poolsim 0.3.0

Python bindings for the Poolsim connection pool sizing CLI

poolsim Python Bindings

poolsim is the Python binding package for the Poolsim connection-pool sizing toolkit.

The package is intentionally a thin wrapper around the stable Rust poolsim CLI JSON interface. It does not reimplement the sizing engine in Python. That design keeps Python services, notebooks, CI scripts, and automation jobs aligned with the same model used by the Rust crates, CLI, REST API, WebSocket API, examples, docs fixtures, and release tests.

Use this package when you want to call Poolsim from Python without manually spawning subprocesses or parsing JSON.

What You Can Do

• Run a full pool-size recommendation from a simulation config.
• Evaluate an existing production pool size.
• Generate sensitivity rows across candidate pool sizes.
• Run batch sizing jobs.
• Compare normal, peak, and incident traffic scenarios.
• Allocate a shared database max_connections budget across services.
• Import telemetry snapshots and compute recommendation diffs.
• Diagnose whether a live pool is too small, too large, or close to saturation.
• Generate framework-specific pool configuration snippets.
• Run a CI capacity gate and consume the gate report as Python data.

Architecture

The Python package calls this command shape internally:

poolsim --format json <command> ...

The returned Python value is decoded from the CLI JSON output. The wrapper deliberately keeps the payloads as normal Python dictionaries and lists so new fields added by the CLI remain available without requiring a wrapper release.

This is a compatibility choice: existing methods stay stable, while the Rust CLI remains the single source of truth for simulation behavior.

Install

Install the Python package:

pip install poolsim

Install the Rust CLI executable separately:

cargo install poolsim-cli
poolsim --version

The default client expects a poolsim executable on PATH. If the binary is installed elsewhere, pass the absolute path:

from poolsim import PoolsimClient

client = PoolsimClient(executable="/opt/tools/poolsim")

Runtime Requirements

• Python 3.9 or newer.
• The Rust poolsim executable from poolsim-cli.
• Config, telemetry, scenario, or policy files that match the documented Poolsim CLI schemas.

The Python package has no runtime third-party dependencies.

Quick Start

from poolsim import PoolsimClient

client = PoolsimClient()
report = client.simulate("docs/fixtures/cli-config.json")

print("recommended pool size:", report["optimal_pool_size"])
print("p99 queue wait ms:", report.get("p99_queue_wait_ms"))
print("saturation:", report.get("saturation"))

Equivalent CLI command:

poolsim --format json simulate --config docs/fixtures/cli-config.json

Minimal Simulation Config

A typical simulation config contains workload assumptions, pool limits, and sizing options:

{
  "workload": {
    "requests_per_second": 220.0,
    "latency_p50_ms": 8.0,
    "latency_p95_ms": 32.0,
    "latency_p99_ms": 85.0
  },
  "pool": {
    "max_server_connections": 120,
    "connection_overhead_ms": 2.0,
    "idle_timeout_ms": 120000,
    "min_pool_size": 3,
    "max_pool_size": 24
  },
  "options": {
    "iterations": 12000,
    "seed": 7,
    "distribution": "LogNormal",
    "queue_model": "MMC",
    "target_wait_p99_ms": 45.0,
    "max_acceptable_rho": 0.85
  }
}

Keep these files in source control when you want sizing assumptions to be reviewable.

API Reference

PoolsimClient(executable="poolsim")

Creates a client that invokes the given executable.

Use the default when poolsim is on PATH:

from poolsim import PoolsimClient

client = PoolsimClient()

Use an explicit path when automation installs the binary in a fixed tool directory:

client = PoolsimClient(executable="/usr/local/bin/poolsim")

simulate(config)

Runs a full sizing simulation from a config file and returns a recommendation report.

report = client.simulate("docs/fixtures/cli-config.json")

optimal = report["optimal_pool_size"]
interval = report.get("confidence_interval")
rho = report.get("rho") or report.get("utilisation_rho")

print(optimal, interval, rho)

Equivalent CLI command:

poolsim --format json simulate --config docs/fixtures/cli-config.json

Use simulate when you are choosing the pool size to deploy.

evaluate(config, pool_size)

Scores a fixed pool size against a workload config.

evaluation = client.evaluate("docs/fixtures/cli-config.json", pool_size=8)

print(evaluation.get("pool_size"))
print(evaluation.get("utilisation_rho"))
print(evaluation.get("p99_queue_wait_ms"))
print(evaluation.get("saturation"))

Equivalent CLI command:

poolsim --format json evaluate --config docs/fixtures/cli-config.json --pool-size 8

Use evaluate when production already has a configured pool and you need to know whether that exact setting is safe.

sweep(config)

Returns sensitivity rows for candidate pool sizes.

rows = client.sweep("docs/fixtures/cli-config.json")

for row in rows:
    print(row.get("pool_size"), row.get("utilisation_rho"), row.get("risk"))

Equivalent CLI command:

poolsim --format json sweep --config docs/fixtures/cli-config.json

Use sweep to explain tradeoffs around nearby pool sizes in code review or capacity planning.

batch(config)

Runs multiple simulation requests from one batch config.

reports = client.batch("docs/fixtures/batch.json")

for index, report in enumerate(reports, start=1):
    print(index, report.get("optimal_pool_size"), report.get("saturation"))

Equivalent CLI command:

poolsim --format json batch --config docs/fixtures/batch.json

Use batch when a platform team wants to size several services in one job.

compare(config)

Compares named traffic scenarios such as normal, peak, and incident load.

comparison = client.compare("docs/fixtures/scenarios.json")

print(comparison.get("baseline"))
print(comparison.get("worst_saturation"))
for row in comparison.get("rows", []):
    print(row)

