Update: We hired Nancy Amandi!
We are very excited to announce that Catalyst has been selected as a participating organization in Google Season of Docs for 2024! If you’re an interested technical writer, please read our project proposal and follow the application instructions below.
We are seeking technical writers who meet most or all of the following prerequisites:
- A strong sense of organization
- Strong technical writing skills
- Experience with writing docstrings and programming in Python
- Experience using Sphinx and ReadTheDocs to document Python projects
- Familiarity with GitHub
- Ability to work with continuous integration testing
- Energy/power system domain knowledge, experience working in energy or climate fields
If you’d like to apply please send an email to grants@catalyst.coop with the following:
- A CV speaking to relevant experiences and previous work in Python
- A short writing sample
- Your response to the Applicant Documentation Rewrite Question (see below)
- Your availability during the grant period (beginning of May – end of October)
Please submit applications before May 10th. We will read and respond to applications on a rolling basis, so the earlier you can submit an application, the better!
Applicant Documentation Rewrite Question
Please edit, reformat, reorganize, or annotate the following paragraph to improve its readability and clarity:
FERC publishes it’s data (for example FERC Form 1 – Annual Report of Major Electric Utilities) in particular difficult to use formats. From 1994-2020 it used the proprietary FoxPro database binary format. Then in 2021 it switched to XBRL. In addition to using two different difficult to parse file formats, the data itself is unclean and poorly organized. Very few people are currently able to use it. We have not yet integrated the vast majority of the available data into PUDL; its useful to just provide programmatic access to the bulk raw data, independent of the cleaner subset of the data included within PUDL. To provide that access, we’ve broken the pudl.extract.ferc1 process down into several distinct steps: clone the 1994-2020 annual database from FoxPro (DBF) into a local file-based sqlite3 database, clone the 2021 and later data from XBRL into another sqlite3 database, with a different structure, derived from the FERC Form 1 XBRL taxonomy. Finally, select a limited subset of the tables in these databases for further processing and integration into the PUDL sqlite3 database.
The FoxPro / XBRL derived FERC Form 1 databases include 100+ tables, containing 3000+ columns.