a python parser for the .fec file format
Project description
This is a library for converting campaign finance filings stored in the .fec format into native python objects. It maps the comma/ASCII 28 delimited fields to canonical names based on the version the filing uses and then converts the values that are dates and numbers into the appropriate int
, float
, or datetime
objects.
This library is in relatively early testing. I've used it on a couple of projects, but I wouldn't trust it to work on all filings. That said, if you do try using it, I'd love to hear about it!
Why?
The FEC makes a ton of data available via the "export" links on the main site and the developer API. For cases where those data sources are sufficient, they are almost certainly the easiest/best way to go. A few cases where one might need to be digging into raw filings are:
-
Getting information from individual itemizations including addresses
-
Getting data as soon as it has been filed, instead of waiting for it to be coded. (The FEC generally codes all filings received by 7pm eastern by 7am the next day. However, that means that a filing received at 11:59pm on Monday wouldn't be available until 7am on Wednesday, for example.)
-
Getting more data than the rate-limit on the developer API would allow
-
Maintaining ones own database with all relevant campaign finance data, perhaps synced with another data source
Raw filings can be found by either downloading the bulk data zip files or from http requests like this. This library includes helper methods for both.
Installation
To get started, install from pypi by running the following command in your preferred terminal:
pip install fecfile
Usage
For the vast majority of filings, the easiest way to use this library will be to load filings all at once by using the from_http(file_number)
, from_file(file_path)
, or loads(input)
methods.
These methods will return a Python dictionary, with keys for header
, filing
, itemizations
, and text
. The itemizations
dictionary contains lists of itemizations grouped by type (Schedule A
, Schedule B
, etc.).
Examples:
import fecfile
import json
filing1 = fecfile.from_file('1229017.fec')
print(json.dumps(filing1, sort_keys=True, indent=2, default=str))
filing2 = fecfile.from_http(1146148)
print(json.dumps(filing2, sort_keys=True, indent=2, default=str))
with open('1229017.fec') as file:
parsed = fecfile.loads(file.read())
print(json.dumps(parsed, sort_keys=True, indent=2, default=str))
url = 'http://docquery.fec.gov/dcdev/posted/1229017.fec'
r = requests.get(url, headers={'User-Agent': 'Mozilla/5.0'})
parsed = fecfile.loads(r.text)
print(json.dumps(parsed, sort_keys=True, indent=2, default=str))
Note #1: the default=str
parameter allows serializing to json for dictionaries like the ones returned by the fecfile
library that contain datetime
objects.
Note #2: the docquery.fec.gov urls cause problems with the requests library when a user-agent is not supplied. There may be a cleaner fix to that though.
Advanced Usage
For some large filings, loading the entire filing into memory like the above examples do would not be a good idea. For those cases, the fecfile
library provides methods for parsing filings one line at a time.
import fecfile
version = None
with open('1263179.fec') as file:
for line in file:
if version is None:
header, version = fecfile.parse_header(line)
else:
parsed = fecfile.parse_line(line, version)
save_to_db(parsed)
API Reference
loads
loads(input)
Deserialize input
(a str
instance
containing an FEC document) to a Python object.
parse_header
parse_header(hdr)
Deserialize a str
or a list of str
instances containing
header information for an FEC document. Returns an Python object, the
version str
used in the document, and the number of lines used
by the header.
The third return value of number of lines used by the header is only
useful for versions 1 and 2 of the FEC file format, when the header
was a multiline string beginning and ending with /*
. This allows
us to pass in the entire contents of the file as a list of lines and
know where to start parsing the non-header lines.
parse_line
parse_line(line, version, line_num=None)
Deserialize a line
(a str
instance
containing a line from an FEC document) to a Python object.
version
is a str
instance for the version of the FEC file format
to be used, and is required.
line_num
is optional and is used for debugging. If an error or
warning is encountered, whatever is passed in to line_num
will be
included in the error/warning message.
from_http
from_http(file_number)
Utility method for getting a parsed Python representation of an FEC
filing when you don't already have it on your computer. This method takes
either a str
or int
as a file_number
and requests it from
the docquery.fec.gov
server, then parses the response.
from_file
from_file(file_path)
Utility method for getting a parsed Python representation of an FEC
filing when you have the .fec file on your computer. This method takes
a str
of the path to the file, and returns the parsed Python object.
print_example
print_example(parsed)
Utility method for debugging - prints out a representative subset of
the Python object returned by one of the deserialization methods. For
filings with itemizations, it only prints the first of each type of
itemization included in the object.
