CSV-Diff Report is a command-line tool for generating diff reports in Excel or
HTML format from CSV files. It uses the CSV-Diff gem to perform diffs, and adds
to that library the ability to generate formatted reports, and a command-line
tool csvdiff for running diffs between files or directories.
Unlike a standard diff that compares line by line, and is sensitive to the ordering of records, CSV-Diff identifies common lines by key field(s), and then compares the contents of the fields in each line.
CSV-Diff is particularly well suited to data in parent-child format. Parent- child data does not lend itself well to standard text diffs, as small changes in the organisation of the tree at an upper level can lead to big movements in the position of descendant records. By instead matching records by key, CSV-Diff avoids this issue, while still being able to detect changes in sibling order.
CSV-Diff Report is supplied as a gem, and has dependencies on a few small libraries. To install it, simply:
gem install csv-diff-report
To compare two CSV files where the field names are in the first row of the file, and the first field contains the unique key for each record, simply use:
csvdiff <file1> <file2>
The csvdiff command-line tool provides many options to control behaviour of
the diff and reporting process. To see all available options, run:
csvdiff --help
This will display a help screen like the following:
CSV-Diff
========
Generate a diff report between two files using the CSV-Diff algorithm.
USAGE
-----
ruby /usr/local/opt/ruby/bin/csvdiff FROM TO [OPTIONS]
FROM The file or dir to use as the left or from source in the diff
TO The file or dir to use as the right or to source in the diff
OPTIONS
-------
Source Options
--pattern PATTERN A file name pattern to use to filter matching files if a directory diff is
being performed
[Default: *]
--field-names FIELD-NAMES A comma-separated list of field names for each field in the source files
--parent-fields PARENT-FIELDS The parent field name(s) or index(es)
--child-fields CHILD-FIELDS The child field name(s) or index(es)
--key-fields KEY-FIELDS The key field name(s) or index(es)
--encoding ENCODING The encoding to use when opening the CSV files
--ignore-header If true, the first line in each source file is ignored; requires the use of
the --field-names option to name the fields
Diff Options
--ignore-fields IGNORE-FIELDS The names or indexes of any fields to be ignored during the diff
--ignore-adds If true, items in TO that are not in FROM are ignored
--ignore-deletes If true, items in FROM that are not in TO are ignored
--ignore-updates If true, changes to non-key properties are ignored
--ignore-moves If true, changes in an item's position are ignored
Output Options
--format FORMAT The format in which to produce the diff report
[Default: HTML]
--output OUTPUT The path to save the diff report to. If not specified, the diff report will
be placed in the same directory as the FROM file, and will be named
Diff_<FROM>_to_<TO>.<FORMAT>
The csvdiff command-line tool supports both file and directory diffs. As directories may contain files of different formats, .csvdiff files can be used to match file names to file types, and specify the appropriate diff settings for each file type.
A .csvdiff file can be placed in either the working directory from which the csvdiff command is run, or the FROM directory. It consists of a YAML-formatted file with the following top-level keys:
- defaults: Contains settings to be applied across all file types unless overridden for a specific file type.
- file_types: A hash whose keys are the file type labels used to describe files of that type, and whose values are the various diff settings to use for that file type.
All settings that can be specified on the command-line can also be specified via .csvdiff for each file type. In addition, several additional settings are available via .csvdiff that are not available on the command-line. These additional settings are as follows:
- pattern: Specifies the file name pattern that is used to match a file name to a file type. File types are checked in the order listed, so more general patterns must appear later in the .csvdiff file to avoid masking more specific patterns; e.g. a pattern of * will match every file, so it should appear as the pattern setting of the last entry in the file_types hash to ensure other more specific patterns get a chance to match a given file name first.
- exclude_pattern: Specifies an exclusion pattern for file names. Can be useful when a single pattern is correct for a file-type but for a class of exceptions.
- ignore: A boolean flag that can be used to ignore processing of matching files. Useful when a directory contains files that should not be diffed in addition to those that should.
- include: A Hash of field names or indexes to either a regular expression or a lambda expression which must be satisfied for records in the source to be diffed. Any records with values in the corresponding columns will not be included in the diff if the value in that column does not satisfy the regular expression or lambda.
- exclude: A Hash of field names or indexes to either a regular expression or a lambda expression which must not be satisfied for records in the source to be diffed. Any records with values in the corresponding columns will not be included in the diff if the value in that column satisfies the regular expression or lambda.
CSVDiff is preferable over a standard line-by-line diff when row order is significantly impacted by small changes. The classic example is a parent-child file generated by a hierarchy traversal. A simple change in position of a parent member near the root of the hierarchy will have a large impact on the positions of all descendant rows. Consider the following example:
Root
|- A
| |- A1
| |- A2
|
|- B
|- B1
|- B2
A hierarchy traversal of this tree into a parent-child format would generate a CSV as follows:
Root,A
A,A1
A,A2
Root,B
B,B1
B,B2
If the positions of A and B were swapped, a hierarchy traversal would now produce a CSV as follows:
Root,B
B,B1
B,B2
Root,A
A,A1
A,A2
A simple diff using a diff utility would highlight this as 3 additions and 3 deletions. CSVDiff, however, would classify this as 2 moves (a change in sibling position for A and B).
