Results for “pas”

Process PDFs with Python and command-line tools: extract text and tables, merge, split, rotate, create, watermark, OCR, and handle passwords.

Ingests EPUBs and ebooks into a local vector index, then answers questions and searches passages via a command-line interface.

Guides implementing authentication, authorization, input validation, and OWASP Top 10 prevention with secure code patterns and validation checkpoints.

Discover and inventory ICS/OT assets using Claroty xDome, including passive monitoring, active queries, and integration with CMDB tools.

Search and retrieve past work from claude-mem's persistent cross-session memory database using a three-layer workflow: search, timeline, and fetch.

Documents MariaDB-specific CREATE USER syntax and behavior, including authentication chaining, TLS options, resource limits, password expiry, and account locking, to help write accurate statements.

Connect to Azure Database for PostgreSQL Flexible Server from Node.js/TypeScript using the pg package with support for password and Microsoft Entra ID authentication.

Resolve timezone questions for .NET and C# code with production-safe guidance and copy-paste-ready snippets, including address-to-timezone lookup, cross-platform ID mapping, and DST-safe scheduling.

Security engineering that protects applications, data, and users from real-world threatsUse when "security, authentication, authorization, encryption, OWASP, vulnerability, XSS, SQL injection, CSRF, secrets, password, JWT, OAuth, permissions, audit, compliance, security, authentication, authorization, encryption, vulnerabilities, OWASP, compliance, audit" mentioned.

Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Write, review, debug, test, and optimize Python Polars code with version-grounded object types, schemas, and execution boundaries.

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Expert guidance for Ibis, the Python dataframe library that provides a pandas-like API but generates SQL for execution on any backend — DuckDB, PostgreSQL, BigQuery, Snowflake, Spark, and more. Helps developers write analytics code once and run it anywhere without rewriting SQL for each database.

Process in-memory datasets with Polars' expression API, lazy evaluation, and parallel execution, including pandas migration patterns and I/O for CSV, Parquet, and JSON.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Build on-chain relational databases on Solana using IQ Labs' IQDB, hanLock, and x402 tools, including CRUD operations, tamper-evident rolling hashes, password-based encoding, and payment-gated file inscription.

Aggregate RSS feeds from YouTube, Vimeo, Behance, Twitter/X, Bilibili, Weibo, Douyin, Xiaohongshu, and Zhihu with incremental updates, deduplication, and AI classification.

Analyze datasets to answer defined questions through statistical methods, trend identification, hypothesis testing, and correlation analysis. Use when the user needs evidence-backed findings or decisions from data; use exploratory-data-analysis instead for open-ended first-pass profiling before questions are defined.

Bypass Web Application Firewall protections using encoding techniques, HTTP method manipulation, parameter pollution, and payload obfuscation to deliver SQL injection, XSS, and other attack payloads past WAF detection rules.

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs.

Analyze Base EVM tokens via the deluagent oracle. Pass a contract address or cashtag to receive a flat decision header (action, conviction, entry/stop/size, read) and a full cognition report. Tiered x402 pricing with sequential calls required.