Project introspection
Finding insights in your project.
Pants provides several goals to provide insights into your project's structure.
xargs
to pipe these goals into other Pants commandsFor example:
$ pants dependents project/util.py | xargs pants test
See Advanced target selection for more info and other techniques to use the results.
list
- find your project's targets
list
will find all targets that match the arguments.
For example, to show all targets in your project:
❯ pants list ::
//:ansicolors
//:setuptools
helloworld:lib
helloworld:pex_binary
helloworld/__init__.py:lib
helloworld/main.py:lib
...
You can specify a file, which will find the target(s) owning that file:
❯ pants list helloworld/greet/greeting_test.py
helloworld/greet/greeting_test.py:tests
list
often works well when paired with the --filter
options from
Advanced Target Selection, e.g.
pants --filter-target-type=python_test list ::
to find all your python_test
targets.
dependencies
- find a target's dependencies
Use dependencies
to list all targets used directly by a target.
❯ pants dependencies helloworld:pex_binary
helloworld/main.py:lib
You can specify a file, which will run on the target(s) owning that file:
❯ pants dependencies helloworld/main.py:lib
//:ansicolors
helloworld/greet/greeting.py:lib
helloworld/main.py:lib
To include transitive dependencies—meaning the dependencies of the direct dependencies—use --transitive
:
❯ pants dependencies --transitive helloworld/main.py:lib
//:ansicolors
//:setuptools
//:types-setuptools
helloworld/greet/greeting.py:lib
helloworld/greet:translations
helloworld/main.py:lib
helloworld/translator/translator.py:lib
dependents
- find which targets depend on a target
The dependents
goal finds all targets that directly depend on the target you specify.
❯ pants dependents //:ansicolors
helloworld/main.py:lib
You can specify a file, which will run on the target(s) owning that file:
❯ pants dependents helloworld/translator/translator.py
helloworld/greet/greeting.py:lib
helloworld/translator:lib
helloworld/translator/translator_test.py:tests
To include transitive dependents — meaning targets that don't directly depend on your target, but which depend on a target that does directly use your target — use --transitive
:
❯ pants dependents --transitive helloworld/translator/translator.py
helloworld:lib
helloworld:pex_binary
helloworld/main.py:lib
helloworld/greet:lib
...
To include the original target itself, use --closed
:
❯ pants dependents --closed //:ansicolors
//:ansicolors
helloworld/main.py:lib
Export dependency graph
Both dependencies
and dependents
goals have the --format
option allowing you to export data in multiple formats.
Exporting information about the dependencies and dependents in JSON format will produce the
adjacency list of your dependency graph:
$ pants dependencies --format=json \
helloworld/greet/greeting.py \
helloworld/translator/translator_test.py
{
"helloworld/greet/greeting.py:lib": [
"//:reqs#setuptools",
"//:reqs#types-setuptools",
"helloworld/greet:translations",
"helloworld/translator/translator.py:lib"
],
"helloworld/translator/translator_test.py:tests": [
"//:reqs#pytest",
"helloworld/translator/translator.py:lib"
]
}
This has various applications, and you could analyze, visualize, and process the data further. Sometimes, a fairly
straightforward jq
query would suffice, but for anything more complex, it may make sense to write a small program
to process the exported graph. For instance, you could:
- find tests with most transitive dependencies
$ pants dependencies --filter-target-type=python_test --format=json :: \
| jq -r 'to_entries[] | "\(.key)\t\(.value | length)"' \
| sort -k2 -n
- find resources that only a few other targets depend on
$ pants dependents --filter-target-type=resource --format=json :: \
| jq -r 'to_entries[] | select(.value | length < 2)'
- find files within the
src/
directory that transitively lead to the most tests
# depgraph.py
import json
with open("data.json") as fh:
data = json.load(fh)
for source, dependents in data.items():
print(source, len([d for d in dependents if d.startswith("tests/")]))
$ pants dependents --transitive --format=json src:: > data.json
$ python3 depgraph.py | sort -k2 -n
For more sophisticated graph querying, you may want to look into graph libraries such as networkx
.
In a larger repository, it may make sense to track the health of the dependency graph and use the output
of the graph export to identify parts of your codebase that would benefit from refactoring.
filedeps
- find which files a target owns
filedeps
outputs all of the files belonging to a target, based on its sources
field.
