The Huawei SUN2000 SDongle has an annoying trait you only trip over once you want to connect more than one device: it accepts exactly one concurrent Modbus-TCP connection. The moment Home Assistant polls it, the AC·THOR stops getting answers; let evcc squeeze in and one of the two gets dropped. In my setup three clients wanted to read the same registers at once — and the dongle let exactly one through.
The usual advice is: use the ha-modbusproxy add-on. It works. But I wanted to understand what happens underneath, and I didn't want a black-box container for something that, at its core, is surprisingly small. So I wrote the proxy myself: roughly 300 lines of asyncio Python that poll the SDongle once every 10 seconds into an in-memory register cache and serve FC3 reads to any number of parallel clients. This post is the developer deep-dive to my concept post on caching Modbus proxies — that one is about the why, this one is about the how, down to the byte level.
The problem: one upstream, many clients
Modbus-TCP is a simple request-response protocol, but the SDongle is designed as a slave with exactly one master. Multiple masters at once aren't part of the standard, and Huawei enforces that hard. The solution is a proxy that behaves toward the dongle like the one permitted master, and toward every other device like a Modbus slave itself. The second half is the key: it answers client reads not by forwarding to the dongle, but from a cache. That way the dongle only ever sees one calm, periodic poller, no matter how many clients hang off the back.
The configuration: the only thing you change
I parameterize the whole proxy through a handful of constants at the top of the file. In the normal case you only change your SDongle's IP and maybe the listen port. Everything else fits a standard Huawei installation.
# === Configuration ===
SDONGLE_HOST = "192.0.2.10" # <- deine Huawei SDongle IP (RFC 5737 Beispiel)
SDONGLE_PORT = 502
DEVICE_ID = 1
SERVER_HOST = "0.0.0.0" # auf allen Interfaces lauschen
SERVER_PORT = 5502
POLL_INTERVAL = 10 # Sekunden
The proxy listens on port 5502 instead of 502 so it can run alongside the actual dongle and needs no root for a privileged port. In Home Assistant, AC·THOR and evcc you then simply enter the proxy host's IP and port 5502 — none of the clients notice they aren't talking to the dongle directly.
Register batching: fewer roundtrips to the dongle
The SDongle is slow, and every single read costs a full TCP roundtrip. Instead of querying each register individually, I read contiguous blocks in one go. Modbus allows up to 125 registers per FC3 read; I group the registers I need into a few batches along the natural gaps in the Huawei map.
REGISTER_BATCHES = [
(32016, 4), # PV string 1/2 voltage + current
(32064, 2), # Input power (int32)
(32080, 2), # Active power (int32)
(32106, 2), # Cumulative energy yield (uint32)
(32114, 2), # Daily energy yield (uint32)
(37760, 1), # Battery SOC
(37765, 2), # Battery power (int32)
(37780, 8), # Battery total charge/discharge + daily
]
Each entry is a (start_address, count) tuple. These eight batches cover everything my clients need — PV string values, power, yield and the full battery block. Per poll cycle that's eight small reads instead of dozens of individual queries, and the entire cycle finishes in well under a second.
Reading one FC3 batch: packing and unpacking the MBAP frame
This is where it gets interesting. A Modbus-TCP frame is the 7-byte MBAP header (transaction ID, protocol ID, length, unit ID) plus the PDU (function code + payload). With struct.pack I build the request frame, write it to the dongle, and unpack the response again. The format string ">HHHBBHH" encodes exactly that structure: three big-endian uint16 for the MBAP head, then unit, function code and the two uint16 for start address and count.
async def read_batch(reader, writer, start, count):
req = struct.pack(">HHHBBHH", 0, 0, 6, DEVICE_ID, 3, start, count)
writer.write(req)
await writer.drain()
resp = await asyncio.wait_for(reader.read(9 + count * 2), timeout=3)
resp_tx, resp_proto, resp_len, resp_unit, resp_fc, byte_count = struct.unpack(
">HHHBBB", resp[:9])
if resp_fc >= 0x80: # Exception
return None
data = resp[9:]
if len(data) >= count * 2:
return struct.unpack(">" + "H" * count, data[:count * 2])
Two details matter. The asyncio.wait_for(..., timeout=3) stops a hung dongle from blocking the whole poller — if the answer never comes, the read times out and the cycle drops into backoff. And the resp_fc >= 0x80 check catches Modbus exceptions: if the dongle sets the top bit of the function code, it's not a data response but an error, so I return None instead of unpacking garbage. The int32/uint32 values from the batches get reassembled later by the caller from two consecutive uint16 registers each.