Developing locally
Assuming you already have Python3 and the ability to create virtual environments installed, first clone this repository from github and cd into it:
git clone https://github.com/esonderegger/fecfile.git
cd fecfile
Then create a virtual environment for this project (I use the following commands, but there are several ways to get the desired result):
python3 -m venv ~/.virtualenvs/fecfile
source ~/.virtualenvs/fecfile/bin/activate
Next, install the dependencies:
python setup.py
Finally, make some changes, and run:
python tests.py
Thanks
This project would be impossible without the work done by the kind folks at The New York Times Newsdev team. In particular, this project relies heavily on fech although it actually uses a transformation of this fork.
Contributing
I would love some help with this, particularly with the mapping from strings to int
, float
, and datetime
types. Please create an issue or make a pull request. Or reach out privately via email - that works too.
To do:
Almost too much to list:
-
Handle files from before v6 when they were comma-delimited -
create a
dumps
method for writing .fec files for round-trip tests -
add more types to the types.json file
-
elegantly handle errors
Changes
0.4.10 (November 7, 2018)
-
strip whitespace when parsing values as float or date
-
fix mis-mapped field in paper F3 filings
0.4.9 (November 6, 2018)
- add mappings for paper versions of F24
0.4.8 (November 6, 2018)
-
fix v5/3 mapping for F3P to include v1 and v2
-
make F5 mappings more explicit and include v6.1
-
add types for F3S
0.4.7 (November 2, 2018)
-
add types for F4, SF, and SL
-
fix issue causing incorrect mapping for F9
0.4.6 (October 29, 2018)
-
add mappings for paper versions of F4
-
add mappings for paper versions of F56
-
add mappings for paper versions of F91
-
add mappings for paper versions of F92
-
add mappings for paper versions of F93
-
add mappings for paper versions of F94
-
add mappings for paper versions of F99
-
add mappings for paper versions of H5 and H6
-
add mappings for paper versions of Schedule L
-
add mapping for version P3.4 for F3Z1 and F3Z2
0.4.5 (October 27, 2018)
- add mappings for paper versions of F3Z
0.4.4 (October 17, 2018)
- fixed out of order mappings for paper versions of F3
0.4.3 (October 10, 2018)
-
add mappings for paper versions of F76
-
add mappings for paper versions of F9
-
add mappings for paper versions of F2
-
add mappings for paper versions of F7
0.4.2 (October 9, 2018)
-
add mappings for paper versions of F57
-
add mappings for paper versions of F5
-
add mappings for paper versions of F3L
-
add mappings for paper versions of F3S
0.4.1 (October 4, 2018)
-
add mappings for versions P1 and P2 of Schedule B
-
add mappings for versions P1 and P2 of Schedule A
-
add mappings for versions P1 and P2 of F3
-
add F99_text field to returned object for form 99 filings
-
add hdr mappings for paper versions 1 and 2
-
do not split on commas when we know the form is using ascii 28
-
add mappings for paper versions of F65
-
add mappings for paper versions of schedule C1
-
add mappings for paper versions of schedule C2
-
add mappings for paper versions of schedule E
0.4.0 (October 2, 2018)
-
Updated documentation
-
add paper versions for schedule F
0.3.9 (October 1, 2018)
- add paper versions for H1, H2, H3, and H4
0.3.8 (September 28, 2018)
- add paper versions for the F1S
0.3.7 (September 27, 2018)
-
add paper versions of F1M
-
add paper versions for F3X
-
add F3P paper filing mappings
0.3.6 (September 27, 2018)
- add F6 paper mappings and fix missing commas
0.3.5 (September 26)
- add all paper versions of form F1
0.3.4 (September 18, 2018)
- expose parse_header and parse_line to consumers of this library
0.3.3 (September 18, 2018)
- add version 8.3 to mappings
0.3.2 (August 29, 2018)
- versions 1 and 2 of schedule H1 and H2
0.3.1 (August 29, 2018)
-
added more mappings
-
add a method to determine which mappings are missing
0.3.0 (August 27, 2018)
-
Rework warnings and errors for cases where mappings are missing
-
add mappings
0.2.3 (August 24, 2018)
- fix for filings that use both quotes and the field separator
0.2.2 (August 23, 2018)
- add support for F13, F132, and F133
0.2.1 (August 21, 2018)
- Fix regression that broke paper filings
0.2.0 (August 2, 2018)
- Add parsing for versions 1 and 2 of the .fec format
0.1.9 (July 18, 2018)
- add parsing for senate paper filings
0.1.8 (June 26, 2018)
- interest rate should never have been a float field
0.1.7 (June 26, 2018)
- handle n/a in number fields
0.1.6 (June 25, 2018)
-
more types
-
update documentation
-
handle percent signs in interest rates
0.1.5 (June 21, 2018)
- Initial published version
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