❯ pants filedeps helloworld/greet:lib
helloworld/greet/BUILD
helloworld/greet/__init__.py
helloworld/greet/greeting.py
To output absolute paths, use the option --absolute
:
$ pants filedeps --absolute helloworld/util:util
/Users/pantsbuild/example-python/helloworld/greet/BUILD
/Users/pantsbuild/example-python/helloworld/greet/__init__.py
/Users/pantsbuild/example-python/helloworld/greet/greeting.py
To include the files used by dependencies (including transitive dependencies), use --transitive
:
$ pants filedeps --transitive helloworld/util:util
BUILD
helloworld/greet/BUILD
helloworld/greet/__init__.py
helloworld/greet/greeting.py
helloworld/greet/translations.json
...
peek
- programmatically inspect a target
peek
outputs JSON for each target specified.
$ pants peek helloworld/util:tests
[
{
"address": "helloworld/util:tests",
"target_type": "python_tests",
"dependencies": null,
"description": null,
"interpreter_constraints": null,
"skip_black": false,
"skip_docformatter": false,
"skip_flake8": true,
"skip_isort": false,
"skip_mypy": false,
"sources": [
"*.py",
"*.pyi",
"!test_*.py",
"!*_test.py",
"!tests.py",
"!conftest.py",
"!test_*.pyi",
"!*_test.pyi",
"!tests.pyi"
],
"tags": null
}
]
You can use --exclude-defaults
for less verbose output:
$ pants peek --exclude-defaults helloworld/util:tests
[
{
"address": "helloworld/util:tests",
"target_type": "python_tests",
"skip_flake8": true,
}
]
peek
can be particularly useful when paired with JQ to query the JSON. For example, you can combine pants peek
with JQ to find all targets where you set the field skip_flake8=True
:
$ pants peek :: | jq -r '.[] | select(.skip_flake8 == true) | .["address"]'
helloworld/greet:lib
helloworld/greet:tests
helloworld/util:lib
pants peek
Some introspection goals, such as filter
, dependencies
and dependents
emit a flat list of target addresses. It's often useful to expand each of those into a full JSON structure with detailed properties of each target, by piping to pants peek
:
pants dependents helloworld/main.py:lib | xargs pants peek --exclude-defaults
[
{
"address": "helloworld:lib",
"target_type": "python_sources",
"dependencies": [
"helloworld/__init__.py:lib",
"helloworld/main.py:lib"
],
"sources": [
"helloworld/__init__.py",
"helloworld/main.py"
]
},
{
"address": "helloworld:pex_binary",
"target_type": "pex_binary",
"dependencies": [
"helloworld/main.py:lib"
],
"entry_point": {
"module": "main.py",
"function": null
}
}
]
Keep in mind, however, that the peek
goal may be invoked by xargs
as many times as necessary to use up the list
of input items. This may break the structured data output, so it may be safer to use the
--spec-files
option.
paths
- find dependency paths
paths
emits a list of all dependency paths between two targets:
$ pants paths --from=helloworld/main.py --to=helloworld/translator/translator.py
[
[
"helloworld/main.py:lib",
"helloworld/greet/greeting.py:lib",
"helloworld/translator/translator.py:lib"
]
]
count-loc
- count lines of code
count-loc
counts the lines of code of the specified files by running the Succinct Code Counter tool.
❯ pants count-loc ::
───────────────────────────────────────────────────────────────────────────────
Language Files Lines Blanks Comments Code Complexity
──────────────────────────────────────────────────── ───────────────────────────
Python 1690 618679 23906 7270 587503 18700
HTML 61 6522 694 67 5761 0
JSON 36 18755 6 0 18749 0
YAML 30 2451 4 19 2428 0
JavaScript 6 671 89 8 574 32
CSV 1 2 0 0 2 0
JSONL 1 4 0 0 4 0
Jinja 1 11 0 0 11 2
Shell 1 13 2 2 9 4
TOML 1 146 5 0 141 0
───────────────────────────────────────────────────────────────────────────────
Total 1828 647254 24706 7366 615182 18738
───────────────────────────────────────────────────────────────────────────────
Estimated Cost to Develop $22,911,268
Estimated Schedule Effort 50.432378 months
Estimated People Required 53.813884
────────────────────────────────────────────────────────────────────────────── ─
SCC has dozens of options. You can pass through options by either setting --scc-args
or using --
at the end of your command, like this:
pants count-loc :: -- --no-cocomo
pants_ignore
.By default, Pants will ignore all globs specified in your .gitignore
, along with dist/
and any hidden files.
To ignore additional files, add to the global option pants_ignore
in your pants.toml
, using the same syntax as .gitignore
files.
For example:
[GLOBAL]
pants_ignore.add = ["/ignore_this_dir/"]