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flight-sweep

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Mis à jour1 mars 2026 à 01:31

Batch-collect flight data across date ranges and analyze with filtering, scoring, and HTML viewer generation

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varunr89

varunr89/claude-marketplace

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Basé sur la classification professionnelle SOC

Développeurs de logicielsProfessions informatiques et mathématiques·SOC 15-1252

SKILL.md

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name	flight-sweep
description	Batch-collect flight data across date ranges and analyze with filtering, scoring, and HTML viewer generation

Flight Sweep

A two-phase pipeline for comprehensive flight analysis:

Collect (flight_sweep_collect.py) -- Fetches flight data from Google Flights and Duffel API across multiple departure dates and trip configurations. Caches raw API responses to disk.
Analyze (flight_sweep_analyze.py) -- Reads cached data, applies constraint filters, builds trip scenarios, scores and ranks them, and generates an interactive HTML viewer.

When to use

Use this skill when the user wants to do a broad search across multiple departure dates and trip duration options, compare strategies, and generate a comprehensive ranked report.

Phase 1: Data Collection

DUFFEL_API_KEY=<your-key> python3 ${CLAUDE_PLUGIN_ROOT}/scripts/flight_sweep_collect.py

What it does:

Iterates over configured departure dates (Fridays and Saturdays)
For each date, calculates leg dates for all combinations of Europe nights (21/22/23) and India nights (5/6/7)
Searches both one-way flights (Google Flights + Duffel) and round-trip flights (Duffel only)
Caches each API response as a JSON file in flight_cache/
Skips already-cached searches for incremental re-runs
Rate-limits Duffel requests (0.5s delay between calls)

Cache format: {source}_{origin}_{dest}_{date}[_rt_{return_date}].json

Phase 2: Analysis

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/flight_sweep_analyze.py

What it does:

Reads all cached flight data from flight_cache/
Applies constraint filters:
- Max 1 stop per leg
- Max 4-hour layover
- Single carrier per leg
- Excludes test/synthetic airlines (e.g., "Duffel Airways")
Builds scenarios for both strategies (3 one-ways, 2 round-trips)
Scores each scenario: flight_cost + (hours * $20) + (stops * $200) + (weekdays * $200)
Prints top 10 results to terminal
Generates flight_sweep_viewer.html -- an interactive DataTables-powered HTML viewer with sorting and filtering
Saves full results to flight_sweep_results.json

Configuration

Both scripts share these configurable constants:

Constant	Default	Description
`DEPARTURE_DATES`	Apr 24 - May 8, 2026	List of departure dates to search
`EUROPE_NIGHTS_OPTIONS`	[21, 22, 23]	Europe stay duration options
`INDIA_NIGHTS_OPTIONS`	[5, 6, 7]	India stay duration options
`MAX_STOPS`	1	Maximum stops per leg
`MAX_LAYOVER_HOURS`	4	Maximum layover duration in hours
`COST_PER_HOUR`	20	Scoring penalty per hour of travel
`COST_PER_STOP`	200	Scoring penalty per stop
`COST_PER_WEEKDAY`	200	Scoring penalty per weekday away

Environment variables

Variable	Required	Description
`DUFFEL_API_KEY`	Yes (collect phase)	Duffel API access token

Dependencies

requests (pip install requests) -- Duffel API calls
fast-flights (pip install fast-flights) -- Optional Google Flights scraper

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name	flight-sweep
description	Batch-collect flight data across date ranges and analyze with filtering, scoring, and HTML viewer generation

Flight Sweep

A two-phase pipeline for comprehensive flight analysis:

Collect (flight_sweep_collect.py) -- Fetches flight data from Google Flights and Duffel API across multiple departure dates and trip configurations. Caches raw API responses to disk.
Analyze (flight_sweep_analyze.py) -- Reads cached data, applies constraint filters, builds trip scenarios, scores and ranks them, and generates an interactive HTML viewer.

When to use

Use this skill when the user wants to do a broad search across multiple departure dates and trip duration options, compare strategies, and generate a comprehensive ranked report.

Phase 1: Data Collection

DUFFEL_API_KEY=<your-key> python3 ${CLAUDE_PLUGIN_ROOT}/scripts/flight_sweep_collect.py

What it does:

Iterates over configured departure dates (Fridays and Saturdays)
For each date, calculates leg dates for all combinations of Europe nights (21/22/23) and India nights (5/6/7)
Searches both one-way flights (Google Flights + Duffel) and round-trip flights (Duffel only)
Caches each API response as a JSON file in flight_cache/
Skips already-cached searches for incremental re-runs
Rate-limits Duffel requests (0.5s delay between calls)

Cache format: {source}_{origin}_{dest}_{date}[_rt_{return_date}].json

Phase 2: Analysis

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/flight_sweep_analyze.py

What it does:

Reads all cached flight data from flight_cache/
Applies constraint filters:
- Max 1 stop per leg
- Max 4-hour layover
- Single carrier per leg
- Excludes test/synthetic airlines (e.g., "Duffel Airways")
Builds scenarios for both strategies (3 one-ways, 2 round-trips)
Scores each scenario: flight_cost + (hours * $20) + (stops * $200) + (weekdays * $200)
Prints top 10 results to terminal
Generates flight_sweep_viewer.html -- an interactive DataTables-powered HTML viewer with sorting and filtering
Saves full results to flight_sweep_results.json

Configuration

Both scripts share these configurable constants:

Constant	Default	Description
`DEPARTURE_DATES`	Apr 24 - May 8, 2026	List of departure dates to search
`EUROPE_NIGHTS_OPTIONS`	[21, 22, 23]	Europe stay duration options
`INDIA_NIGHTS_OPTIONS`	[5, 6, 7]	India stay duration options
`MAX_STOPS`	1	Maximum stops per leg
`MAX_LAYOVER_HOURS`	4	Maximum layover duration in hours
`COST_PER_HOUR`	20	Scoring penalty per hour of travel
`COST_PER_STOP`	200	Scoring penalty per stop
`COST_PER_WEEKDAY`	200	Scoring penalty per weekday away

Environment variables

Variable	Required	Description
`DUFFEL_API_KEY`	Yes (collect phase)	Duffel API access token

Dependencies

requests (pip install requests) -- Duffel API calls
fast-flights (pip install fast-flights) -- Optional Google Flights scraper