Serving the cache to every client
The second half of the proxy is the server side. When a client connects and sends an FC3 read, I answer it not from the dongle but from the in-memory cache. I read the requested start address and count from the client PDU, pull the values out of the cache dictionary under an asyncio.Lock, and build a valid Modbus response with a correct MBAP header back.
if fc == 3 and len(pdu) >= 5:
reg_addr, reg_count = struct.unpack(">HH", pdu[1:5])
values = []
async with cache_lock:
for i in range(reg_count):
values.append(register_cache.get(reg_addr + i, 0))
byte_count = reg_count * 2
resp_pdu = struct.pack(">BB", fc, byte_count)
resp_pdu += struct.pack(">" + "H" * reg_count, *values)
resp_header = struct.pack(">HHHB", tx_id, 0, len(resp_pdu) + 1, unit_id)
client_writer.write(resp_header + resp_pdu)
The cache_lock is not optional: the reader loop writes the cache while several client handlers read it at the same time — without the lock you could serve a half-updated register row. It's also important that I mirror the client's tx_id (transaction ID) in the response; a correct Modbus master matches responses precisely on that field, and a wrong value makes some clients discard the answer. Missing registers I answer with 0 rather than an error — that keeps picky clients happy.
The reader loop: poll, backoff, stale warning
Holding it all together is a single long-running task that polls the dongle in a loop. As long as everything is fine it runs at the normal 10-second cadence. If a poll fails, it goes into a shorter retry, and if the cache gets too old, it writes a warning to the log.
async def reader_loop():
retry_delay = 5
while True:
success = await read_sdongle()
if success:
last_update = time.time()
retry_delay = POLL_INTERVAL
else:
retry_delay = min(retry_delay, 10)
age = time.time() - last_update if last_update > 0 else -1
if age > 120:
logger.warning(f"Cache stale for {age:.0f}s")
await asyncio.sleep(retry_delay)
The stale warning after 120 seconds is my early-warning system: when it shows up in the log I know the dongle has stopped answering before the clients even start showing weird values. I deliberately kept the cache holding the last valid values on failure rather than dropping to zero — otherwise every dongle hiccup would push a PV power of 0 W to all clients and trigger false alarms and broken statistics in Home Assistant.
Wiring it into Home Assistant and checking it
On the HA side almost nothing changes versus a direct connection — you just point the Modbus hub at the proxy instead of the dongle. I now run three clients against the same upstream, and on the PV dashboard I see sensor.my_pv_pv_leistung, sensor.my_pv_batteriestand and sensor.pv_gesamt_ertrag updating live — all sourced through the proxy at the same time, without the clients stealing the connection from each other. How I turn these raw values into self-consumption and autarky is in the post on self-consumption and autarky sensors.
Frequently asked questions
Why not just use the ha-modbusproxy add-on?
You can, and for most people it's the right call. But I wanted to understand what happens under the hood and have full control over batching, cache behaviour and logging. If you're happy for an add-on to stay a black box, use the add-on; if you want to understand or extend the mechanism (e.g. your own computed registers, different poll intervals per batch), the home-built proxy is exactly right.
Doesn't the cache serve stale values?
At most as old as your poll interval — 10 seconds here. For PV power, battery SOC and yield that's perfectly fine; these values don't change meaningfully second by second. If you need it faster, lower POLL_INTERVAL, but keep in mind the SDongle gets cranky under overly aggressive polling. Ten seconds is the stable sweet spot for me.
Does the proxy support writes (FC6/FC16)?
Not this version — it's deliberately read-only and only handles FC3. That covers the sensor connection this post is about. Writes (say, a battery charge-mode control) you'd have to add, and then the 1-connection limit bites even harder: writes must not overlap. For pure data sharing across multiple clients, read-only is the safe and sufficient path.
What happens if the SDongle drops out briefly?
The reader loop goes into retry backoff and the cache holds the last valid values instead of falling to zero — so clients see no crash, just frozen values. After 120 seconds without an update the proxy writes a stale warning to the log. When the dongle comes back, the next successful poll refills the cache and the normal 10-second cadence resumes automatically.
