snippet to write solaredge optimisers panel data in an influxdb database

solaredge.py

import requests, pickle
from datetime import datetime
import json, pytz
import pandas as pd
from influxdb import DataFrameClient

# Set "static" variables
login_url = "https://monitoring.solaredge.com/solaredge-apigw/api/login"
panels_url = "https://monitoring.solaredge.com/solaredge-web/p/playbackData"
DAILY_DATA = "4"
WEEKLY_DATA = "5"

# Set "customizable" variables.  Update as appropriate
COOKIEFILE = 'solaredge.cookies'
TIMEPERIOD = DAILY_DATA
SOLAREDGE_USER = "" # web username
SOLAREDGE_PASS = "" # web password
SOLAREDGE_SITE_ID = "" # site id
INFLUXDB_IP = ""
INFLUXDB_PORT = 8086
INFLUXDB_DATABASE = ""
INFLUXDB_SERIES = "optimizers"
INFLUXDB_RETENTION_POLICY = "autogen"

session = requests.session()
try: # Make sure the cookie file exists
    with open(COOKIEFILE, 'rb') as f:
        f.close()
except IOError:  # Create the cookie file 
    session.post(login_url, headers = {"Content-Type": "application/x-www-form-urlencoded"}, data={"j_username": SOLAREDGE_USER, "j_password": SOLAREDGE_PASS})
    panels = session.post(panels_url, headers = {"Content-Type": "application/x-www-form-urlencoded", "X-CSRF-TOKEN": session.cookies["CSRF-TOKEN"]}, data={"fieldId": SOLAREDGE_SITE_ID, "timeUnit": TIMEPERIOD})
    try:
        with open(COOKIEFILE, 'wb') as f:
            pickle.dump(session.cookies, f)
            f.close()
    except IOError:
        print('Unable to create cookie file (readonly filesystem?): ' + COOKIEFILE)

try:
    with open(COOKIEFILE, 'rb') as f:
        session.cookies.update(pickle.load(f))
except IOError:
    print('Unable to open cookie file: ' + COOKIEFILE)
    print('Will continue running with new login...')
    session.post(login_url, headers = {"Content-Type": "application/x-www-form-urlencoded"}, data={"j_username": SOLAREDGE_USER, "j_password": SOLAREDGE_PASS})

# Get the cookie expiration
for cookie in session.cookies:
        if cookie.name == 'SolarEdge_SSO-1.4':
            cookie_expiration = cookie.expires
panels = session.post(panels_url, headers = {"Content-Type": "application/x-www-form-urlencoded", "X-CSRF-TOKEN": session.cookies["CSRF-TOKEN"]}, data={"fieldId": SOLAREDGE_SITE_ID, "timeUnit": TIMEPERIOD})
if (panels.status_code != 200) or (datetime.now() > datetime.fromtimestamp(cookie_expiration)):  # Update cookie if expired
    session.post(login_url, headers = {"Content-Type": "application/x-www-form-urlencoded"}, data={"j_username": SOLAREDGE_USER, "j_password": SOLAREDGE_PASS})
    panels = session.post(panels_url, headers = {"Content-Type": "application/x-www-form-urlencoded", "X-CSRF-TOKEN": session.cookies["CSRF-TOKEN"]}, data={"fieldId": SOLAREDGE_SITE_ID, "timeUnit": TIMEPERIOD})
    if (panels.status_code != 200):
        exit() # Terminate if unable to get panel data
    f.close()
    try:
        with open(COOKIEFILE, 'wb') as f:
            pickle.dump(session.cookies, f)
            f.close()
    except IOError:
        print('Unable to update expired cookie file [' + str(datetime.fromtimestamp(cookie_expiration)) + '] (readonly filesystem?): ' + COOKIEFILE)
    
response = panels.content.decode("utf-8").replace('\'', '"').replace('Array', '').replace('key', '"key"').replace('value', '"value"')
response = response.replace('timeUnit', '"timeUnit"').replace('fieldData', '"fieldData"').replace('reportersData', '"reportersData"')
response = json.loads(response)
    
data = {}
for date_str in response["reportersData"].keys():
    date = datetime.strptime(date_str, '%a %b %d %H:%M:%S GMT %Y')
    date = pytz.timezone('America/New_York').localize(date).astimezone(pytz.utc)
    for sid in response["reportersData"][date_str].keys():
        for entry in response["reportersData"][date_str][sid]:
            if entry["key"] not in data.keys():
                data[entry["key"]] = {}
            data[entry["key"]][date] = float(entry["value"].replace(",", ""))

df = pd.DataFrame(data)
conn = DataFrameClient(INFLUXDB_IP, INFLUXDB_PORT, "", "", INFLUXDB_DATABASE)
conn.write_points(df, INFLUXDB_SERIES, retention_policy=INFLUXDB_RETENTION_POLICY)

Another question: I compared the values from the script with the values in the portal and could not find any match. Now, I'm a bit confused. What do we get here? Energy or Power values? And do you have a clue, why the portal delivers different values to the script?

