14 KiB
14 KiB
wttr.in Data Flow Documentation
Request Processing Flow
1. Initial Request
Client → Go Proxy (port 8082)
Input:
- HTTP request with location in URL
- Headers: User-Agent, Accept-Language, X-Forwarded-For
- Query parameters
Go Proxy Actions:
- Extract cache key:
UserAgent:Host+URI:ClientIP:AcceptLanguage - Check if request is cacheable (no
:in location) - Look up in LRU cache (12,800 entries)
Cache Hit Path:
Go Proxy → Check expiry → Return cached response
Cache Miss Path:
Go Proxy → Set InProgress flag → Forward to Python Backend
2. Python Backend Processing
Go Proxy → Python Backend (port 8002) → Flask Router
Flask Routes:
/→wttr_srv.wttr(None, request)/{location}→wttr_srv.wttr(location, request)/:help,/:bash.function, etc. → Static file handlers
3. Request Parsing (wttr_srv.py)
Phase 1: Fast Path (Cache + Static)
parse_request(location, request, query, fast_mode=True)
↓
_response(parsed_query, query, fast_mode=True)
↓
Check Python LRU cache
↓
Check if static page (:help, :bash.function, etc.)
↓
Return if found, else continue to slow path
Phase 2: Full Processing
parse_request(location, request, query, fast_mode=False)
↓
Location Processing
↓
_response(parsed_query, query, fast_mode=False)
↓
Render weather
↓
Cache and return
4. Location Processing (location.py)
Input: Location string, Client IP
Processing Steps:
1. Detect location type
├─ Empty/MyLocation → Use client IP
├─ IP address → Resolve to location
├─ @domain → Resolve domain to IP, then location
├─ ~search → Use geolocator service
├─ Moon → Special moon handler
└─ Name → Use as-is
2. Normalize location
├─ Lowercase
├─ Replace _ and + with space
└─ Remove special chars (!@#$*;:\)
3. Check aliases (share/aliases)
└─ from:to mapping
4. Check blacklist (share/blacklist)
└─ Return 403 if blocked
5. Resolve location
├─ IP → Location (GeoIP/IP2Location/IPInfo)
├─ Name → GPS coords (Geolocator service)
└─ IATA code → Airport location
6. Get hemisphere (for moon queries)
└─ GPS latitude > 0 = North
Output:
location- Normalized location or GPS coordsoverride_location_name- Display namefull_address- Full address from geolocatorcountry- Country namequery_source_location- Client's location (city, country)hemisphere- True=North, False=South
5. IP to Location Resolution
Method Priority (configurable via WTTR_IPLOCATION_ORDER):
1. GeoIP (MaxMind GeoLite2)
├─ Read from GeoLite2-City.mmdb
├─ Extract city and country
└─ Fast, local, free
2. IP2Location API (optional)
├─ HTTP GET to api.ip2location.com
├─ Requires API key (~/.ip2location.key)
├─ Cache result in /wttr.in/cache/ip2l/{ip}
└─ Format: city;country
3. IPInfo API (optional)
├─ HTTP GET to ipinfo.io
├─ Requires token (~/.ipinfo.key)
├─ Cache result in /wttr.in/cache/ip2l/{ip}
└─ JSON response
Fallback: NOT_FOUND_LOCATION ("not found")
Caching:
- File cache:
/wttr.in/cache/ip2l/{ip_address} - Format:
city;countryorlocation;country;extra;city - Persistent across restarts
6. Geolocator Service
For search terms (~location) and non-ASCII names:
Python Backend → HTTP GET localhost:8004/{location}
↓
Geolocator Service (separate microservice)
↓
Returns JSON:
{
"latitude": 48.8582602,
"longitude": 2.29449905432,
"address": "Tour Eiffel, 5, Avenue Anatole France..."
}
Used for:
~Eiffel Tower→ GPS coordinates~Kilimanjaro→ GPS coordinates- Non-ASCII location names
- IATA airport codes
7. Weather Data Fetching
Two data sources (configured via WWO_KEY):
Option A: met.no (Norwegian Meteorological Institute)
Python Backend → metno.py
↓
HTTP GET to api.met.no
↓
Parse XML/JSON response
↓
Transform to standard JSON format
↓
Return weather data
Advantages:
- Free, no API key required
- High quality data
- No rate limits
Option B: WorldWeatherOnline (WWO)
Python Backend → bin/proxy.py (separate service)
↓
Check proxy cache (/wttr.in/cache/proxy-wwo/)
↓
If miss: HTTP GET to api.worldweatheronline.com
↓
Cache response
↓
Return weather data
Advantages:
- More locations supported
- Historical data available
Disadvantages:
- Requires API key (~/.wwo.key)
- Rate limited (500 queries/day free tier)
Weather Data Structure:
{
"current_condition": [{
"temp_C": "22",
"temp_F": "72",
"weatherCode": "122",
"weatherDesc": [{"value": "Overcast"}],
"windspeedKmph": "7",
"humidity": "76",
...
