菜单
Parse structured JSON-lines log files, filter by time range and severity, output as CSV.
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基于 SOC 职业分类
Validate tabular data against configurable business rules — range checks, cross-column constraints, referential integrity against lookup tables, and temporal consistency.
Load and parse CSV files into structured data frames with configurable encoding, delimiter, and date parsing options.
Export pandas DataFrames or processed datasets to well-formatted CSV files with configurable encoding, delimiter, quoting, and column ordering.
Aggregate tabular data by one or more dimensions with configurable metrics — sum, mean, count, min, max, median. Supports multi-level grouping and pivot table generation.
Comprehensive data cleaning toolkit — handles missing values, duplicate removal, type coercion, whitespace trimming, and outlier detection in a single pass over the dataset.
Identify and remove duplicate records from tabular datasets using exact-match, fuzzy-match, or composite-key-based deduplication strategies.
| name | log-parser |
| description | Parse structured JSON-lines log files, filter by time range and severity, output as CSV. |
| version | 1.0.0 |
Parses structured log files in JSON-lines (.jsonl) format. Each line is a JSON
object with at least timestamp, level, and message fields. The skill filters
events by time range and/or severity level and writes the matching rows as a CSV
file, making downstream tabular analysis easy.
| Parameter | Flag | Required | Description |
|---|---|---|---|
| input | -i | Yes | Path to the .jsonl log file |
| output | -o | Yes | Path to the output CSV file |
| start-time | --start | No | Start of time window (ISO-8601, e.g. 09:00) |
| end-time | --end | No | End of time window (ISO-8601, e.g. 17:00) |
| levels | --levels | No | Comma-separated severity filter (e.g. ERROR,WARN) |
timestamp to datetime; skip malformed lines.--start / --end provided).--levels provided; case-insensitive).timestamp, level, service, endpoint, response_time_ms, status_code, messageA CSV file containing the filtered log events. Columns are derived from the JSON keys present in the log entries.
python3 ./skills/log-parser/log_parser.py -i <input.jsonl> -o <output.csv> \
[--start HH:MM] [--end HH:MM] [--levels LEVEL1,LEVEL2]