Sery Python SDK
Query your private data mesh by sery:// address — one SQL statement, run on whichever machine holds the data. Raw data never moves through Sery; only result rows come back.
pip install sery # core
pip install sery[pandas] # + .to_pandas()
Quick start
import sery
client = sery.Client(api_key="sery_...") # from app.sery.ai → Settings → API Keys
df = client.query("""
SELECT customer, SUM(amount) AS total
FROM 'sery://sam-laptop/local/sales/orders.parquet'
GROUP BY customer
ORDER BY total DESC
""").to_pandas()
Addresses
Sources are addressed as sery://<machine>/<protocol>/<path>:
<machine>— a machine's stable id or its name (e.g.sam-laptop)<protocol>—local,s3, orhttps<path>— the file path / bucket key
Discover what's addressable with the catalog:
for src in client.catalog():
print(src.sery_uri, "—", src.machine, src.file_format)
# sery://sam-laptop/local/sales/orders.parquet — sam-laptop parquet
Pass any sery_uri straight into query().
Results
result = client.query("SELECT * FROM 'sery://my-mac/local/data.parquet' LIMIT 5")
result.columns # ['id', 'name', ...]
result.rows # [[1, 'a'], [2, 'b'], ...]
for row in result: # iterate as dicts
print(row["name"])
result.to_pandas() # DataFrame (needs pandas)
result.incomplete # True if a machine didn't respond
result.warnings # human-readable warnings to surface
When
incompleteisTrue, one or more machines were offline — checkwarningsbefore trusting an aggregate (a SUM/COUNT may undercount).
Errors
Every failure is a typed exception (sery.errors):
| Exception | When |
|---|---|
AuthError |
missing / invalid API key (401) |
QueryError |
no sery:// refs, bad address, unsupported protocol (400) |
MachineNotFound |
unknown machine (404) |
AmbiguousMachine |
a name matched >1 machine — .candidates lists machine_ids (409) |
CrossMachineJoinUnsupported |
the query spans machines — .machines (422) |
MachinesUnavailable |
every targeted machine offline — .failures (503) |
import sery
try:
client.query("SELECT * FROM 'sery://laptop/local/x.parquet'")
except sery.AmbiguousMachine as e:
for c in e.candidates:
print(c["label"], c["machine_id"]) # re-issue with the machine_id
Limitations (v1)
- All sources in one query must live on the same machine — cross-machine joins raise
CrossMachineJoinUnsupported. - Routable protocols:
local,s3,https.
License
MIT
Metadata
Release files for sery 0.2.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| sery-0.2.0.tar.gz | 10.3 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sery-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.4 kB
Release files / sery-0.2.0.tar.gz
| Download URL | sery-0.2.0.tar.gz |
|---|---|
| Size | 10.3 kB |
| Tags | Source |
|
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aac64810337ed8acba51cd1da7ae64471a39d57b18fed6065e8964c08cbb77b1
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| Size | 8.1 kB |
| Tags | Python 3 |
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Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
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