}],
"weather": [
{
"date": "2025-12-17",
"maxtempC": "25",
"mintempC": "18",
"hourly": [...]
}
]
}
8. Weather Rendering
Route to appropriate renderer based on query:
parsed_query → Determine view type
↓
├─ format=1,2,3,4 → view/line.py (one-line format)
├─ format=j1 → Return raw JSON
├─ format=p1 → view/prometheus.py
├─ format=v2 → view/v2.py (data-rich)
├─ location=Moon → view/moon.py
└─ default → view/wttr.py (main view)
Main View (view/wttr.py)
get_wetter(parsed_query)
↓
Call wego binary (Go program)
├─ Pass flags: -city, -lang, -imperial, -narrow, etc.
├─ wego fetches weather data
├─ wego renders ANSI output
└─ Return ANSI text
↓
Post-process output
├─ Add location name override
├─ Add "not found" message if needed
└─ Format for display
↓
If HTML output:
└─ Convert ANSI to HTML (ansi2html.sh)
wego Command Example:
/path/to/we-lang \
--city=London,GB \
-lang=en \
-imperial \
-narrow \
-location_name="London"
One-Line View (view/line.py)
wttr_line(query, parsed_query)
↓
Get weather data (JSON)
↓
Parse format string
├─ Predefined: 1, 2, 3, 4
└─ Custom: %c, %t, %h, %w, etc.
↓
Replace format codes with data
├─ %c → Weather emoji
├─ %t → Temperature
├─ %h → Humidity
└─ etc.
↓
Return formatted string
Format Examples:
format=3→London: ⛅️ +7°Cformat=%l:+%c+%t→London: ⛅️ +7°C
Moon View (view/moon.py)
get_moon(parsed_query)
↓
Parse date from location (Moon@2016-12-25)
↓
Call pyphoon-lolcat binary
├─ Pass date parameter
└─ Return ASCII moon phase art
↓
Return moon phase output
v2 View (view/v2.py)
Experimental data-rich format
↓
Get weather data
↓
Render:
├─ Temperature graph (ASCII)
├─ Precipitation graph (ASCII)
├─ Moon phases (4 days)
├─ Current conditions (detailed)
├─ Astronomical times (dawn, sunrise, etc.)
└─ GPS coordinates
↓
Return formatted output
Prometheus View (view/prometheus.py)
Get weather data (JSON)
↓
Convert to Prometheus metrics format
├─ temperature_feels_like_celsius{forecast="current"} 7
├─ humidity_percent{forecast="current"} 65
└─ etc.
↓
Return metrics text
9. PNG Rendering (fmt/png.py)
For .png requests:
ANSI text output
↓
Spawn thread (ThreadPool, 25 workers)
↓
render_ansi(output, options)
↓
Create virtual terminal (pyte)
├─ Feed ANSI sequences
└─ Capture terminal state
↓
Render to image (PIL)
├─ Draw characters with font
├─ Apply colors from ANSI codes
└─ Apply transparency if requested
↓
Return PNG bytes
↓
Cache in /wttr.in/cache/png/
Options:
t- Transparency (150)transparency={0-255}- Custom transparency{width}x{height}- Image dimensions
10. Translation (translations.py)
Language Detection:
1. Check subdomain (de.wttr.in → lang=de)
2. Check lang parameter (?lang=de)
3. Check Accept-Language header
4. Default to English
Translation Files:
share/translations/{lang}.txt- Weather conditionsshare/translations/{lang}-help.txt- Help pages
Translation Process:
Weather condition text (English)
↓
Look up in translations.py:TRANSLATIONS dict
↓
Find translation for target language
↓
Return translated text
Example:
TRANSLATIONS = {
"en": {"Partly cloudy": "Partly cloudy"},
"de": {"Partly cloudy": "Teilweise bewölkt"},
"fr": {"Partly cloudy": "Partiellement nuageux"}
}
11. Caching (cache.py)
Python LRU Cache:
Request → Generate cache signature
↓
signature = f"{user_agent}:{query_string}:{client_ip}:{lang}"
↓
Check in-memory LRU (10,000 entries)
↓
If found and not expired:
├─ If value starts with "file:" or "bfile:"
│ └─ Read from /wttr.in/cache/lru/{md5_hash}
└─ Return value
↓
If not found:
├─ Generate response
├─ If response > 80 bytes:
│ ├─ Write to /wttr.in/cache/lru/{md5_hash}
│ └─ Store "file:{md5_hash}" in LRU
└─ Else: Store value directly in LRU
↓
Set expiry: current_time + random(1000, 2000) seconds
↓
Return response
Dynamic Timestamps:
Cached response with %{{NOW(timezone)}}
↓
