Results for “pyshark”

Analyze network packet captures (PCAP/PCAPNG) using Wireshark, tshark, tcpdump, and Python to reconstruct communications, extract files, and identify malicious traffic.

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events, extract artifacts, and identify malicious communications.

Write, review, debug, test, or optimize Python code using PyArrow arrays, schemas, tables, compute kernels, datasets, Parquet, and Arrow IPC.

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

Generate Python SDK setup, CRUD, bulk, and paging snippets for Microsoft Dataverse using official patterns.

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Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

嵌入式网络调试工具，用于发现接口、抓包、分析 pcap/pcapng、做连通性测试、端口扫描和流量统计。 当用户提到 Wireshark、tshark、Npcap、抓包、网络联调、端口扫描、连通性排查、pcap 分析、 网络接口、ping 测试、traceroute、流量统计、Modbus TCP、EtherNet/IP 等网络协议调试时自动触发， 也兼容 /net 显式调用。即使用户只是说"抓个包看看"、"扫一下端口"、"网络通不通"或"分析一下这个 pcap"， 只要上下文中出现具体工具名（tshark、Wireshark、Npcap）、协议名（Modbus TCP、EtherNet/IP、ICMP 等）、 调试动作（抓包、端口扫描、连通性测试、ping、traceroute、流量统计、pcap 分析）或网络接口操作，就应触发此 skill。

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.

Apply image blur effects and privacy masks using Python PIL processing. Use when you need to blur, redact faces, or mask sensitive regions in images.

Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.

Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

朴树（音乐人）认知与表达框架（压缩蒸馏）：内向真诚、少话多留白、生命与创作一体… 触发：平凡之路 等。不消费抑郁；非医疗建议

Applies senior Python rules for typing, async, APIs, persistence, tests, packaging, and architecture.

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.