forked from mirrors/nixpkgs
fd045173ce
Using a simple algorithm, convert the references to a path in to a
sorted list of dependent paths based on how often they're referenced
and how deep in the tree they live. Equally-"popular" paths are then
sorted by name.
The existing writeReferencesToFile prints the paths in a simple
ascii-based sorting of the paths.
Sorting the paths by graph improves the chances that the difference
between two builds appear near the end of the list, instead of near
the beginning. This makes a difference for Nix builds which export a
closure for another program to consume, if that program implements its
own level of binary diffing.
For an example, Docker Images. If each store path is a separate layer
then Docker Images can be very efficiently transfered between systems,
and we get very good cache reuse between images built with the same
version of Nixpkgs. However, since Docker only reliably supports a
small number of layers (42) it is important to pick the individual
layers carefully. By storing very popular store paths in the first 40
layers, we improve the chances that the next Docker image will share
many of those layers.*
Given the dependency tree:
A - B - C - D -\
\ \ \ \
\ \ \ \
\ \ - E ---- F
\- G
Nodes which have multiple references are duplicated:
A - B - C - D - F
\ \ \
\ \ \- E - F
\ \
\ \- E - F
\
\- G
Each leaf node is now replaced by a counter defaulted to 1:
A - B - C - D - (F:1)
\ \ \
\ \ \- E - (F:1)
\ \
\ \- E - (F:1)
\
\- (G:1)
Then each leaf counter is merged with its parent node, replacing the
parent node with a counter of 1, and each existing counter being
incremented by 1. That is to say `- D - (F:1)` becomes `- (D:1, F:2)`:
A - B - C - (D:1, F:2)
\ \ \
\ \ \- (E:1, F:2)
\ \
\ \- (E:1, F:2)
\
\- (G:1)
Then each leaf counter is merged with its parent node again, merging
any counters, then incrementing each:
A - B - (C:1, D:2, E:2, F:5)
\ \
\ \- (E:1, F:2)
\
\- (G:1)
And again:
A - (B:1, C:2, D:3, E:4, F:8)
\
\- (G:1)
And again:
(A:1, B:2, C:3, D:4, E:5, F:9, G:2)
and then paths have the following "popularity":
A 1
B 2
C 3
D 4
E 5
F 9
G 2
and the popularity contest would result in the paths being printed as:
F
E
D
C
B
G
A
* Note: People who have used a Dockerfile before assume Docker's
Layers are inherently ordered. However, this is not true -- Docker
layers are content-addressable and are not explicitly layered until
they are composed in to an Image.
521 lines
14 KiB
Python
521 lines
14 KiB
Python
# IMPORTANT: Making changes?
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#
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# Validate your changes with python3 ./closure-graph.py --test
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# Using a simple algorithm, convert the references to a path in to a
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# sorted list of dependent paths based on how often they're referenced
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# and how deep in the tree they live. Equally-"popular" paths are then
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# sorted by name.
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#
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# The existing writeReferencesToFile prints the paths in a simple
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# ascii-based sorting of the paths.
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#
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# Sorting the paths by graph improves the chances that the difference
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# between two builds appear near the end of the list, instead of near
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# the beginning. This makes a difference for Nix builds which export a
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# closure for another program to consume, if that program implements its
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# own level of binary diffing.
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#
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# For an example, Docker Images. If each store path is a separate layer
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# then Docker Images can be very efficiently transfered between systems,
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# and we get very good cache reuse between images built with the same
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# version of Nixpkgs. However, since Docker only reliably supports a
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# small number of layers (42) it is important to pick the individual
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# layers carefully. By storing very popular store paths in the first 40
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# layers, we improve the chances that the next Docker image will share
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# many of those layers.*
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#
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# Given the dependency tree:
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#
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# A - B - C - D -\
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# \ \ \ \
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# \ \ \ \
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# \ \ - E ---- F
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# \- G
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#
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# Nodes which have multiple references are duplicated:
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#
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# A - B - C - D - F
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# \ \ \
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# \ \ \- E - F
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# \ \
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# \ \- E - F
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# \
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# \- G
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#
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# Each leaf node is now replaced by a counter defaulted to 1:
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#
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# A - B - C - D - (F:1)
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# \ \ \
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# \ \ \- E - (F:1)
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# \ \
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# \ \- E - (F:1)
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# \
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# \- (G:1)
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#
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# Then each leaf counter is merged with its parent node, replacing the
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# parent node with a counter of 1, and each existing counter being
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# incremented by 1. That is to say `- D - (F:1)` becomes `- (D:1, F:2)`:
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#
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# A - B - C - (D:1, F:2)
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# \ \ \
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# \ \ \- (E:1, F:2)
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# \ \
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# \ \- (E:1, F:2)
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# \
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# \- (G:1)
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#
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# Then each leaf counter is merged with its parent node again, merging
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# any counters, then incrementing each:
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#
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# A - B - (C:1, D:2, E:2, F:5)
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# \ \
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# \ \- (E:1, F:2)
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# \
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# \- (G:1)
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#
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# And again:
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#
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# A - (B:1, C:2, D:3, E:4, F:8)
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# \
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# \- (G:1)
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#
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# And again:
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#
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# (A:1, B:2, C:3, D:4, E:5, F:9, G:2)
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#
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# and then paths have the following "popularity":
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#
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# A 1
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# B 2
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# C 3
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# D 4
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# E 5
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# F 9
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# G 2
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#
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# and the popularity contest would result in the paths being printed as:
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#
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# F
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# E
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# D
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# C
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# B
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# G
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# A
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#
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# * Note: People who have used a Dockerfile before assume Docker's
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# Layers are inherently ordered. However, this is not true -- Docker
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# layers are content-addressable and are not explicitly layered until
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# they are composed in to an Image.