On retrieval: Replace with current time in timezone
↓
Example: %{{NOW(Europe/London)}} → 14:32:15+0000
12. Response Wrapping
Final response preparation:
Response text/bytes
↓
Determine content type
├─ PNG → image/png
├─ HTML → text/html
└─ ANSI/text → text/plain
↓
Add buttons (if HTML and not format query)
├─ Add interactive UI elements
└─ Wrap in HTML template
↓
Set HTTP headers
├─ Content-Type
├─ Cache-Control (PNG only)
└─ Access-Control-Allow-Origin: *
↓
Return Flask response
13. Go Proxy Caching
After Python backend returns:
Python Backend → Response
↓
Go Proxy receives response
↓
If status code 200 or 304:
├─ Store in LRU cache
├─ Set expiry: current_time + random(1000, 1500) seconds
└─ Remove InProgress flag
↓
Else (error):
└─ Remove from cache
↓
Return response to client
14. Peak Request Prefetching
Cron-based prefetching:
Every hour at :30 and :00
↓
Record incoming requests in sync.Map
↓
At :24 and :54 (5 minutes before peak)
↓
Iterate through recorded requests
↓
For each request:
├─ Spawn goroutine
├─ Call processRequest() (refreshes cache)
├─ Sleep (spread over 300 seconds)
└─ Delete from sync.Map
↓
Cache is warm for peak time
Peak Times:
- :30 past the hour (recorded at :30, prefetched at :24)
- :00 on the hour (recorded at :00, prefetched at :54)
Data Structures
Parsed Query
{
"location": "London,GB", # Normalized location
"orig_location": "London", # Original input
"override_location_name": None, # Display name override
"full_address": "London, UK", # Full address
"country": "GB", # Country code
"query_source_location": ("Paris", "France"), # Client location
"hemisphere": True, # North=True, South=False
"lang": "en", # Language code
"view": None, # View type (v2, etc.)
"html_output": False, # HTML vs ANSI
"png_filename": None, # PNG filename if .png request
"ip_addr": "1.2.3.4", # Client IP
"user_agent": "curl/7.68.0", # User agent
"request_url": "http://...", # Full request URL
# Query options
"use_metric": True, # Metric units
"use_imperial": False, # Imperial units
"use_ms_for_wind": False, # m/s for wind
"narrow": False, # Narrow output
"inverted_colors": False, # Inverted colors
"no-terminal": False, # Plain text
"no-caption": False, # No caption
"no-city": False, # No city name
"no-follow-line": False, # No follow line
"days": "3", # Number of days
"transparency": None, # PNG transparency
"padding": False, # Add padding
"force-ansi": False, # Force ANSI
}
Cache Entry (Go)
type responseWithHeader struct {
InProgress bool // Request being processed
Expires time.Time // Expiration time
Body []byte // Response body
Header http.Header // HTTP headers
StatusCode int // HTTP status code
}
Cache Entry (Python)
{
"val": "response text" or "file:md5hash",
"expiry": 1702834567.123 # Unix timestamp
}
Error Handling Flow
Location Not Found
Location resolution fails
↓
Set location = NOT_FOUND_LOCATION ("not found")
↓
Fetch weather for default location (Oymyakon)
↓
Append "not found" message in user's language
↓
Return response
API Error
Weather API returns error
↓
Log error
↓
If HTML output:
└─ Return malformed-response.html (500)
Else:
└─ Return "capacity limit reached" message (503)
Rate Limit Exceeded
Check IP against limits (300/min, 3600/hour, 86400/day)
↓
If exceeded:
└─ Return 429 with error message
Blocked Location
Check location against blacklist
↓
If blocked:
└─ Return 403 Forbidden
Performance Optimizations
- Two-tier caching (Go + Python)
- Fast path (cache + static files checked first)
- File cache for large responses (>80 bytes)
- Prefetching at peak times
- ThreadPool for PNG rendering (25 workers)
- Gevent for async I/O in Python
- LRU eviction prevents memory bloat
- Randomized TTL prevents thundering herd
- InProgress flag prevents duplicate work
- IP location caching (persistent file cache)