zincware / ZnTrack

Create, visualize, run & benchmark DVC pipelines in Python & Jupyter notebooks.
https://zntrack.readthedocs.io
Apache License 2.0
44 stars 4 forks source link

small docs improvements #757

Closed PythonFZ closed 4 months ago

codecov[bot] commented 5 months ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 91.06%. Comparing base (da08e15) to head (e441a66).

Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #757 +/- ## ======================================= Coverage 91.06% 91.06% ======================================= Files 25 25 Lines 2059 2059 Branches 979 979 ======================================= Hits 1875 1875 Misses 184 184 ``` | [Flag](https://app.codecov.io/gh/zincware/ZnTrack/pull/757/flags?src=pr&el=flags&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=zincware) | Coverage Ξ” | | |---|---|---| | [fulltest](https://app.codecov.io/gh/zincware/ZnTrack/pull/757/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=zincware) | `86.83% <ΓΈ> (ΓΈ)` | | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=zincware#carryforward-flags-in-the-pull-request-comment) to find out more.

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PythonFZ commented 4 months ago

@CodiumAI-Agent /review

CodiumAI-Agent commented 4 months ago

PR Analysis

πŸ’‘ General suggestions: The changes made in this PR are valuable as they improve the clarity and readability of the documentation. The updated code examples are more accurate and reflect the current state of the project. However, it would be beneficial to ensure that all the code examples in the documentation are tested to ensure they work as expected.

πŸ€– Code feedback:
relevant filedocs/source/_get-started/api_classes.rst
suggestion      
**It would be helpful to include a brief explanation of what `zntrack.params()` and `zntrack.outs()` do in the context of the code example. This will provide more context to the reader and make the documentation more informative. [medium]**
relevant linea = zntrack.params()

relevant filedocs/source/_get-started/index.rst
suggestion      
**Consider breaking down the long sentences into shorter ones for better readability. Also, try to avoid passive voice where possible to make the text more engaging. [medium]**
relevant lineZnTrack is designed to build workflows, track parameters, and keep a record of associated outputs and metrics.


✨ Usage guide:
**Overview:** The `review` tool scans the PR code changes, and generates a PR review. The tool can be triggered [automatically](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools) every time a new PR is opened, or can be invoked manually by commenting on any PR. When commenting, to edit [configurations](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L19) related to the review tool (`pr_reviewer` section), use the following template: ``` /review --pr_reviewer.some_config1=... --pr_reviewer.some_config2=... ``` With a [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#working-with-github-app), use the following template: ``` [pr_reviewer] some_config1=... some_config2=... ```
Utilizing extra instructions
The `review` tool can be configured with extra instructions, which can be used to guide the model to a feedback tailored to the needs of your project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify the relevant sub-tool, and the relevant aspects of the PR that you want to emphasize. Examples for extra instructions: ``` [pr_reviewer] # /review # extra_instructions=""" In the code feedback section, emphasize the following: - Does the code logic cover relevant edge cases? - Is the code logic clear and easy to understand? - Is the code logic efficient? ... """ ``` Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.
How to enable\disable automation
- When you first install PR-Agent app, the [default mode](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools) for the `review` tool is: ``` pr_commands = ["/review", ...] ``` meaning the `review` tool will run automatically on every PR, with the default configuration. Edit this field to enable/disable the tool, or to change the used configurations
About the 'Code feedback' section
The `review` tool provides several type of feedbacks, one of them is code suggestions. If you are interested **only** in the code suggestions, it is recommended to use the [`improve`](./IMPROVE.md) feature instead, since it dedicated only to code suggestions, and usually gives better results. Use the `review` tool if you want to get a more comprehensive feedback, which includes code suggestions as well.
Auto-labels
The `review` tool can auto-generate two specific types of labels for a PR: - a `possible security issue` label, that detects possible [security issues](https://github.com/Codium-ai/pr-agent/blob/tr/user_description/pr_agent/settings/pr_reviewer_prompts.toml#L136) (`enable_review_labels_security` flag) - a `Review effort [1-5]: x` label, where x is the estimated effort to review the PR (`enable_review_labels_effort` flag)
Extra sub-tools
The `review` tool provides a collection of possible feedbacks about a PR. It is recommended to review the [possible options](https://github.com/Codium-ai/pr-agent/blob/main/docs/REVIEW.md#enabledisable-features), and choose the ones relevant for your use case. Some of the feature that are disabled by default are quite useful, and should be considered for enabling. For example: `require_score_review`, `require_soc2_review`, `enable_review_labels_effort`, and more.
More PR-Agent commands
> To invoke the PR-Agent, add a comment using one of the following commands: > - **/review**: Request a review of your Pull Request. > - **/describe**: Update the PR title and description based on the contents of the PR. > - **/improve [--extended]**: Suggest code improvements. Extended mode provides a higher quality feedback. > - **/ask \**: Ask a question about the PR. > - **/update_changelog**: Update the changelog based on the PR's contents. > - **/add_docs** πŸ’Ž: Generate docstring for new components introduced in the PR. > - **/generate_labels** πŸ’Ž: Generate labels for the PR based on the PR's contents. > - **/analyze** πŸ’Ž: Automatically analyzes the PR, and presents changes walkthrough for each component. >See the [tools guide](https://github.com/Codium-ai/pr-agent/blob/main/docs/TOOLS_GUIDE.md) for more details. >To list the possible configuration parameters, add a **/config** comment.
See the [review usage](https://github.com/Codium-ai/pr-agent/blob/main/docs/REVIEW.md) page for a comprehensive guide on using this tool.
CodiumAI-Agent commented 4 months ago

