You have rust? cool! try:
cargo install havocompare
You just want a binary: Check our binary downloads on github-pages
Havocompare was developed with a few design goals in mind. We wanted a human readable and easily composable configuration file format.
After a few tries we ended up with the current format, which is a list of rules inside a yaml file.
See the following example config.yaml:
yaml
rules:
- name: "Numerical results csv"
pattern_include: "**/export_*.csv"
pattern_exclude: "**/export_1337.csv"
CSV:
comparison_modes:
- Relative: 0.1
- Absolute: 1.0
It creates a new rule named rule including all files matching "export*.csv" in all sub-folders but exclude "export1337.csv".
String cells will be checked for perfect identity, numbers (including numbers with units) will be checked for a relative deviation smaller than 0.1
AND absolute deviation smaller than 1.0.
Comparison rules
- Relative means validity is checked like: |nominal - actual| / |nominal| < tolerance
- Absolute means validity is checked like: |nominal - actual| < tolerance
- "nan" and "nan" is equal
- 0 difference with 0 nominal value is valid for any relative difference
Running the comparison is super easy, just supply nominal, actual and the config:
./havocompare compare nominal_dir actual_dir config.yaml
The report of the comparison will be written inside the ./report folder. Differences will also be printed to the terminal.
Furthermore, if differences are found, the return code will be 1, if no differences are found, it will be 0 making integration of
havocompare into a CI system rather easy.
Writing a valid configuration file can be error prone without auto completion. We suggest using json schema to validate your yaml
and even enable auto completion in IDEs like pycharm. To generate the schema you can call:
./havocompare schema > config_scheme.json and import the resulting scheme into your IDE.
The comparison_modes option is required and of type 'list'. It can comprise either a relative numerical ('Relative') maximum deviation or a maximum
deviation ('Absolute').
You can specify the decimal separator and the field separator. If you don't specify, havocompare will try to guess it from each csv file.
Note: If delimiters are not specified, even different delimiters between nominal and actual are accepted as long as all deviations are in bounds.
To ignore specific cells, you can specify an exclusion regex.
The preprocessing steps are done after the file is parsed using the given delimiters (or guessing) but before anything else. Processing order is as written in the list. In the below example, headers will be extracted from the csv-input file, then a column with the title "Columnn to delete" will be deleted. If any of the preprocessing steps fail, havocompare will exit with an error immediately so use them carefully.
See the following example with all optional parameters set:
yaml
rules:
- name: "CSV - Demo all options"
# what files to include
pattern_include: "**/*.csv"
# optional: of all included files, remove the ones matching the exclude pattern
pattern_exclude: "**/ignored.csv"
CSV:
# delimiters are optional, if not given, they will be auto-detected.
# auto-detection allows different delimiters for nominal and actual
decimal_separator: '.'
field_delimiter: ';'
# can have Absolute or Relative
comparison_modes:
- Absolute: 1.0
- Relative: 0.1
# optional: exclude fields matching the regex from comparison
exclude_field_regex: "Excluded"
# optional: preprocessing of the csv files
preprocessing:
# extracts the headers to the header-fields, makes reportings more legible and allows for further processing "ByName"
- ExtractHeaders
# Sort the table by column 0, beware that the column must only contain numbers / quantities
- SortByColumnNumber: 0
# Delete a column by name, needs `ExtractHeaders` first
- DeleteColumnByName: "Column to delete"
- DeleteColumnByNumber: 1
# Sorts are stable, so a second sort will keep the first sort as sub-order.
- SortByColumnName: "Sort by column name blabla"
Image comparison is done using the image compare crate's hybrid comparison which does MSSIM on the luma and RMS on the color information.
Only a threshold can be specified:
yaml
rules:
- name: "JPG comparison"
pattern_include: "**/*.jpg"
# exclude can of course also be specified!
Image:
# threshold is between 0.0 for total difference, 0.5 for very dissimilar and 1.0 for perfect mach
# Usually you want to test with values between 0.90 and 0.97
threshold: 0.9
For plain text comparison the file is read and compared line by line. For each line the normalized Damerau-Levenshtein distance from the strsim
crate is used. You can ignore single lines which you know are different by specifying an arbitrary number of ignored lines:
yaml
- name: "HTML-Compare strict"
pattern_exclude: "**/*_changed.html"
pattern_include: "**/*.html"
PlainText:
# Normalized Damerau-Levenshtein distance
threshold: 1.0
# All lines matching any regex below will be ignored
ignore_lines:
- "stylesheet"
- "next_ignore"
- "[A-Z]*[0-9]"
For binary files which cannot otherwise be checked we can also do a simple hash comparison. Currently we only support SHA-256 but more checks can be added easily.
yaml
- name: "Hash comparison strict"
pattern_exclude: "**/*.bin"
Hash:
# Currently we only have Sha256
function: Sha256