasicAuth(MESHIFY_USERNAME, MESHIFY_PASSWORD)
if not MESHIFY_USERNAME or not MESHIFY_PASSWORD:
print("Be sure to set the meshify username and password as environment variables MESHIFY_USERNAME and MESHIFY_PASSWORD")
exit()
def find_by_name(name, list_of_stuff):
"""Find an object in a list of stuff by its name parameter."""
for x in list_of_stuff:
if x['name'] == name:
return x
return False
def query_meshify_api(endpoint):
"""Make a query to the meshify API."""
q_url = MESHIFY_BASE_URL + endpoint
q_req = requests.get(q_url, auth=MESHIFY_AUTH)
return json.loads(q_req.text) if q_req.status_code == 200 else []
def post_meshify_api(endpoint, data):
"""Post data to the meshify API."""
q_url = MESHIFY_BASE_URL + endpoint
q_req = requests.post(q_url, data=json.dumps(data), auth=MESHIFY_AUTH)
if q_req.status_code != 200:
print(q_req.status_code)
return json.loads(q_req.text) if q_req.status_code == 200 else []

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reports_xlsx.py
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"""Prepare and send daily reports for Advanced VFD IPP devices in Meshify."""
import meshify
import json
from os import getenv
from sys import exit, stdout
from smtplib import SMTP
from datetime import datetime, timedelta
from email.mime.multipart import MIMEMultipart
from email import encoders
from email.mime.base import MIMEBase
from time import sleep, time
from tzlocal import get_localzone
import xlsxwriter
import argparse
import logging
from logging.handlers import RotatingFileHandler
logger = ""
DEVICE_TYPE_NAME = ""
datestring = datetime.now().strftime("%Y%m%d")
VALUES_TO_INCLUDE = []
MESHIFY_NAMES = []
CONFIG_PATH = ""
OUTPUT_PATH = ""
SMTP_EMAIL = getenv("SMTP_EMAIL")
SMTP_PASSWORD = getenv("SMTP_PASSWORD")
def join_company_info(obj_with_companyId, company_lookup_obj):
"""Add company information to an object with companyId property."""
obj_with_companyId['company'] = company_lookup_obj[obj_with_companyId['companyId']]
return obj_with_companyId
def filter_object_parameters(ob, list_of_parameters):
"""Return an object of just the list of paramters."""
new_ob = {}
for par in list_of_parameters:
try:
new_ob[par] = ob[par]
except KeyError:
new_ob[par] = None
return new_ob
def group_by_company(devices):
"""Group a list of devices by company."""
grouped = {}
for dev in devices:
try:
grouped[dev['company']['name']].append(dev)
except KeyError:
grouped[dev['company']['name']] = [dev]
return grouped
def main(sendEmail=False):
"""Get the data and optionally send an email."""
if sendEmail:
if not SMTP_EMAIL or not SMTP_PASSWORD:
logger.error("Be sure to set the SMTP email and password as environment variables SMTP_EMAIL and SMTP_PASSWORD")
exit()
devicetypes = meshify.query_meshify_api("devicetypes")
this_devicetype = meshify.find_by_name(DEVICE_TYPE_NAME, devicetypes)
companies = meshify.query_meshify_api("companies")
company_lookup = {}
for x in companies:
company_lookup[x['id']] = x
devices = meshify.query_meshify_api("devices")
this_devices = filter(lambda x: x['deviceTypeId'] == this_devicetype['id'], devices)
this_devices = [join_company_info(x, company_lookup) for x in this_devices]
for i in range(0, len(this_devices)):
this_devices[i]['values'] = filter_object_parameters(
meshify.query_meshify_api("devices/{}/values".format(this_devices[i]['id'])), MESHIFY_NAMES)
this_devices = group_by_company(this_devices)
for comp in this_devices:
local_tz = get_localzone()
now_t = time()
now_dt = datetime.utcfromtimestamp(now_t)
now = local_tz.localize(now_dt)
workbook = xlsxwriter.Workbook("{}/{}_{}_{}.xlsx".format(OUTPUT_PATH, DEVICE_TYPE_NAME, comp, datestring))
worksheet = workbook.add_worksheet()
worksheet.set_column('A:A', 20)
bold = workbook.add_format({'bold': True})
red = workbook.add_format({'font_color': 'red'})
worksheet.write(0, 0, "Well Name", bold)
for i in range(0, len(VALUES_TO_INCLUDE)):