PR Review

⏱️ Estimated effort to review [1-5] 2, because the PR primarily involves documentation changes and minor code adjustments in examples. The changes are straightforward and do not involve complex logic or architectural modifications.
πŸ§ͺ Relevant tests No
πŸ” Possible issues No
πŸ”’ Security concerns No
Code feedback:
relevant filedocs/source/_get-started/api_classes.rst
suggestion       Consider adding a brief explanation or example of how `zntrack.params_path()` and `zntrack.outs_path()` can be used in practice. This would provide clarity to users on when and why to use these methods over the more automatic `zntrack.params()` and `zntrack.outs()`. [important]
relevant lineAlternatively, you can use the ``zntrack.params_path()`` and ``zntrack.outs_path()`` to define the paths to the respective files.

relevant filedocs/source/_get-started/index.rst
suggestion       It might be beneficial to include a simple example or code snippet in this introductory section to immediately engage the reader with a practical illustration of ZnTrack's capabilities. This can help in grasping the basic concepts more effectively. [medium]
relevant lineThe following sections will guide you through the basic concepts of ZnTrack and how to use it.

relevant filedocs/source/index.rst
suggestion       Given the introduction of DVC links, it would be helpful to briefly mention how ZnTrack integrates with DVC or complements its features, especially for readers who might be familiar with DVC but new to ZnTrack. This could enhance the understanding of ZnTrack's value proposition. [medium]
relevant line.. _DVC: https://dvc.org/

relevant filedocs/source/index.rst
suggestion       To make the documentation more engaging and visually appealing, consider adding a few screenshots or diagrams that illustrate the workflow or the concept of Nodes in ZnTrack. Visual aids can significantly improve comprehension and retention of information. [medium]
relevant lineZnTrack is designed to simplify code sharing and reproducibility.


✨ Review tool usage guide:
**Overview:** The `review` tool scans the PR code changes, and generates a PR review. The tool can be triggered [automatically](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools) every time a new PR is opened, or can be invoked manually by commenting on any PR. When commenting, to edit [configurations](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L19) related to the review tool (`pr_reviewer` section), use the following template: ``` /review --pr_reviewer.some_config1=... --pr_reviewer.some_config2=... ``` With a [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#working-with-github-app), use the following template: ``` [pr_reviewer] some_config1=... some_config2=... ```
Utilizing extra instructions
The `review` tool can be configured with extra instructions, which can be used to guide the model to a feedback tailored to the needs of your project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify the relevant sub-tool, and the relevant aspects of the PR that you want to emphasize. Examples for extra instructions: ``` [pr_reviewer] # /review # extra_instructions=""" In the 'possible issues' section, emphasize the following: - Does the code logic cover relevant edge cases? - Is the code logic clear and easy to understand? - Is the code logic efficient? ... """ ``` Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.
How to enable\disable automation
- When you first install PR-Agent app, the [default mode](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools) for the `review` tool is: ``` pr_commands = ["/review", ...] ``` meaning the `review` tool will run automatically on every PR, with the default configuration. Edit this field to enable/disable the tool, or to change the used configurations
Auto-labels
The `review` tool can auto-generate two specific types of labels for a PR: - a `possible security issue` label, that detects possible [security issues](https://github.com/Codium-ai/pr-agent/blob/tr/user_description/pr_agent/settings/pr_reviewer_prompts.toml#L136) (`enable_review_labels_security` flag) - a `Review effort [1-5]: x` label, where x is the estimated effort to review the PR (`enable_review_labels_effort` flag)
Extra sub-tools
The `review` tool provides a collection of possible feedbacks about a PR. It is recommended to review the [possible options](https://github.com/Codium-ai/pr-agent/blob/main/docs/REVIEW.md#enabledisable-features), and choose the ones relevant for your use case. Some of the feature that are disabled by default are quite useful, and should be considered for enabling. For example: `require_score_review`, `require_soc2_ticket`, and more.
Auto-approve PRs
By invoking: ``` /review auto_approve ``` The tool will automatically approve the PR, and add a comment with the approval. To ensure safety, the auto-approval feature is disabled by default. To enable auto-approval, you need to actively set in a pre-defined configuration file the following: ``` [pr_reviewer] enable_auto_approval = true ``` (this specific flag cannot be set with a command line argument, only in the configuration file, committed to the repository) You can also enable auto-approval only if the PR meets certain requirements, such as that the `estimated_review_effort` is equal or below a certain threshold, by adjusting the flag: ``` [pr_reviewer] maximal_review_effort = 5 ```
More PR-Agent commands
> To invoke the PR-Agent, add a comment using one of the following commands: > - **/review**: Request a review of your Pull Request. > - **/describe**: Update the PR title and description based on the contents of the PR. > - **/improve [--extended]**: Suggest code improvements. Extended mode provides a higher quality feedback. > - **/ask \**: Ask a question about the PR. > - **/update_changelog**: Update the changelog based on the PR's contents. > - **/add_docs** πŸ’Ž: Generate docstring for new components introduced in the PR. > - **/generate_labels** πŸ’Ž: Generate labels for the PR based on the PR's contents. > - **/analyze** πŸ’Ž: Automatically analyzes the PR, and presents changes walkthrough for each component. >See the [tools guide](https://github.com/Codium-ai/pr-agent/blob/main/docs/TOOLS_GUIDE.md) for more details. >To list the possible configuration parameters, add a **/config** comment.
See the [review usage](https://github.com/Codium-ai/pr-agent/blob/main/docs/REVIEW.md) page for a comprehensive guide on using this tool.
PythonFZ commented 4 months ago

