Research output per year
Research output per year
Abstract
PyRCS is an open-source Python package that simplifies the collection and management of railway codes used across different systems in the UK rail industry. It provides a practical toolkit for researchers, practitioners and frequent users of the Railway Codes website who work extensively with railway codes in the UK. By leveraging Python's capabilities, PyRCS enables efficient access, retrieval and manipulation of railway code data, enhancing productivity and effectiveness in working with these codes.
During installation, PyRCS includes a set of pre-packaged data. When users request data from a specific category on the Railway Codes website, PyRCS loads the corresponding pre-packaged data for that category by default. Additionally, it provides functionality for direct access to the latest data from the source website, ensuring users stay up to date. Users can also update the pre-packaged data as needed, keeping their resources synchronized with the latest developments.
With PyRCS, users can leverage Python's power to streamline workflows and enhance productivity when working with railway codes in the UK rail industry.
During installation, PyRCS includes a set of pre-packaged data. When users request data from a specific category on the Railway Codes website, PyRCS loads the corresponding pre-packaged data for that category by default. Additionally, it provides functionality for direct access to the latest data from the source website, ensuring users stay up to date. Users can also update the pre-packaged data as needed, keeping their resources synchronized with the latest developments.
With PyRCS, users can leverage Python's power to streamline workflows and enhance productivity when working with railway codes in the UK rail industry.
| Original language | English |
|---|---|
| Publisher | Zenodo |
| Media of output | Online |
| DOIs | |
| Publication status | Published - 2020 |
Keywords
- Python
- Railway codes
- Railway
- Bridges
- CRS
- NLC
- TIPLOC
- STANOX
- Electrification
- ELR and Mileage
- LOR
- Stations
- Signal boxes
- Tunnels
- Viaducts
- Depots
- Tracks
Fingerprint
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Development of an Integrated Computing Platform for Measuring, Predicting, and Analyzing the Profile-Specific Fixity of Railway Tracks
Fu, Q., Easton, J. & Burrow, M., Jun 2024, In: Transportation Research Record. 2678, 6, p. 1-13 13 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile107 Downloads (Pure) -
PyDriosm: an open-source tool for downloading, reading and PostgreSQL-based I/O of OpenStreetMap data
Fu, Q., 2020Research output: Non-textual form › Software
Open Access -
PyHelpers: An open-source toolkit for facilitating Python users' data manipulation tasks
Fu, Q., 2020Research output: Non-textual form › Software
Open Access -
A data model for heat-related rail buckling: implications for operations, maintenance and long-term adaptation
Jaroszweski, D., Fu, Q. & Easton, J., 1 Aug 2019, (Accepted/In press) Proceedings of the 12th World Congress on Railway Research. 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile -
A data model for prediction of weather-related rail incidents: a case-study example of wind-related incidents on the rail network in Great Britain
Fu, Q. & Easton, J., 5 Jan 2018. 12 p.Research output: Contribution to conference (unpublished) › Paper › peer-review
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A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain
Fu, Q., Jaroszweski, D. & Easton, J., 25 Jun 2018, Proceedings of the 8th International Conference on Railway Engineering (ICRE 2018). Institution of Engineering and Technology, 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Prediction of weather-related incidents on the rail network: prototype data model for wind-related delays in Great Britain
Fu, Q. & Easton, J., Sept 2018, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 4, 3, 12 p., 04018027.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Citations (Scopus)427 Downloads (Pure)
Projects
- 2 Finished
-
Forecasting resilience of railway network under propagating uncertainty
Fu, Q. (Principal Investigator) & Mills, S. (Co-Investigator)
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/04/24 → 31/12/24
Project: Research Councils
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Post-Doctoral Enrichment Award
Styles, I. (Principal Investigator), Chu, M. (Co-Investigator), Chua, W. W. L. (Co-Investigator) & Fu, Q. (Co-Investigator)
1/03/22 → 31/10/22
Project: Research