Runs

Runs#

This page discusses ways to manipulate your runs.

import mlflow
mlflow.set_tracking_uri("file:///tmp/runs_page")

Search runs#

Using mlflow.search_runs, you can load a set of runs that correspond to specified conditions. The most useful parameters are:

Parameter	Description
`experiments_ids`	The IDs of the experiments from which the runs will be retrieved
`search_al_experiments`	Will return runs from all awailable experiments

The following cell generates a set of experiments, as well as a set of runs for each experiment.

for i in range(5):
    experiment_name = f"experiment {i + 1}"
    mlflow.create_experiment(experiment_name)
    mlflow.set_experiment(experiment_name=experiment_name)
    for j in range(5):
        mlflow.start_run(run_name = f"run {j + 1}")
        mlflow.end_run()

The following cell shows the runs of the experiment 1.

mlflow.search_runs(experiment_ids=[mlflow.get_experiment_by_name("experiment 1").experiment_id])

	run_id	experiment_id	status	artifact_uri	start_time	end_time	tags.mlflow.user	tags.mlflow.runName	tags.mlflow.source.name	tags.mlflow.source.type
0	1d3b84196bf04311b515df92ded6e29b	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/1d3b8...	2025-09-26 12:37:43.683000+00:00	2025-09-26 12:37:43.685000+00:00	user	run 5	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
1	7d0de82b412d421aac32258101c81136	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/7d0de...	2025-09-26 12:37:43.680000+00:00	2025-09-26 12:37:43.682000+00:00	user	run 4	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
2	c6d2dde7251a4847941a1abe664832e6	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/c6d2d...	2025-09-26 12:37:43.676000+00:00	2025-09-26 12:37:43.679000+00:00	user	run 3	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
3	d8ac0efee591417bb46b36614c037ccd	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/d8ac0...	2025-09-26 12:37:43.671000+00:00	2025-09-26 12:37:43.675000+00:00	user	run 2	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
4	5e93a7b1b5bc418cb7aa59a526b7e2d0	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/5e93a...	2025-09-26 12:37:43.664000+00:00	2025-09-26 12:37:43.669000+00:00	user	run 1	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL

The same, but also runs of the experiment 2 are added.

experiments_ids = [
    mlflow.get_experiment_by_name("experiment 1").experiment_id,
    mlflow.get_experiment_by_name("experiment 2").experiment_id,
]
mlflow.search_runs(experiment_ids=experiments_ids)

	run_id	experiment_id	status	artifact_uri	start_time	end_time	tags.mlflow.user	tags.mlflow.runName	tags.mlflow.source.name	tags.mlflow.source.type
0	e6c7219efbe34a8582a4500a11d3ccac	459248949934636608	FINISHED	file:///tmp/runs_page/459248949934636608/e6c72...	2025-09-26 12:37:43.700000+00:00	2025-09-26 12:37:43.702000+00:00	user	run 5	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
1	ddc7e8c1884c421d885158211f9a5acd	459248949934636608	FINISHED	file:///tmp/runs_page/459248949934636608/ddc7e...	2025-09-26 12:37:43.697000+00:00	2025-09-26 12:37:43.699000+00:00	user	run 4	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
2	20fd7890661a4ca6bd2a56d61fb88dfc	459248949934636608	FINISHED	file:///tmp/runs_page/459248949934636608/20fd7...	2025-09-26 12:37:43.694000+00:00	2025-09-26 12:37:43.696000+00:00	user	run 3	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
3	4ff4fdacb5bf408092498a187f8e6a0a	459248949934636608	FINISHED	file:///tmp/runs_page/459248949934636608/4ff4f...	2025-09-26 12:37:43.691000+00:00	2025-09-26 12:37:43.693000+00:00	user	run 2	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
4	4706fd7e7596464b9d25deee41f9b2db	459248949934636608	FINISHED	file:///tmp/runs_page/459248949934636608/4706f...	2025-09-26 12:37:43.688000+00:00	2025-09-26 12:37:43.690000+00:00	user	run 1	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
5	1d3b84196bf04311b515df92ded6e29b	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/1d3b8...	2025-09-26 12:37:43.683000+00:00	2025-09-26 12:37:43.685000+00:00	user	run 5	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
6	7d0de82b412d421aac32258101c81136	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/7d0de...	2025-09-26 12:37:43.680000+00:00	2025-09-26 12:37:43.682000+00:00	user	run 4	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
7	c6d2dde7251a4847941a1abe664832e6	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/c6d2d...	2025-09-26 12:37:43.676000+00:00	2025-09-26 12:37:43.679000+00:00	user	run 3	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
8	d8ac0efee591417bb46b36614c037ccd	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/d8ac0...	2025-09-26 12:37:43.671000+00:00	2025-09-26 12:37:43.675000+00:00	user	run 2	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL
9	5e93a7b1b5bc418cb7aa59a526b7e2d0	460233828277669480	FINISHED	file:///tmp/runs_page/460233828277669480/5e93a...	2025-09-26 12:37:43.664000+00:00	2025-09-26 12:37:43.669000+00:00	user	run 1	/home/user/.virtualenvironments/python/lib/pyt...	LOCAL

Child & Parent#

MLFlow allows the creation of nested runs. There is an outer run - the parent run and an inner run - the child run. To create a child run, you need to start another run while one is running and pass nested=True to the mlflow.start_run.

