ml4t-polars-patterns skillA
ml4t-polars-patterns is agent-read markdown (skill) from ml4t/skills: Polars-first data processing patterns for financial data. Use when writing efficient grouped, windowed, or lazy-evaluated data transformations..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Polars Patterns for Quant Finance
Pandas groupby-apply with Python functions is 10-100x slower than Polars lazy expressions with `.over()`. For financial data - where most operations are per-symbol rolling computations - the performance gap determines whether your pipeline takes minutes or hours.
## The Problem
A typical quant workflow: load 500 symbols of daily data (2M rows), compute 20-day rolling features per symbol, cross-sectional rank, then join with labels. In pandas with `groupby().apply()`, this takes 45 seconds and 8 GB of RAM. The same logic in Polars lazy mode takes 2 seconds and 800 MB. The difference is not optimization - it is a fundamentally different execution model.
## The Pattern
### WRONG
```python
import pandas as pd
# Pandas: iterative groupby-apply - Python loop per group
df = pd.read_parquet("prices.parquet")
# Slow: Python function called once per symbol
def compute_features(group):
group["momentum"] = group["close"].pct_change(20)
group["volatility"] = group["close"].pct_change().rolling(20).std()
group["rank"] = group["momentum"].rank(pct=True)
return group
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-polars-patterns@git:20260901.c415df0mdr add ml4t/skills/ml4t-polars-patterns@sha256:bcc9062c8b494776Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_7nijr7aca7c7fhf3)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.c415df0 latest | 2026-09-01 | c415df0 | 4,778 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,798 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4778 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ml4t/skills · 19 stars · license Apache-2.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_7nijr7aca7c7fhf3 GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-polars-patterns GET https://markdownregistry.com/api/v1/blob/bcc9062c8b4947765ef467c3becf3c1873eac16612118c2bdd187adcaf62df8e
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