pyvark
Python client for the Anthive
single-cell RNA-seq REST API. Sibling of the Go vark
CLI — same backend, two front ends.
API surface verified against anthive REST API 2.36.0 (2026-08-07).
Why the dual name?
The Go CLI ships as a binary called vark. To avoid clobbering it on
the user's $PATH and to keep the PyPI / Codeberg slug obvious, the
distribution name is pyvark but the importable name is vark.
pip install pyvark # distribution
python -c "from vark import AnthiveClient; print('ok')" # usage
(Both CLI and library live next to each other in the same Anthive setup
with no shell collision: vark = the Go binary, vark = the Python
import.)
Install
From PyPI:
pip install pyvark # or: uv add pyvark
Version pin (semver-safe):
pip install "pyvark>=0.4.0,<0.5"
Editable from a local checkout (development):
git clone ssh://git@codeberg.org/mfiers/pyvark.git
cd pyvark
uv pip install -e .
# with pandas for `format='dataframe'` support:
uv pip install -e ".[pandas]"
Pyodide / JupyterLite:
import micropip
await micropip.install("pyvark")
from vark import AnthiveClient
client = AnthiveClient() # auto-detects {origin}/api/ in the browser
Minimal example
from vark import AnthiveClient
client = AnthiveClient(
"https://my.anthive.example/api",
auth=("user", "password"),
)
# What's on this server?
print(client.get_version()["version"])
databases = client.get_databases()
print(f"{len(databases)} datasets available")
# Pick a dataset and show its metadata fields
info = client.get_database_info(databases[0]["id"])
print(info["title"], info["n_cells"], "cells")
# Render a UMAP scatter server-side and write the PNG
plot = client.get_plot(
info["id"], "scatter",
color="cell_type",
palette_categorical="tab20",
width=6, height=5, dpi=150,
)
open("umap.png", "wb").write(plot["bytes"])
# The X-Plot-Caption header carries anthive's prose figure legend —
# this is the ONLY place the multi-sentence caption exists.
print(plot["caption"])
Reusing vark CLI credentials
Anthive credentials are stored once by the Go vark
CLI — username + password are encrypted at rest with age
(modern X25519 + ChaCha20-Poly1305) into ~/.config/vark/secrets.age.
pyvark reads from that same store, so a notebook or script never
needs a password literal, an environment variable, or a getpass()
prompt.
One-time setup (Go CLI side)
Install the Go vark binary, then
register your server:
vark server login --name myserver \
--url https://my.anthive.example/api \
--user me
# → prompts for the password; encrypts it into ~/.config/vark/secrets.age
vark server ls # confirm the entry is there
That writes two files:
~/.config/vark/config.yaml— the server registry (name, URL, user,insecure:flag).~/.config/vark/secrets.age— age-encrypted password store.
Install the pyvark extras
pip install "pyvark[vark-config]" # adds pyrage (age) + PyYAML
The base install of pyvark is unchanged; the extras are only needed
for credential discovery.
Use it from Python
Auto-discover by URL — no auth= argument, no password in code:
from vark import AnthiveClient
client = AnthiveClient("https://my.anthive.example/api")
# pyvark matches the URL against `vark server ls`, pulls
# (user, password) from secrets.age, and (if insecure: true is set
# on the entry) demotes `verify` to False automatically.
Look up by registered name — handy when you don't want a URL hard-coded in the notebook:
client = AnthiveClient.from_vark_server("myserver")
The vark_config= constructor knob
| Value | Behaviour |
|---|---|
None |
Default. Auto-discover; silently no-op if the config dir or extras are missing. |
True |
Require. Raise VarkConfigError if no entry matches the URL. |
False |
Skip. Never read ~/.config/vark/, even if it exists. |
str / Path |
Use that directory instead of ~/.config/vark/ (useful for tests / portable setups). |
Explicit auth=(user, password) always wins — vark-config discovery
never overrides a caller-supplied auth. Pyodide / JupyterLite skip
discovery automatically (no filesystem in the browser).
Troubleshooting
401 Unauthorizedon the first request. Did you actually runvark server loginfor this server? A freshvarkinstall lays down a placeholdersecrets.agethat decrypts cleanly but contains no real password — the server then 401s. Re-runvark server loginto overwrite it.NoSuchEntryError(or "no matching server entry"). The URL passed toAnthiveClient()doesn't match any entry invark server ls. URLs are normalised (trailing slash stripped, host case-folded) before matching, so it's almost always a typo or a missing/apisuffix — comparevark server lsoutput against your constructor argument character-for-character.ImportError: pyrageorImportError: yaml. You installed the basepyvarkwithout the extras. Fix:pip install "pyvark[vark-config]".
