cifparse is a parser for the Coded Instrument Flight Procedures file, released every 28 days by the FAA. It allows pilots, dispatchers, and others interested in flight data to quickly parse the file into Python dictionaries or a SQLite database for use in other programs. For example, the parsed data can then be used to draw maps of the flight paths, individual named points, or airspace.
If you are interested in the mapping aspect, have a look at FacilityMapper.
| Version | Description | Release Date |
|---|---|---|
| 2.0.9 | Bugfix for missing vert_angle in procedure_points records. |
2025-11-07 |
| 2.0.8 | Bugfix for incorrect lat/lon parse in controlled_points records. |
2025-10-23 |
| 2.0.7 | Bugfix for incorrect time scale in dist_time field. |
2025-08-20 |
| 2.0.6 | Bugfix for missing time field in procedure_points. |
2025-08-20 |
| 2.0.5 | Section parsing fixes. | 2025-06-21 |
| 2.0.4 | Field parsing fixes. | 2025-06-18 |
| 2.0.3 | NDB Parsing bugfix. | 2025-06-18 |
| 2.0.2 | Build bugfix. | 2025-05-25 |
| 2.0.1 | Minor fixes to internal module handling. | 2025-05-25 |
| 2.0.0 | Major update. See MIGRATION.md for details. | 2025-05-22 |
| 1.0.1 | Minor fixes to SQL statements. | 2025-04-24 |
| 1.0.0 | Updated table handling to include additional detail and data types. | 2024-12-11 |
| 0.9.3 | Updated procedure handling (breaking changes) and database support. | 2024-11-15 |
| 0.9.2 | Minor fixes. | 2024-07-13 |
| 0.9.0 | Initial public release. | 2024-07-13 |
A changelog is available in the CHANGELOG.md with additional detail and guidance.
Install using pip:
pip install cifparse
Usage is relatively straightforward. Setting the path to the file can be somewhat finnicky, as it will only accept relative paths. To keep things simple, place the CIFP file in your project directory. Otherwise, if you want to go up several folders into a download folder, it might end up looking like ../../../../Downloads/FAACIFP18.
Given the amount of data, parsing can take a moment. If dumping the data to a file, that can also add time. Dumping every airport to JSON can take around 15 seconds, and the resulting file is about 330MB.
Start by importing cifparse, setting the path to the CIFP file, and then parsing the data.
import cifparse
# Initialize the parser:
from cifparse import CIFP
# Set the relative path to where you have the CIFP file:
c = CIFP("FAACIFP18")
# Parse the data in the file:
c.parse()
# ...or parse only a specific subset by using any combination of the following:
c.parse_moras()
c.parse_vhf_navaids()
c.parse_ndb_navaids()
c.parse_enroute_waypoints()
c.parse_airway_markers()
c.parse_holds()
c.parse_airway_points()
c.parse_preferred_routes()
c.parse_airway_restrictions()
c.parse_enroute_comms()
c.parse_heliports()
c.parse_heli_terminal_waypoints()
c.parse_heli_procedures()
c.parse_heli_taas()
c.parse_heli_msas()
c.parse_heli_terminal_comms()
c.parse_airports()
c.parse_gates()
c.parse_terminal_waypoints()
c.parse_procedures()
c.parse_runways()
c.parse_loc_gss()
c.parse_company_routes()
c.parse_alternate_records()
c.parse_taas()
c.parse_mlss()
c.parse_terminal_markers()
c.parse_path_points()
c.parse_flight_plannings()
c.parse_msas()
c.parse_glss()
c.parse_terminal_comms()
c.parse_cruise_tables()
c.parse_reference_tables()
c.parse_controlled()
c.parse_fir_uir()
c.parse_restrictive()After parsing the data, the results will be in the CIFP object, accessible via getters that return lists of the objects.
all_moras = c.get_moras()
all_vhf_navaids = c.get_vhf_navaids()
all_ndb_navaids = c.get_ndb_navaids()
all_enroute_waypoints = c.get_enroute_waypoints()
all_airway_markers = c.get_airway_markers()
all_holds = c.get_holds()
all_airway_points = c.get_airway_points()
all_preferred_routes = c.get_preferred_routes()
all_airway_restrictions = c.get_airway_restrictions()
all_enroute_comms = c.get_enroute_comms()
all_heliports = c.get_heliports()
all_heli_terminal_waypoints = c.get_heli_terminal_waypoints()
all_heli_procedures = c.get_heli_procedures()
all_heli_taas = c.get_heli_taas()
all_heli_msas = c.get_heli_msas()
all_heli_terminal_comms = c.get_heli_terminal_comms()
all_airports = c.get_airports()
all_gates = c.get_gates()
all_terminal_waypoints = c.get_terminal_waypoints()
all_procedures = c.get_procedures()
all_runways = c.get_runways()
all_loc_gss = c.get_loc_gss()
all_company_routes = c.get_company_routes()
all_alternate_records = c.get_alternate_records()
all_taas = c.get_taas()
all_mlss = c.get_mlss()
all_terminal_markers = c.get_terminal_markers()
all_path_points = c.get_path_points()
all_flight_plannings = c.get_flight_plannings()
all_msas = c.get_msas()
all_terminal_comms = c.get_terminal_comms()
all_fir_uir = c.get_fir_uir()
all_cruise_tables = c.get_cruise_tables()
all_reference_tables = c.get_reference_tables()
all_controlled = c.get_controlled()
all_restrictive = c.get_restrictive()Each object has its own to_dict() method. This is useful when you need to dump the data to json:
from cifparse import CIFP
import json
c = CIFP("FAACIFP18")
c.parse_airports()
airports = c.get_airports()
airport_dicts = [item.to_dict() for item in airports]
with open("output.json", "w") as json_file:
json.dump(airport_dicts, json_file, indent=2)Each object has its own to_db() method. This is useful when you would like the data to persist, or query it using standard database methods:
c = CIFP("FAACIFP18")
c.parse()
c.to_db("FAACIFP18.db")NOTE: The resulting tables are somewhat less-optimally normalized than they could be. This is mostly to allow flexibility in querying. For example, the airway_points table can be queried directly to retrieve all points on the airways, or a summary can be found on airways in a way similar to using SELECT DISTINCT ... on a subset of fields. Airspace follows a similar principle.
A breakdown of the different objects can be found in the Docs directory.