Equivalent CLI command:

poolsim --format json compare --config docs/fixtures/scenarios.json

Use compare when one pool setting must survive several traffic assumptions.

budget(config)

Plans allocation of a database connection budget across services and replicas.

plan = client.budget("docs/fixtures/budget.json")

print(plan.get("status"))
print(plan.get("available_connections"))
print(plan.get("allocated_total_connections"))
for service in plan.get("services", []):
    print(service)

Equivalent CLI command:

poolsim --format json budget --config docs/fixtures/budget.json

Use budget when the database has a shared max_connections limit and several services compete for it.

telemetry_recommend(config)

Imports a telemetry snapshot and returns a recommendation diff from the current pool setting.

recommendation = client.telemetry_recommend("docs/fixtures/telemetry.json")

diff = recommendation.get("diff", {})
print(recommendation.get("service_name"))
print("current:", diff.get("current_pool_size"))
print("recommended:", diff.get("recommended_pool_size"))
print("change:", diff.get("change"))

Equivalent CLI command:

poolsim --format json import telemetry --config docs/fixtures/telemetry.json

Use telemetry_recommend when you have observed production traffic and want to compare the configured pool with the recommended pool.

doctor(config)

Diagnoses a telemetry snapshot and classifies risk.

diagnosis = client.doctor("docs/fixtures/telemetry.json")

print(diagnosis.get("status"))
for finding in diagnosis.get("findings", []):
    print(finding.get("severity"), finding.get("message"), finding.get("action"))

Equivalent CLI command:

poolsim --format json doctor telemetry --config docs/fixtures/telemetry.json

Use doctor when an engineer asks: is this pool too small, too large, or close to saturation?

generate_config(framework, config)

Generates a framework-specific runtime configuration snippet from a simulation recommendation.

snippet = client.generate_config("sqlx", "docs/fixtures/cli-config.json")

print(snippet.get("framework"))
print(snippet.get("recommended_pool_size"))
print(snippet.get("snippet"))

Equivalent CLI command:

poolsim --format json generate-config --framework sqlx simulate --config docs/fixtures/cli-config.json

Supported framework names follow the CLI:

• hikaricp
• spring-boot
• sqlalchemy
• prisma
• node-pg
• sqlx
• deadpool

Use generate_config after simulate when you want a copy-pasteable starting point for a real runtime pool.

gate(policy, telemetry_config)

Runs a capacity gate against a telemetry snapshot and policy file.

gate = client.gate("docs/fixtures/gate-policy.toml", "docs/fixtures/telemetry.json")

print(gate.get("status"))
print(gate.get("deployment_safe"))
for check in gate.get("checks", []):
    print(check)

Equivalent CLI command:

poolsim --format json gate --policy docs/fixtures/gate-policy.toml telemetry --config docs/fixtures/telemetry.json

gate treats CLI exit codes 0 and 2 as valid machine-readable outcomes. Exit code 2 means the capacity gate failed, not that the Python wrapper failed. Other non-zero exit codes raise PoolsimError.

CI Usage

A minimal GitHub Actions step can install both packages and fail the job when your policy says the deployment is unsafe:

- name: Install poolsim
  run: |
    cargo install poolsim-cli
    python -m pip install poolsim

- name: Run capacity gate
  run: |
    python - <<'PY'
    from poolsim import PoolsimClient

    client = PoolsimClient()
    report = client.gate("capacity-policy.toml", "telemetry.json")
    print(report)
    if not report.get("deployment_safe", False):
        raise SystemExit(1)
    PY

Error Handling

The wrapper raises PoolsimError when:

• the CLI exits with an unexpected exit code
• the CLI writes invalid JSON
• the executable cannot be started by Python's subprocess layer

from poolsim import PoolsimClient, PoolsimError

client = PoolsimClient()

try:
    report = client.simulate("missing.json")
except PoolsimError as exc:
    print(f"Poolsim failed: {exc}")
else:
    print(report)

The error message includes CLI stderr when the CLI provides it.

Working With Returned Data

Return types intentionally use ordinary Python containers:

• JSON objects become dictionaries.
• JSON arrays become lists.
• JSON strings, numbers, booleans, and null become standard Python values.

This keeps the binding forward-compatible when the CLI adds new output fields. Prefer dict.get(...) for optional fields when writing automation that should tolerate additional CLI versions.

Troubleshooting

FileNotFoundError or executable startup failure

The Rust CLI is not installed or is not on PATH.

cargo install poolsim-cli
poolsim --version

Or pass an explicit executable path:

client = PoolsimClient(executable="/absolute/path/to/poolsim")

PoolsimError: poolsim did not emit valid JSON

The wrapper always passes --format json. This error usually means the executable path points to a different program, an older incompatible binary, or a command failed before producing JSON.

Check the CLI directly:

poolsim --format json simulate --config docs/fixtures/cli-config.json

Gate returns a failed policy report

That is expected behavior when capacity assumptions are unsafe. Inspect status, deployment_safe, and checks in the returned object. The wrapper will still return JSON for CLI exit code 2.

Compatibility Notes

• The Python wrapper does not change CLI semantics.
• The Rust CLI remains the source of truth for formulas, validation, and output fields.
• Existing method names are intended to remain stable.
• New CLI output fields can appear in returned dictionaries without a Python package change.

Support

• Documentation: https://github.com/gregorian-09/poolsim/tree/main/docs
• Issues: https://github.com/gregorian-09/poolsim/issues
• Repository: https://github.com/gregorian-09/poolsim