API coverage (highlights)
get_root,get_health,get_metrics,get_version,get_changelog— version + latency telemetry (/healthexposesmean_response_ms/p50_response_ms/n_samples).get_databases,get_database_info,get_group(group_id)— catalog + per-collection landing-page data (API 2.5+).get_plot(db_id, geom, ...)— every server-side geom:scatter,hexbin,kde2d,violin,box,bar,histogram,ecdf,kde,heatmap,rolling,volcano,ma,forest,de_heatmap,de_quadrant. Captures theX-Plot-Captionresponse header (the multi-sentence figure legend — API 2.7.2+). Supportscolor_scale=auto|sequential| divergent, plot clamps (log2fc_clip,neglog10p_clip,logmean_clip), bargroup_by, hexbin auto-clip (vmin_quantile/vmax_quantile), per-axis transforms (transform_x/transform_y,asinh_scale), KDE knobs (kde_n,kde_bw,n_levels,iso_overlay,point_overlay), marginals / regline overlays, and on-the-fly binning of a continuouscolorfield viabin_color=N(2..20) +bin_color_method='quantile'|'width'— wired on scatter, hexbin, rolling (API 2.34+), kde2d (2.35+), histogram / ecdf / kde (2.36+). Data export viaformat="csv"/"tsv"returns the dataframe the plot was built from (API 2.6+).list_de_studies,get_de_study,list_de_contrasts,get_de_rows,get_de_by_gene— DE data flow (API 2.3+).analytics_schema,analytics_query,analytics_viz— SELECT-only SQL sandbox + Parquet-backed visualisation.module_score,list_module_scores— on-the-fly and pre-computed module scores.list_genesets,get_geneset,rescan_genesets.list_catalogs,get_catalog,get_catalog_module,get_catalog_score,rescan_catalogs— unified module-catalog view over starCAT (weighted programs, one-segment id likeMICROGLIA_V1_0) + genesets (plain gene lists, two-segment id likeSierksma2025/WGCNA). Score recipes let you reproduce binary*_poscalls client-side (API 2.30+).pick_fastest(base_urls, ...)— server-selection helper that consumes/healthlatency telemetry.
Module catalogs (starCAT + genesets)
Anthive REST API 2.30 unifies starCAT programs and genesets behind a
single /catalogs view. Both sources answer to the same route
templates, so a client can walk every module catalog without
branching by kind:
from vark import AnthiveClient
client = AnthiveClient("https://my.anthive.example/api")
# 1. Discover every catalog (or filter by source).
inventory = client.list_catalogs(source="starcat")
for cat in inventory["catalogs"]:
print(cat["source"], cat["catalog_id"], cat.get("n_modules"))
# 2. Drill into one catalog — module + score summaries.
# catalog_id is one segment for starcat, two for geneset.
starcat = client.get_catalog("starcat", "MICROGLIA_V1_0")
print(len(starcat["modules"]), "modules")
print(len(starcat["scores"]), "derived scores")
geneset = client.get_catalog("geneset", "Sierksma2025/WGCNA")
# 3. Fetch one module's gene weights (starcat) or list (geneset).
mod = client.get_catalog_module(
"starcat", "MICROGLIA_V1_0", "Microglia_Border_CAM", top=20,
)
for row in mod["top_genes"]:
print(f"{row['rank']:2} {row['gene']:10} {row['weight']:+.4f}")
# 4. Fetch a derived-score recipe — enough to reproduce it
# client-side. Binary `*_pos` calls are just
# `usage[column] > threshold` on normalised usage.
recipe = client.get_catalog_score(
"starcat", "MICROGLIA_V1_0", "Border_CAM_pos",
)
# {"name": "Border_CAM_pos", "kind": "discrete",
# "columns": ["Microglia_Border_CAM"], "threshold": 0.0448, ...}
client.rescan_catalogs() forces a server-side reload after you
drop a new starCAT TSV or geneset YAML onto the store.
Recipe — module-score vs gene on the XY plot (API 2.29+)
REST API 2.29 lifted the restriction that made attach_sessions
columns unusable as x / y on the XY plot endpoints (they
worked as color= already). That unlocks the "score-vs-gene"
figure — compute a module score on the fly, then plot it against a
single gene's expression:
from vark import AnthiveClient
client = AnthiveClient("https://my.anthive.example/api")
db_id = "Sierksma2025/microglia"
# Compute a Seurat-style module score for a small gene list and
# capture the session id the server hands back.
score = client.module_score(
db_id,
genes=["APOE", "TREM2", "CD9", "SPP1"],
name="DAM_score",
)
session_col = score["column"] # e.g. "session_1::DAM_score"
# Now use the score as X on an XY scatter, gene expression as Y.
# Pre-2.29 servers reject this with 400; 2.29+ returns a plot.
plot = client.get_plot(
db_id, "scatter",
x=session_col, y="SPP1",
color="cell_type",
marginals="hist", regline=True,
width=6, height=5, dpi=150,
)
open("dam_vs_spp1.png", "wb").write(plot["bytes"])
print(plot["caption"])
session_col is dataset-scoped and lives only inside this client's
plot-request context — the server re-materialises it from the
Parquet sidecar keyed on session_id. Nothing is written back to
the duckdb.
Tests
# Offline (no server needed):
uv run --with pytest --with requests python -m pytest tests/test_offline.py -v
# Live smoke (round-trip):
ANTHIVE_TEST_URL=https://my.anthive/api \
ANTHIVE_TEST_USER=user ANTHIVE_TEST_PASSWORD=pass \
uv run --with pytest --with requests --with pandas \
python -m pytest tests/test_smoke.py -v
Versioning
pyvark starts at 0.1.0 as a clean break from the legacy
antclient 1.x history that previously lived under
anthive4/antclient/. The Anthive REST API uses its own semver
(X.Y.Z) — see client.AnthiveClient.API_TARGET for the version this
release was last verified against.
License
MIT — see LICENSE.
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