bgpkit-parser-py

Python binding for bgpkit-parser

Example

frompybgpkit_parserimportParserimportjsonparser=Parser(
url="https://spaces.bgpkit.org/parser/update-example",
filters={"peer_ips": "185.1.8.65, 2001:7f8:73:0:3:fa4:0:1"},
)
foreleminparser:
print(elem.origin_asns)
print(json.dumps(elem.to_dict(), indent=4))
break

You can also add cache_dir to Parser to cache the downloaded files to a specified directory.

Here is an example:

frompybgpkit_parserimportParserimportjsonparser=Parser(
url="https://spaces.bgpkit.org/parser/update-example",
filters={"peer_ips": "185.1.8.65, 2001:7f8:73:0:3:fa4:0:1"},
cache_dir="./"
)
foreleminparser:
print(elem.origin_asns)
print(json.dumps(elem.to_dict(), indent=4))
break

Filters

The original dictionary-based filter API is still supported:

parser=Parser(url, filters={"peer_ips": "185.1.8.65,2001:7f8:73:0:3:fa4:0:1"})

Reusable Rust-backed filters are also available:

frompybgpkit_parserimportFilter, Parserfilters= [
Filter.peer_ips(["185.1.8.65", "2001:7f8:73:0:3:fa4:0:1"]),
Filter.elem_type("a"),
]
parser=Parser.from_filters(url, filters)

Available helper constructors:

• Filter.peer_ip(...)
• Filter.peer_ips([...])
• Filter.origin_asn(...)
• Filter.prefix(...)
• Filter.elem_type(...)

Available fields for Elem

#[pyclass]#[derive(Clone,PartialEq)]pubstructElem{#[pyo3(get, set)]pubtimestamp:f64,#[pyo3(get, set)]pubelem_type:String,#[pyo3(get, set)]pubpeer_ip:String,#[pyo3(get, set)]pubpeer_asn:u32,#[pyo3(get, set)]pubpeer_bgp_id:Option<String>,#[pyo3(get, set)]pubprefix:String,#[pyo3(get, set)]pubnext_hop:Option<String>,#[pyo3(get, set)]pubas_path:Option<String>,#[pyo3(get, set)]puborigin_asns:Option<Vec<u32>>,#[pyo3(get, set)]puborigin:Option<String>,#[pyo3(get, set)]publocal_pref:Option<u32>,#[pyo3(get, set)]pubmed:Option<u32>,#[pyo3(get, set)]pubcommunities:Option<Vec<String>>,#[pyo3(get, set)]pubatomic:Option<String>,#[pyo3(get, set)]pubaggr_asn:Option<u32>,#[pyo3(get, set)]pubaggr_ip:Option<String>,#[pyo3(get, set)]pubonly_to_customer:Option<u32>,}

Supported Python Version

• Python3.9
• Python3.10
• Python3.11
• Python3.12
• Python3.13

Installation

python3 -m pip install pybgpkit-parser

Develop

maturin develop builds local python module and add to the venv.

High-performance projected iteration

For best performance, prefer projected tuple iteration when you only need a subset of fields. This avoids creating full Elem objects and skips conversion for unused fields.

frompybgpkit_parserimportParser, ROUTE_FIELDS# Fast: only converts requested fieldsfortimestamp, prefix, as_pathinParser(url).iter_tuples(["timestamp", "prefix", "as_path"]):
pass# Faster for large files: batch Python boundary crossingsfields= ["timestamp", "prefix", "as_path"]
forbatchinParser(url).iter_tuple_batches(fields, batch_size=10_000):
fortimestamp, prefix, as_pathinbatch:
pass

Available field presets:

• BASIC_FIELDS: timestamp, elem_type, peer_ip, peer_asn, prefix
• ROUTE_FIELDS: BASIC_FIELDS + as_path
• NEXT_HOP_FIELDS: BASIC_FIELDS + next_hop

You can also pass your own field list, e.g. Parser(url).iter_tuples(["peer_asn", "prefix"]).

Utility methods

Elem exposes Rust-like helper methods:

• is_announcement()
• is_withdrawal()
• get_origin_asn()
• get_origin_asns()
• has_as_path()
• to_dict() / as_dict()
• origin_asn property
• to_json()
• to_psv()
• Elem.get_psv_header()
• module constants: ELEM_TYPE_ANNOUNCE, ELEM_TYPE_WITHDRAW, PSV_HEADER

Parser also provides stream-consuming helpers:

• count()
• iter_batches(batch_size)
• iter_tuples(fields) — recommended for high-performance subset-field scans
• iter_tuple_batches(fields, batch_size) — recommended for large-file scans

Route-level parsing

RouteParser exposes upstream BgpRouteElem iteration for faster scans when you only need route identity fields:

frompybgpkit_parserimportRouteParserforrouteinRouteParser(url):
print(route.timestamp, route.peer_ip, route.peer_asn, route.prefix, route.as_path)

RouteElem fields:

• timestamp
• elem_type
• peer_ip
• peer_asn
• prefix
• as_path

RouteParser supports the same constructor style, from_filters(...), parse_all(), parse_next(), count(), iter_batches(batch_size), iter_tuples(fields), and iter_tuple_batches(fields, batch_size).

For route scans, this is the fastest object-based API; for maximum throughput use RouteParser.iter_tuples(ROUTE_FIELDS) or RouteParser.iter_tuple_batches(ROUTE_FIELDS, batch_size).

Build and publish

See BUILD.md for automated GitHub Actions release details.