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General docs tidy ups. Improve Script guides #1199

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Sep 13, 2024
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General docs tidy ups. Improve Script guides #1199

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d2e0f13
Fix example using explicit `Script` and `Task` in script basics guide
elliotgunton Sep 11, 2024
f04267c
Tidy up script/pydantic docs
elliotgunton Sep 12, 2024
0caf55e
Update expr user guide
elliotgunton Sep 12, 2024
cb351f7
Tidy up history.md
elliotgunton Sep 12, 2024
b33fd92
Tidy up README and tagline docs
elliotgunton Sep 12, 2024
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25 changes: 12 additions & 13 deletions README.md
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# Hera

<img src =docs/assets/hera-logo.svg width="30%">
<img src=https://github.com/argoproj-labs/hera/main/docs/assets/hera-logo.svg width="30%" alt="Hera mascot">

Hera is a Python framework for constructing and submitting Argo Workflows. The main goal of Hera is to make the Argo
ecosystem accessible by simplifying workflow construction and submission.
Hera makes Python code easy to orchestrate on Argo Workflows through native Python integrations. It lets you construct and
submit your Workflows entirely in Python.

[See the Quick Start guide](https://hera.readthedocs.io/en/stable/walk-through/quick-start/) to start using Hera to
orchestrate your Argo Workflows!
Expand All @@ -13,9 +13,9 @@ The Argo was constructed by the shipwright Argus,
and its crew were specially protected by the goddess Hera.
```

### PyPi stats
### PyPI stats

[![Pypi](https://img.shields.io/pypi/v/hera.svg)](https://pypi.python.org/pypi/hera)
[![PyPI](https://img.shields.io/pypi/v/hera.svg)](https://pypi.python.org/pypi/hera)
[![Versions](https://img.shields.io/pypi/pyversions/hera.svg)](https://github.com/argoproj-labs/hera)

[![Downloads](https://static.pepy.tech/badge/hera)](https://pepy.tech/project/hera)
Expand Down Expand Up @@ -128,15 +128,14 @@ w.create()

## Installation

| Source | Command |
|------------------------------------------------------|---------------------------------------------------------------------------------------------------------|
| [PyPI](https://pypi.org/project/hera/) | `pip install hera` |
| [GitHub repo](https://github.com/argoproj-labs/hera) | `python -m pip install git+https://github.com/argoproj-labs/hera --ignore-installed` |

> **Note** Hera went through a name change - from `hera-workflows` to `hera`. This is reflected in the published Python
> package. If you'd like to install versions prior to `5.0.0`, you have to use `hera-workflows`. Hera currently
> publishes releases to both `hera` and `hera-workflows` for backwards compatibility purposes.

| Source | Command |
|----------------------------------------------------------|------------------------------------------------------------------------------------------------------|
| [PyPi](https://pypi.org/project/hera/) | `pip install hera` |
| [PyPi](https://pypi.org/project/hera-workflows/) | `pip install hera-workflows` |
| [GitHub repo](https://github.com/argoproj-labs/hera) | `python -m pip install git+https://github.com/argoproj-labs/hera --ignore-installed; pip install .` |
> package. If you'd like to install versions prior to `5.0.0`, you should do `pip install hera-workflows<5`. Hera
> currently publishes releases to both `hera` and `hera-workflows` for backwards compatibility purposes.

### Optional dependencies

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../README.md
7 changes: 3 additions & 4 deletions docs/contributing/history.md
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Expand Up @@ -12,8 +12,9 @@ There have been other libraries available for structuring and submitting Argo Wo
While the aforementioned libraries provided amazing functionality for Argo workflow construction and submission, they
required an advanced understanding of Argo concepts. When [Dyno Therapeutics](https://dynotx.com) started using Argo
Workflows, it was challenging to construct and submit experimental machine learning workflows. Scientists and engineers
at [Dyno Therapeutics](https://dynotx.com) used a lot of time for workflow definition rather than the implementation of
the atomic unit of execution - the Python function - that performed, for instance, model training.
were using a lot of time for workflow definition rather than the implementation of the atomic unit of execution - the
Python function - that performed, for instance, model training. Hera was created to help focus on the unit of execution,
and was released as an open-source library for the benefit of Python Argo Workflows users.

Hera presents an intuitive Python interface to the underlying API of Argo, with custom classes making use of context
managers and callables, empowering users to focus on their own executable payloads rather than workflow setup.
Expand Down Expand Up @@ -146,8 +147,6 @@ class DagDiamond(Workflow):

## Hera V5 vs V4

_Reserving here for Bloomberg history with Argo/Hera._

Hera v5 is a major release that introduces breaking changes from v4. The main reason for this is that v5 is a complete
rewrite of the library, and is now based on the OpenAPI specification of Argo Workflows. This allows us to provide a
more intuitive interface to the Argo API, while also providing full feature parity with Argo Workflows. This means that
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# Hera Python -> expr transpiler
# Python → expr transpiler

[**Expr**](https://github.com/antonmedv/expr/blob/master/docs/Language-Definition.md) is an expression evaluation language used by [**Argo**](https://argoproj.github.io/argo-workflows/variables/#expression).
[Expr](https://expr-lang.org/) is a Go-centric expression language used by
[Argo Workflows](https://argoproj.github.io/argo-workflows/variables/#expression).

Hera provides an easy way to construct `expr` expressions in `Python`. It supports the full language definition of `expr` including the enhancements added by `Argo`.
Hera provides an easy way to construct `expr` expressions in Python. It supports the full language definition of `expr`
including the enhancements added by Argo.

## Usage

The recommended way of using the `hera.expr` module is to construct the expression in Python. Once your expressions is ready to be used,
you may call `str(<expression>)` to convert it to an appropriate `expr` expression. `hera` also supports formatting expressions such that they are surrounded by braces which is useful in Argo when substituting variables.. You can do this via Python string format literals and by adding `$` as a format string.
The recommended way of using the `hera.expr` module is to construct the expression in Python. Once your expressions is
ready to be used, you may call `str(<expression>)` to convert it to an appropriate `expr` expression. Hera also supports
formatting expressions such that they are surrounded by braces which is useful in Argo when substituting variables. You
can do this via Python string format literals and by adding `$` as a format string.

Example:

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