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import sys
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import json
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import unittest
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from pprint import pprint
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from collections import defaultdict
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# Find paths in the original dataset which are never referenced by
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# any other paths
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def find_roots(closures):
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roots = [];
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for closure in closures:
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path = closure['path']
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if not any_refer_to(path, closures):
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roots.append(path)
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return roots
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class TestFindRoots(unittest.TestCase):
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def test_find_roots(self):
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self.assertCountEqual(
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find_roots([
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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{
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"path": "/nix/store/bar",
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"references": [
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"/nix/store/bar",
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"/nix/store/tux"
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]
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},
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{
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"path": "/nix/store/hello",
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"references": [
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]
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}
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]),
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["/nix/store/foo", "/nix/store/hello"]
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)
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def any_refer_to(path, closures):
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for closure in closures:
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if path != closure['path']:
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if path in closure['references']:
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return True
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return False
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class TestAnyReferTo(unittest.TestCase):
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def test_has_references(self):
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self.assertTrue(
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any_refer_to(
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"/nix/store/bar",
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[
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/bar"
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]
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},
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]
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),
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)
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def test_no_references(self):
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self.assertFalse(
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any_refer_to(
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"/nix/store/foo",
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[
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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]
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),
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)
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def all_paths(closures):
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paths = []
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for closure in closures:
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paths.append(closure['path'])
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paths.extend(closure['references'])
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paths.sort()
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return list(set(paths))
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class TestAllPaths(unittest.TestCase):
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def test_returns_all_paths(self):
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self.assertCountEqual(
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all_paths([
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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{
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"path": "/nix/store/bar",
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"references": [
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"/nix/store/bar",
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"/nix/store/tux"
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]
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},
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{
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"path": "/nix/store/hello",
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"references": [
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]
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}
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]),
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["/nix/store/foo", "/nix/store/bar", "/nix/store/hello", "/nix/store/tux",]
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)
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def test_no_references(self):
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self.assertFalse(
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any_refer_to(
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"/nix/store/foo",
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[
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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]
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),
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)
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# Convert:
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#
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# [
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# { path: /nix/store/foo, references: [ /nix/store/foo, /nix/store/bar, /nix/store/baz ] },
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# { path: /nix/store/bar, references: [ /nix/store/bar, /nix/store/baz ] },
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# { path: /nix/store/baz, references: [ /nix/store/baz, /nix/store/tux ] },
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# { path: /nix/store/tux, references: [ /nix/store/tux ] }
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# ]
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#
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# To:
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# {
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# /nix/store/foo: [ /nix/store/bar, /nix/store/baz ],
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# /nix/store/bar: [ /nix/store/baz ],
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# /nix/store/baz: [ /nix/store/tux ] },
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# /nix/store/tux: [ ]
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# }
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#
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# Note that it drops self-references to avoid loops.
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def make_lookup(closures):
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lookup = {}
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for closure in closures:
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# paths often self-refer
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nonreferential_paths = [ref for ref in closure['references'] if ref != closure['path']]
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lookup[closure['path']] = nonreferential_paths
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return lookup
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class TestMakeLookup(unittest.TestCase):
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def test_returns_lookp(self):
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self.assertDictEqual(
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make_lookup([
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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{
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"path": "/nix/store/bar",
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"references": [
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"/nix/store/bar",
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"/nix/store/tux"
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]
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},
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{
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"path": "/nix/store/hello",
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"references": [
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]
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}
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]),
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{
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"/nix/store/foo": [ "/nix/store/bar" ],
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"/nix/store/bar": [ "/nix/store/tux" ],
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"/nix/store/hello": [ ],
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}
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)
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# Convert:
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#
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# /nix/store/foo with
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# {
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# /nix/store/foo: [ /nix/store/bar, /nix/store/baz ],
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# /nix/store/bar: [ /nix/store/baz ],
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# /nix/store/baz: [ /nix/store/tux ] },
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# /nix/store/tux: [ ]
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# }
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#
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# To:
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#
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# {
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# /nix/store/bar: {
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# },
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# }
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def make_graph_segment_from_root(root, lookup):
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children = {}
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for ref in lookup[root]:
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children[ref] = make_graph_segment_from_root(ref, lookup)
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return children