worksheet.write(0, i+1, VALUES_TO_INCLUDE[i]['vanity_name'], bold)
sorted_company_devices = sorted(this_devices[comp], key=lambda x: x['vanityName'])
for j in range(0, len(sorted_company_devices)):
dev = sorted_company_devices[j]
worksheet.write(j+1, 0, dev['vanityName'])
for k in range(0, len(MESHIFY_NAMES)):
v = MESHIFY_NAMES[k]
dt_ts = datetime.utcfromtimestamp(dev['values'][v]['timestamp'])
dt_loc = local_tz.localize(dt_ts)
stale = (now - dt_loc) > timedelta(hours=24)
try:
v = round(float(dev['values'][v]['value']), 3)
if stale:
worksheet.write_number(j+1, 1+k, v, red)
else:
worksheet.write_number(j+1, 1+k, v)
except ValueError:
v = str(dev['values'][v]['value'])
if stale:
worksheet.write(j+1, 1+k, v, red)
else:
worksheet.write(j+1, 1+k, v)
workbook.close()
if sendEmail:
with open("{}/{}_to.json".format(CONFIG_PATH, DEVICE_TYPE_NAME), 'r') as to_file:
to_lookup = json.load(to_file)
try:
email_to = to_lookup[comp]
except KeyError:
logger.error("No recipients for that company({})!".format(comp))
continue
# part1 = MIMEText(header + values, "plain")
attachment = MIMEBase('application', 'octet-stream')
attachment.set_payload(open("{}/{}_{}_{}.xlsx".format(OUTPUT_PATH, DEVICE_TYPE_NAME, comp, datestring), "rb").read())
encoders.encode_base64(attachment)
now = datetime.now()
datestr = now.strftime("%a %b %d, %Y")
msg = MIMEMultipart('alternative')
msg['Subject'] = "{} Daily {} Report for {}".format(comp, DEVICE_TYPE_NAME.upper(), datestr)
msg['From'] = "alerts@henry-pump.com"
msg['To'] = ", ".join(email_to)
filename = "{} {}.xlsx".format(comp, datestr)
attachment.add_header('Content-Disposition', 'attachment', filename=filename)
# msg.attach(part1)
# msg.attach(part2)
msg.attach(attachment)
# s = SMTP(host="secure.emailsrvr.com", port=25)
s = SMTP(host="email-smtp.us-east-1.amazonaws.com", port=587)
s.starttls()
s.login(SMTP_EMAIL, SMTP_PASSWORD)
s.sendmail(from_addr="alerts@henry-pump.com", to_addrs=email_to, msg=msg.as_string())
logger.info("Email sent to {} for {}".format(email_to, comp))
sleep(2)
def setup_logger():
"""Setup and return the logger module."""
log_formatter = logging.Formatter('%(asctime)s %(levelname)s %(funcName)s(%(lineno)d) %(message)s')
logFile = '{}/emailreports.log'.format(CONFIG_PATH)
my_handler = RotatingFileHandler(logFile, mode='a', maxBytes=500*1024, backupCount=2, encoding=None, delay=0)
my_handler.setFormatter(log_formatter)
my_handler.setLevel(logging.INFO)
logger = logging.getLogger("emailreports")
logger.setLevel(logging.INFO)
logger.addHandler(my_handler)
console_out = logging.StreamHandler(stdout)
console_out.setFormatter(log_formatter)
logger.addHandler(console_out)
return logger
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('deviceType', help="Meshify device type")
parser.add_argument('-s', '--send', action='store_true', help="Send emails to everyone in the _to.json file")
parser.add_argument('-c', '--config-path', default="channel_config", help="The folder path that holds the configuration files")
parser.add_argument('-o', '--output-path', default="files", help="The folder path that holds the output files")
args = parser.parse_args()
DEVICE_TYPE_NAME = args.deviceType
SEND_EMAIL = args.send
CONFIG_PATH = args.config_path
if CONFIG_PATH[-1] == '/':
CONFIG_PATH = CONFIG_PATH[:-1]
OUTPUT_PATH = args.output_path
if OUTPUT_PATH[-1] == '/':
OUTPUT_PATH = OUTPUT_PATH[:-1]
logger = setup_logger()
try:
with open("{}/{}_channels.json".format(CONFIG_PATH, DEVICE_TYPE_NAME), 'r') as channel_file:
VALUES_TO_INCLUDE = json.load(channel_file)
MESHIFY_NAMES = [m['meshify_name'] for m in VALUES_TO_INCLUDE]
except IOError:
logger.error("No channel file named {}_channels.json".format(DEVICE_TYPE_NAME))
exit()
except ValueError as e:
logger.error("Channel file {}_channels.json is misformed: {}".format(DEVICE_TYPE_NAME, e))
exit()
main(sendEmail=SEND_EMAIL)