The script returns the Power values (technically averaged over a 15 minute period since that is a granularity that SE provides via the monitoring site). Since the values are only updated/published very 15 minutes or so, there is no value in running the script more often than every 15 minutes.

Run the script over a 24 hour period and see if the data stored in InfluxDB matches what is on the SE site....

Hi
thank you for the advice. Tested the script results (before Influx) against the Solar Edge Web Portal (CSV export). It's quite similar, but not exactly the same. I assume it's some different roundings... See below:

I'm really not familiar with python, could you give me a hint where at the script you choose the data to be extracted and could the other data (Energy, Current, Voltage Panel, Voltage Optimizer) as well be extracted?

Merry christmay

Hi @cooldil I'm wondering whether you happen to have a list of API parameters that I could use alongside those that you programmed in this GIST. Or, could you confirm that these are the only ones?

Hi
I am wondering how to find this url on dashboard. Thanks!
panels_url = "https://monitoring.solaredge.com/solaredge-web/p/playbackData"

Hi I am wondering how to find this url on dashboard. Thanks! panels_url = "https://monitoring.solaredge.com/solaredge-web/p/playbackData"

The URL you referenced is called when you change over to the Layout area and then click on "Show playback". This brings up a "slider view" where you can see what the output of each of your panels was for any given 15 minute interval.

Thanks for your reply. It works well for me!
Another question, it seems that we are only able to retrive data on current day. Cause the "Show playback" can't display historical daily data. Am I right? And do you have any idea to retrive historical panel data. Thanks.

the ouptput dataframe's column names are be like:
197469474 | 197469507 | 197469573 | 197469606

I am wondering how to match it with the module number on the dashboard. Thanks again!

Thanks for your reply. It works well for me! Another question, it seems that we are only able to retrive data on current day. Cause the "Show playback" can't display historical daily data. Am I right? And do you have any idea to retrive historical panel data. Thanks.

You can go back upto a week. Change the TIMEPERIOD variable to "WEEKLY_DATA"

the ouptput dataframe's column names are be like: 197469474 | 197469507 | 197469573 | 197469606

I am wondering how to match it with the module number on the dashboard. Thanks again!

See my earlier comment: https://gist.github.com/cooldil/0b2c5ee22befbbfcdefd06c9cf2b7a98?permalink_comment_id=4408019#gistcomment-4408019

Hello @cooldil, thanks for sharing your snippet and insights - very helpful and useful! I just added some code to automatically extract the logical IDs (in my case 1.1.1. – 1.1.29.) and serial numbers of optimizers from SE. Hope that might helpful for somebody else.

Here is the code:

# code snippet (2025-06-04 by Thomas Hermann) to retrieve logical IDs 
# (e.g. 1.1.1 -- 1.1.29) and serial numbers for panel optimizers from SE, 
# Instruction: add the following code after df = pd.DataFrame(data) in cooldils 
# snippet (s. line 79). Disclaimer: I did not use/test this with influxdb !
#
# The code requests/extracts information from SE and persists it as dict into
# a pickle file. If that file already exists, it is simply loaded.
# As SE keys stay identical, getting the info needs to be done only once, 
#
# Note that API calls work only directly after retrieving data, as otherwise the cookie
# would be outdated.
#
# Results: 
# - SE_keys_to_ids is a dictionary where keys are the SE keys of the panels, and values 
#    are tuples containing (logical_id, serial_nr). 
try:
    with open("SE_keys_to_ids.pickle", 'rb') as fp:
        SE_keys_to_ids = pickle.load(fp)
except FileNotFoundError:
    SE_keys_to_ids = {}
    for module_key in df.columns:  # column names are SE keys
        print(f"get logical ID and serial nr for SE_key {module_key}")
        res = session.post(
            "https://monitoring.solaredge.com/solaredge-web/p/systemData",
            headers={
                "Content-Type": "application/x-www-form-urlencoded",
                "X-CSRF-TOKEN": session.cookies["CSRF-TOKEN"],
            },
            data=dict(
                fieldId=SOLAREDGE_SITE_ID,
                reporterId=module_key,
                activeTab="0",
                isPublic="false",
                type="panel",
            )
        )
        # res.text contains a javascript file which contains
        # as first statement ```SE.systemData = {...}```, a 
        # dictionary definition which is evaluted in the next line
        # a bit quick and dirty...
        module_dict = eval(res.text.split("\n")[11][16:-1])
        logical_id = module_dict['description'].split()[1]
        serial_nr = module_dict['serialNumber']
        SE_keys_to_ids[module_key] = (logical_id, serial_nr)
        # all information extracted, lets safe pickle file
    with open("SE_keys_to_ids.pickle", 'wb') as fp:
        pickle.dump(SE_keys_to_ids, fp)
print("Loading, resp. extracting SE_keys_to_ids completed")

# set proper df column names (replacing SE_keys by panel name)
df.columns = [ SE_keys_to_ids[mkey][0] for mkey in df.columns]