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class TestMakeGraphSegmentFromRoot(unittest.TestCase):
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def test_returns_graph(self):
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self.assertDictEqual(
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make_graph_segment_from_root("/nix/store/foo", {
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"/nix/store/foo": [ "/nix/store/bar" ],
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"/nix/store/bar": [ "/nix/store/tux" ],
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"/nix/store/tux": [ ],
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"/nix/store/hello": [ ],
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}),
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{
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"/nix/store/bar": {
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"/nix/store/tux": {}
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}
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}
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)
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def test_returns_graph_tiny(self):
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self.assertDictEqual(
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make_graph_segment_from_root("/nix/store/tux", {
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"/nix/store/foo": [ "/nix/store/bar" ],
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"/nix/store/bar": [ "/nix/store/tux" ],
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"/nix/store/tux": [ ],
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}),
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{}
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)
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# Convert a graph segment in to a popularity-counted dictionary:
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#
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# From:
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# {
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# /nix/store/foo: {
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# /nix/store/bar: {
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# }
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# }
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# }
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#
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# to:
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# [
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# /nix/store/foo: 1
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# /nix/store/bar: 2
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# /nix/store/baz: 4
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# /nix/store/tux: 6
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# ]
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def graph_popularity_contest(full_graph):
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popularity = defaultdict(int)
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for path, subgraph in full_graph.items():
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popularity[path] += 1
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subcontest = graph_popularity_contest(subgraph)
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for subpath, subpopularity in subcontest.items():
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popularity[subpath] += subpopularity + 1
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return popularity
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class TestGraphPopularityContest(unittest.TestCase):
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def test_counts_popularity(self):
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self.assertDictEqual(
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graph_popularity_contest({
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"/nix/store/foo": {
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"/nix/store/bar": {
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"/nix/store/baz": {
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"/nix/store/tux": {}
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}
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},
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"/nix/store/baz": {
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"/nix/store/tux": {}
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}
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}
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}),
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{
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"/nix/store/foo": 1,
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"/nix/store/bar": 2,
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"/nix/store/baz": 4,
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"/nix/store/tux": 6,
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}
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)
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# Emit a list of packages by popularity, most first:
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#
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# From:
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# [
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# /nix/store/foo: 1
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# /nix/store/bar: 1
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# /nix/store/baz: 2
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# /nix/store/tux: 2
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# ]
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#
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# To:
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# [ /nix/store/baz /nix/store/tux /nix/store/bar /nix/store/foo ]
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def order_by_popularity(paths):
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paths_by_popularity = defaultdict(list)
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popularities = []
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for path, popularity in paths.items():
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popularities.append(popularity)
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paths_by_popularity[popularity].append(path)
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popularities = list(set(popularities))
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popularities.sort()
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flat_ordered = []
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for popularity in popularities:
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paths = paths_by_popularity[popularity]
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paths.sort(key=package_name)
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flat_ordered.extend(reversed(paths))
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return list(reversed(flat_ordered))
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class TestOrderByPopularity(unittest.TestCase):
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def test_returns_in_order(self):
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self.assertEqual(
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order_by_popularity({
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"/nix/store/foo": 1,
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"/nix/store/bar": 1,
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"/nix/store/baz": 2,
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"/nix/store/tux": 2,
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}),
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[
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"/nix/store/baz",
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"/nix/store/tux",
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"/nix/store/bar",
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"/nix/store/foo"
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]
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)
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def package_name(path):
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parts = path.split('-')
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start = parts.pop(0)
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# don't throw away any data, so the order is always the same.
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# even in cases where only the hash at the start has changed.
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parts.append(start)
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return '-'.join(parts)
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def main():
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filename = sys.argv[1]
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key = sys.argv[2]
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with open(filename) as f:
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data = json.load(f)
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# Data comes in as:
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# [
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# { path: /nix/store/foo, references: [ /nix/store/foo, /nix/store/bar, /nix/store/baz ] },
|
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# { path: /nix/store/bar, references: [ /nix/store/bar, /nix/store/baz ] },
|
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# { path: /nix/store/baz, references: [ /nix/store/baz, /nix/store/tux ] },
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# { path: /nix/store/tux, references: [ /nix/store/tux ] }
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# ]
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#
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# and we want to get out a list of paths ordered by how universally,
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# important they are, ie: tux is referenced by every path, transitively
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# so it should be #1
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#
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# [
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# /nix/store/tux,
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# /nix/store/baz,
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# /nix/store/bar,
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# /nix/store/foo,
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# ]
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graph = data[key]
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|
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roots = find_roots(graph);
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lookup = make_lookup(graph)
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|
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full_graph = {}
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for root in roots:
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full_graph[root] = make_graph_segment_from_root(root, lookup)
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|
|
ordered = order_by_popularity(graph_popularity_contest(full_graph))
|
|
missing = []
|
|
for path in all_paths(graph):
|
|
if path not in ordered:
|
|
missing.append(path)
|
|
|
|
ordered.extend(missing)
|
|
print("\n".join(ordered))
|
|
|
|
if "--test" in sys.argv:
|
|
# Don't pass --test otherwise unittest gets mad
|
|
unittest.main(argv = [f for f in sys.argv if f != "--test" ])
|
|
else:
|
|
main()
|