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Sort dvc pipeline list #2669

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f01acd3
Added path.lstrip for / in imports
SrividyaKK Oct 23, 2019
23fbb04
Merge branch 'master' of github.com:iterative/dvc
SrividyaKK Oct 23, 2019
c011d94
Merge branch 'master' of github.com:iterative/dvc
SrividyaKK Oct 25, 2019
81b5dd6
Postorder traversal - pipeline list
SrividyaKK Oct 25, 2019
9d13d0c
Postorder traversal - pipeline list
SrividyaKK Oct 25, 2019
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13 changes: 9 additions & 4 deletions dvc/command/pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -162,13 +162,18 @@ def run(self):

class CmdPipelineList(CmdBase):
def run(self):
import networkx
import networkx as nx

pipelines = self.repo.pipelines
for p in pipelines:
stages = networkx.get_node_attributes(p, "stage")
for stage in stages:
logger.info(stage)
stages = nx.get_node_attributes(p, "stage")
for node in p:
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Please correct me if I'm wrong, but what you are doing here is you are walking through all nodes in the pipeline in the random order, then you do a dfs_postorder for each one of those and then just print it. This is basically the same as what it was before but now with a redundant step of dfs_postorder_nodes. 🙂 Looks like we can do better than that 🙂

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@efiop efiop Oct 25, 2019 •
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Good way to think about it is to imagine how the pipeline looks. So it has a N start nodes (p.out_degree(node) == 0), M end nodes (p.in_degree(node) == 0) and some nodes between them. The way dvc repro --pipeline works, is it finds all end nodes and for each of them does dfs_postorder_nodes and just runs those. But obviously, that real order of execution is not going to look good here 🙁 Could we somehow order them better here? Maybe nx.topological_sort(p)?

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Thank you for the explanation. I'll work on it.

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p.out_degree(node) == 0 for end nodes and p.in_degree(node) == 0 for start nodes right?

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@efiop efiop Oct 28, 2019 •
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@SrividyaKK Actually no, our DAG has a reversed shape right now because we put edges in the direction from dependent stage to the one it depends on. So say your pipeline is cleanup step and then process step, then DAG would look like cleanup <- process. Just a caveat of the current design, we might change it in the future 😉

stage = stages[node]
# if not stage.locked:
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Please don't leave commented-out code like that. Looks like you don't need it, right? If so - remove it.

# continue
for n in nx.dfs_postorder_nodes(p, node):
if n == node:
logger.info(stage)
if len(stages) != 0:
logger.info("=" * 80)
logger.info("{} pipelines total".format(len(pipelines)))
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