Check out the Understanding Parent and Child Runs in MLflow tutorial for more details.

The following cell creates a “parent” run, and inside it iteratively starts some other runs with the names child_0, child_1 and so on.

mlflow.set_experiment("nested_runs")
with mlflow.start_run(run_name="parent"):
    for i in range(10):
        with mlflow.start_run(run_name=f"child_{i}", nested=True):
            pass

🏃 View run child_0 at: http://localhost:5000/#/experiments/362948453640932348/runs/2562f6f88bd24fd18e590fefc985cc33
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_1 at: http://localhost:5000/#/experiments/362948453640932348/runs/9b0233bb13e045e581d79a73e1ef1f73
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_2 at: http://localhost:5000/#/experiments/362948453640932348/runs/17799d3fd383422c8ebf2086237854e2
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_3 at: http://localhost:5000/#/experiments/362948453640932348/runs/c1283382a89549959c423a12fe09b6fb
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_4 at: http://localhost:5000/#/experiments/362948453640932348/runs/4b1163851f0d46eeaebf210102b5d1ab
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_5 at: http://localhost:5000/#/experiments/362948453640932348/runs/3fdd20b7cfdb4746b44ce73eb9e19bc9
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_6 at: http://localhost:5000/#/experiments/362948453640932348/runs/74eaf04c30c043edbbf6eec9a48b5866
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_7 at: http://localhost:5000/#/experiments/362948453640932348/runs/e1d880c924ec4a7cb896a043f29615ed
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_8 at: http://localhost:5000/#/experiments/362948453640932348/runs/c292b24e66e24fd7aa8ea632e478388e
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run child_9 at: http://localhost:5000/#/experiments/362948453640932348/runs/2225de115c2e45e0be8c8149dc8fb85c
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348
🏃 View run parent at: http://localhost:5000/#/experiments/362948453640932348/runs/a6793e5651944acea30396464bb3bdd7
🧪 View experiment at: http://localhost:5000/#/experiments/362948453640932348

The next code displays the names of the runs and the parent ids of the runs that were just created.

id = mlflow.get_experiment_by_name("nested_runs").experiment_id
runs = mlflow.search_runs(experiment_ids=id)
runs.loc[:, ["run_id", "tags.mlflow.runName", "tags.mlflow.parentRunId"]]

	run_id	tags.mlflow.runName	tags.mlflow.parentRunId
0	2225de115c2e45e0be8c8149dc8fb85c	child_9	a6793e5651944acea30396464bb3bdd7
1	c292b24e66e24fd7aa8ea632e478388e	child_8	a6793e5651944acea30396464bb3bdd7
2	e1d880c924ec4a7cb896a043f29615ed	child_7	a6793e5651944acea30396464bb3bdd7
3	74eaf04c30c043edbbf6eec9a48b5866	child_6	a6793e5651944acea30396464bb3bdd7
4	3fdd20b7cfdb4746b44ce73eb9e19bc9	child_5	a6793e5651944acea30396464bb3bdd7
5	4b1163851f0d46eeaebf210102b5d1ab	child_4	a6793e5651944acea30396464bb3bdd7
6	c1283382a89549959c423a12fe09b6fb	child_3	a6793e5651944acea30396464bb3bdd7
7	17799d3fd383422c8ebf2086237854e2	child_2	a6793e5651944acea30396464bb3bdd7
8	9b0233bb13e045e581d79a73e1ef1f73	child_1	a6793e5651944acea30396464bb3bdd7
9	2562f6f88bd24fd18e590fefc985cc33	child_0	a6793e5651944acea30396464bb3bdd7
10	a6793e5651944acea30396464bb3bdd7	parent	None

As a result, in the tags.mlflow.parentRunId column, for the “parent” run there is None, but all other runs refer to the “parent” through this column.

Note that in the mlflow GUI runs are ordered in a hierachal order - check how to work with it in the Understanding Parent and Child Runs in MLflow tutorial.

Runs

Contents

Runs#

Search runs#

Child & Parent#