From 52be59797abf2f0c5dbfcb28d1af970fdca4f246 Mon Sep 17 00:00:00 2001 From: Andrew Savchyn Date: Sun, 1 Oct 2023 12:23:50 +0200 Subject: [PATCH 1/3] Fix list formatting in README --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 52a39c02c..7d7ab28f8 100644 --- a/README.md +++ b/README.md @@ -27,14 +27,14 @@ Hamilton is a novel paradigm for specifying a flow of delayed execution in pytho This paradigm makes modifications easy to build and track, ensures code is self-documenting, and makes it natural to unit test your data transformations. When connected together, these functions form a [Directed Acyclic Graph](https://en.wikipedia.org/wiki/Directed_acyclic_graph) (DAG), which the Hamilton framework can execute, optimize, and report on. ## Problems Hamilton Solves -✅ Model a dataflow -- If you can model your problem as a DAG in python, Hamilton is the cleanest way to build it. -✅ Unmaintainable spaghetti code -- Hamilton dataflows are unit testable, self-documenting, and provide lineage. -✅ Long iteration/experimentation cycles -- Hamilton provides a clear, quick, and methodical path to debugging/modifying/extending your code. +✅ Model a dataflow -- If you can model your problem as a DAG in python, Hamilton is the cleanest way to build it. +✅ Unmaintainable spaghetti code -- Hamilton dataflows are unit testable, self-documenting, and provide lineage. +✅ Long iteration/experimentation cycles -- Hamilton provides a clear, quick, and methodical path to debugging/modifying/extending your code. ✅ Reusing code across contexts -- Hamilton encourages code that is independent of infrastructure and can run regardless of execution setting. ## Problems Hamilton Does not Solve -❌ Provisioning infrastructure -- you want a macro-orchestration system (see airflow, kubeflow, sagemaker, etc...). -❌ Doing your ML for you -- we organize youir code, BYOL (bring your own libraries). +❌ Provisioning infrastructure -- you want a macro-orchestration system (see airflow, kubeflow, sagemaker, etc...). +❌ Doing your ML for you -- we organize youir code, BYOL (bring your own libraries). ❌ Tracking execution + associated artifacts -- Hamilton is lightweight, but if this is important to you see the [DAGWorks product](www.dagworks.io). See the table below for more specifics/how it compares to other common tooling. From 43d9bcf879ac6cf802f491950adc61c7040777b4 Mon Sep 17 00:00:00 2001 From: Andrew Savchyn Date: Sun, 1 Oct 2023 12:31:41 +0200 Subject: [PATCH 2/3] Replace trailing spaces with
to avoid linting error --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 7d7ab28f8..49038f21e 100644 --- a/README.md +++ b/README.md @@ -27,14 +27,14 @@ Hamilton is a novel paradigm for specifying a flow of delayed execution in pytho This paradigm makes modifications easy to build and track, ensures code is self-documenting, and makes it natural to unit test your data transformations. When connected together, these functions form a [Directed Acyclic Graph](https://en.wikipedia.org/wiki/Directed_acyclic_graph) (DAG), which the Hamilton framework can execute, optimize, and report on. ## Problems Hamilton Solves -✅ Model a dataflow -- If you can model your problem as a DAG in python, Hamilton is the cleanest way to build it. -✅ Unmaintainable spaghetti code -- Hamilton dataflows are unit testable, self-documenting, and provide lineage. -✅ Long iteration/experimentation cycles -- Hamilton provides a clear, quick, and methodical path to debugging/modifying/extending your code. +✅ Model a dataflow -- If you can model your problem as a DAG in python, Hamilton is the cleanest way to build it.
+✅ Unmaintainable spaghetti code -- Hamilton dataflows are unit testable, self-documenting, and provide lineage.
+✅ Long iteration/experimentation cycles -- Hamilton provides a clear, quick, and methodical path to debugging/modifying/extending your code.
✅ Reusing code across contexts -- Hamilton encourages code that is independent of infrastructure and can run regardless of execution setting. ## Problems Hamilton Does not Solve -❌ Provisioning infrastructure -- you want a macro-orchestration system (see airflow, kubeflow, sagemaker, etc...). -❌ Doing your ML for you -- we organize youir code, BYOL (bring your own libraries). +❌ Provisioning infrastructure -- you want a macro-orchestration system (see airflow, kubeflow, sagemaker, etc...).
+❌ Doing your ML for you -- we organize youir code, BYOL (bring your own libraries).
❌ Tracking execution + associated artifacts -- Hamilton is lightweight, but if this is important to you see the [DAGWorks product](www.dagworks.io). See the table below for more specifics/how it compares to other common tooling. From e7ced9d41afdd16963dfb7af4f73958309866dc5 Mon Sep 17 00:00:00 2001 From: Stefan Krawczyk Date: Sun, 1 Oct 2023 20:01:13 -0700 Subject: [PATCH 3/3] Fixes typo in README youir -> your --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 49038f21e..ddd4bb754 100644 --- a/README.md +++ b/README.md @@ -34,7 +34,7 @@ This paradigm makes modifications easy to build and track, ensures code is self- ## Problems Hamilton Does not Solve ❌ Provisioning infrastructure -- you want a macro-orchestration system (see airflow, kubeflow, sagemaker, etc...).
-❌ Doing your ML for you -- we organize youir code, BYOL (bring your own libraries).
+❌ Doing your ML for you -- we organize your code, BYOL (bring your own libraries).
❌ Tracking execution + associated artifacts -- Hamilton is lightweight, but if this is important to you see the [DAGWorks product](www.dagworks.io). See the table below for more specifics/how it compares to other common tooling.