Python CLI tool and library for diffing CSV and JSON files
Tool for viewing the difference between two CSV, TSV or JSON files. See Generating a commit log for San Francisco’s official list of trees (and the sf-tree-history repo commit log) for background information on this project.
pip install csv-diff
Consider two CSV files:
one.csv
id,name,age
1,Cleo,4
2,Pancakes,2
two.csv
id,name,age
1,Cleo,5
3,Bailey,1
csv-diff
can show a human-readable summary of differences between the files:
$ csv-diff one.csv two.csv --key=id
1 row changed, 1 row added, 1 row removed
1 row changed
Row 1
age: "4" => "5"
1 row added
id: 3
name: Bailey
age: 1
1 row removed
id: 2
name: Pancakes
age: 2
The --key=id
option means that the id
column should be treated as the unique key, to identify which records have changed.
The tool will automatically detect if your files are comma- or tab-separated. You can over-ride this automatic detection and force the tool to use a specific format using --format=tsv
or --format=csv
.
You can also feed it JSON files, provided they are a JSON array of objects where each object has the same keys. Use --format=json
if your input files are JSON.
Use --show-unchanged
to include full details of the unchanged values for rows with at least one change in the diff output:
% csv-diff one.csv two.csv --key=id --show-unchanged
1 row changed
id: 1
age: "4" => "5"
Unchanged:
name: "Cleo"
You can use the --json
option to get a machine-readable difference:
$ csv-diff one.csv two.csv --key=id --json
{
"added": [
{
"id": "3",
"name": "Bailey",
"age": "1"
}
],
"removed": [
{
"id": "2",
"name": "Pancakes",
"age": "2"
}
],
"changed": [
{
"key": "1",
"changes": {
"age": [
"4",
"5"
]
}
}
],
"columns_added": [],
"columns_removed": []
}
You can also import the Python library into your own code like so:
from csv_diff import load_csv, compare
diff = compare(
load_csv(open("one.csv"), key="id"),
load_csv(open("two.csv"), key="id")
)
diff
will now contain the same data structure as the output in the --json
example above.
If the columns in the CSV have changed, those added or removed columns will be ignored when calculating changes made to specific rows.