pyrcs 0.2.3

A small web scraper for collecting the railway codes used in the UK rail industry

pyrcs

Author: Qian Fu

A small web scraper for collecting railway codes and other data used in the UK rail industry.

Installation

pip install --upgrade pyrcs

Note:

• Make sure you have the most up-to-date version of pip installed.

  python -m pip install --upgrade pip
  

• Python-Levenshtein, one of the dependencies of this package, may fail to be installed on a Windows OS without VC2015 (or above). A workaround is to download and install its .whl file. In this case, you should go for python_Levenshtein-0.12.0-cp37-cp37m-win_amd64.whl if you're using Python 3.7 on 64-bit OS:

  pip install --upgrade \path\to\python_Levenshtein-0.12.0-cp37-cp37m-win_amd64.whl
  

Quick start (Examples)

The following examples may provide a quick guide to the usage of the package.

1. CRS, NLC, TIPLOC and STANOX Codes

If your preferred import style is from <module> import <name>:

from pyrcs.line_data_cls import crs_nlc_tiploc_stanox as ldlc

If your preferred import style is import <module>.<name>:

import pyrcs.line_data_cls.crs_nlc_tiploc_stanox as ldlc

After importing the module, you can create a 'class' for the location codes (including all CRS, NLC, TIPLOC, STANME and STANOX) :

location_codes = ldlc.LocationIdentifiers()

Given different preferences, there are several alternative ways of importing the module.

Alternative 1:

from pyrcs.line_data import crs_nlc_tiploc_stanox as ldlc
location_codes = ldlc.LocationIdentifiers()

Alternative 2 (Preferred and used for the following examples):

from pyrcs.line_data import LineData
line_data_cls = LineData()  # contains all classes under the category of 'Line data'
location_codes = line_data_cls.LocationIdentifiers

1.1 Locations beginning with a given letter

You can get the location codes starting with a specific letter, say 'A' or 'a', by using the methodcollect_location_codes_by_initial, which returns a dict.

# The input is case-insensitive
location_codes_a = location_codes.collect_location_codes_by_initial('A')

The keys of location_codes_a include:

• 'A'
• 'Last_updated_date'
• 'Additional_note'

The corresponding values are:

• location_codes_a['A'] is a pandas.DataFrame that contains the table data. You may compare it with the table on the web page: http://www.railwaycodes.org.uk/crs/CRSa.shtm
• location_codes_a['Last_updated_date'] is the date (in str) when the web page was last updated
• location_codes_a['Additional_note'] is some important additional information on the web page (if available)

1.2 All available location codes in this category

You can also get all available location codes in this category as a whole , using the method fetch_location_codes, which also returns a dict:

location_codes_data = location_codes.fetch_location_codes()

The keys of location_codes_a include:

• 'Location_codes'
• 'Latest_updated_date'
• 'Additional_note'
• 'Other_systems'

The corresponding values are:

• location_codes_data['Location_codes'] is a pandas.DataFrame that contains all table data (from 'A' to 'Z')
• location_codes_data['Latest_updated_date'] is the latest 'Last_updated_date' (in str) among all initial-specific table data
• location_codes_data['Additional_note'] is some important additional information on the web page (if available)
• location_codes_data['Other_systems'] is a dict for Other systems

2. Engineer's Line References (ELRs)

em = line_data_cls.ELRMileages

2.1 ELR codes

To get ELR codes starting with a specific letter, say 'A', by using the method collect_elr_by_initial, which returns a dict.

elr_a = em.collect_elr_by_initial('A')  # em.collect_elr_by_initial('a')

The keys of elr_a include:

• 'A'
• 'Last_updated_date'

The corresponding values are:

• elr_a['A'] is a pandas.DataFrame that contains the table data. You may compare it with the table on the web page: http://www.railwaycodes.org.uk/elrs/elra.shtm
• elr_a['Last_updated_date'] is the date (in str) when the web page was last updated

To get all available ELR codes, by using the method fetch_elr, which returns a dict:

elr_codes = em.fetch_elr()

The keys of elr_codes include:

• 'ELRs_mileages'
• 'Latest_updated_date'

The corresponding values are:

• elr_codes['ELRs_mileages'] is a pandas.DataFrame that contains all table data (from 'A' to 'Z')
• elr_codes['Latest_updated_date'] is the latest 'Last_updated_date' (in str) among all initial-specific table data

2.2 Mileage files

To collect more detailed mileage data for a given ELR, say 'AAM', by using the method fetch_mileage_file, which returns a dict:

em_amm = em.fetch_mileage_file('AAM')

The keys of em_amm include:

• 'ELR'
• 'Line'
• 'Sub-Line'
• 'AAM'

The corresponding values are:

• em_amm['ELR'] is the name (in str) of the given ELR
• em_amm['Line'] is associated line name (in str)
• em_amm['Sub-Line'] is associated sub line name (in str), if available
• em_amm['AAM'] is a pandas.DataFrame of the mileage file data

3. Railway stations data

The data of railway stations belongs to another category, 'Other assets'

from pyrcs.other_assets import OtherAssets
other_assets_cls = OtherAssets()

Similar to getting 'CRS, NLC, TIPLOC and STANOX Codes' above, to get stations data by a given initial letter (say 'A'):

stations_a = other_assets_cls.Stations.collect_station_locations('A')

To get all available stations data:

stations = other_assets_cls.Stations.fetch_station_locations()

The data type of both stations_a and stations are dict.