In order to do this, CSVDiff needs to know what field(s) confer uniqueness on each row. In this example, we could use the child field alone (since each member name only appears once); however, this would imply a flat structure, where all rows are children of a single parent. This in turn would cause CSVDiff to classify the above change as a Move (i.e. a change in order) of all 6 rows.
The more correct specification of this file is that column 0 contains a unique parent identifier, and column 1 contains a unique child identifier. CSVDiff can then correctly deduce that there is in fact only two changes in order - the swap in positions of A and B below Root.
Note: If you aren't interested in changes in the order of siblings, then you could use CSVDiff with a :key_field option of column 1, and specify the :ignore_moves option.
When processing and diffing files, CSVDiff may encounter problems with the data or the specifications it has been given. It will continue even in the face of problems, but will log details of the problems in a #warnings Array. The number of warnings will also be included in the Hash returned by the #summary method.
Warnings may be raised for any of the following:
- Missing fields: If the right/to file contains fields that are not present in the left/from file, a warning is raised and the field is ignored for diff purposes.
- Duplicate keys: If two rows are found that have the same values for the key field(s), a warning is raised, and the duplicate values are ignored.
The simplest use case is as shown above, where the data to be diffed is in CSV files with the column names as the first record, and where the unique key is the first column in the data. In this case, a diff can be created simply via:
diff = CSVDiff.new(file1, file2)Often however, rows are not uniquely identifiable via the first column in the file. In a parent-child hierarchy, for example, combinations of parent and child may be necessary to uniquely identify a row. In these cases, it is necessary to indicate which fields are used to uniquely identify common rows across the two files. This can be done in several different ways.
-
Using the :key_fields option with field numbers (these are 0-based):
diff = CSVDiff.new(file1, file2, key_fields: [0, 1])
-
Using the :key_fields options with column names:
diff = CSVDiff.new(file1, file2, key_fields: ['Parent', 'Child'])
-
Using the :parent_fields and :child_fields with field numbers:
diff = CSVDiff.new(file1, file2, parent_field: 1, child_fields: [2, 3])
-
Using the :parent_fields and :child_fields with column names:
diff = CSVDiff.new(file1, file2, parent_field: 'Date', child_fields: ['HomeTeam', 'AwayTeam'])
Data from non-CSV sources can be diffed, as long as it can be supplied as an Array of Arrays:
DATA1 = [
['Parent', 'Child', 'Description'],
['A', 'A1', 'Account 1'],
['A', 'A2', 'Account 2']
]
DATA2 = [
['Parent', 'Child', 'Description'],
['A', 'A1', 'Account1'],
['A', 'A2', 'Account2']
]
diff = CSVDiff.new(DATA1, DATA2, key_fields: [1, 0])If your data file does not include column headers, you can specify the names of each column when creating the diff. The names supplied are the keys used in the diff results:
DATA1 = [
['A', 'A1', 'Account 1'],
['A', 'A2', 'Account 2']
]
DATA2 = [
['A', 'A1', 'Account1'],
['A', 'A2', 'Account2']
]
diff = CSVDiff.new(DATA1, DATA2, key_fields: [1, 0], field_names: ['Parent', 'Child', 'Description'])If your data file does contain a header row, but you wish to use your own column names, you can specify the :field_names option and the :ignore_header option to ignore the first row.
If your data contains fields that you aren't interested in, these can be excluded from the diff process using the :ignore_fields option:
diff = CSVDiff.new(file1, file2, parent_field: 'Date', child_fields: ['HomeTeam', 'AwayTeam'],
ignore_fields: ['CreatedAt', 'UpdatedAt'])If you need to filter source data before running the diff process, you can use the :include and :exclude options to do so. Both options take a Hash as their value; the hash should have keys that are the field names or indexes (0-based) on which to filter, and whose values are regular expressions or lambdas to be applied to values of the corresponding field. Rows will only be diffed if they satisfy :include conditions, and do not satisfy :exclude conditions.
# Generate a diff of Arsenal home games not refereed by Clattenburg
diff = CSVDiff.new(file1, file2, parent_field: 'Date', child_fields: ['HomeTeam', 'AwayTeam'],
include: {HomeTeam: 'Arsenal'}, exclude: {Referee: /Clattenburg/})
# Generate a diff of games played over the Xmas/New Year period
diff = CSVDiff.new(file1, file2, parent_field: 'Date', child_fields: ['HomeTeam', 'AwayTeam'],
include: {Date: lambda{ |d| holiday_period.include?(Date.strptime(d, '%y/%m/%d')) } })CSVDiff identifies Adds, Updates, Moves and Deletes; any of these changes can be selectively ignored, e.g. if you are not interested in Deletes, you can pass the :ignore_deletes option:
diff = CSVDiff.new(file1, file2, parent_field: 'Date', child_fields: ['HomeTeam', 'AwayTeam'],
ignore_fields: ['CreatedAt', 'UpdatedAt'],
ignore_deletes: true, ignore_moves: true)