@CodiumAI-Agent /improve

CodiumAI-Agent commented 4 months ago

PR Code Suggestions

CategorySuggestions                                                                                                                                                       
Enhancement
Add an example or explanation of automatic serialization with zntrack.. ___ **Consider adding a brief explanation or example of how Python objects are automatically
serialized using zntrack.. This will help users understand the practical benefits and how
it integrates with their workflows.** [docs/source/_get-started/api_classes.rst [17]](https://github.com/zincware/ZnTrack/pull/757/files#diff-8f4891f3abdf880c05001d7dfc1109226f0e4aa171e7d9d8a9245c5d2e03ea57R17-R17) ```diff -The ``zntrack.`` enables seamless integration with your existing workflows, allowing Python objects to be automatically serialized. +The ``zntrack.`` enables seamless integration with your existing workflows by allowing Python objects to be automatically serialized. For example, if you have a complex data structure as a parameter, `zntrack.` can automatically handle its conversion to and from JSON format, simplifying data management. ```
Add an explanation or example for zntrack.params_path() and zntrack.outs_path(). ___ **To improve readability and understanding, consider adding a brief explanation or example
of how zntrack.params_path() and zntrack.outs_path() are used to define paths for
parameters and outputs.** [docs/source/_get-started/api_classes.rst [18]](https://github.com/zincware/ZnTrack/pull/757/files#diff-8f4891f3abdf880c05001d7dfc1109226f0e4aa171e7d9d8a9245c5d2e03ea57R18-R18) ```diff -Alternatively, you can use the ``zntrack.params_path()`` and ``zntrack.outs_path()`` to define the paths to the respective files. +Alternatively, you can use the ``zntrack.params_path()`` and ``zntrack.outs_path()`` to explicitly define the paths to the respective files for parameters and outputs. For instance, `zntrack.params_path("my_params.json")` specifies that parameters should be stored in "my_params.json". ```
Clarify the roles of zntrack.params(), zntrack.outputs(), and zntrack.deps(). ___ **It's recommended to add a brief explanation about the difference between zntrack.params(),
zntrack.outputs(), and zntrack.deps() to clarify their specific roles and usage in
defining node dependencies and outputs.** [docs/source/_get-started/project.rst [13-21]](https://github.com/zincware/ZnTrack/pull/757/files#diff-b9046250b6ca6f3c5d15032beba5265a643e260f99aa7023dedfcdebf98b3051R13-R21) ```diff -parameter: int = zntrack.params() -outputs: int = zntrack.outputs() -parameter: int = zntrack.deps() +parameter: int = zntrack.params() # Use `zntrack.params()` to define input parameters. +outputs: int = zntrack.outputs() # Use `zntrack.outputs()` to specify the outputs of the node. +parameter: int = zntrack.deps() # Use `zntrack.deps()` to declare dependencies on other nodes. ```
Add an overview of ZnTrack's key features and benefits. ___ **To enhance the introduction of ZnTrack, consider adding a brief overview of its key
features and benefits. This can help new users quickly grasp the value proposition of
ZnTrack.** [docs/source/index.rst [20-22]](https://github.com/zincware/ZnTrack/pull/757/files#diff-4eec6cec5f6fab1548b85433ea8ca81315ae165db4b7f84019f287df9015699fR20-R22) ```diff Welcome to ZnTrack, the first developer package from zincware _. -We're excited to have you on board! -ZnTrack is designed to simplify code sharing and reproducibility. +We're excited to have you on board! ZnTrack simplifies code sharing and reproducibility by offering features like workflow automation, parameter tracking, and integration with DVC for data version control. It's designed to make your data science projects more manageable and shareable. ```
Clarify the role of zntrack.outs in storing node outputs. ___ **To ensure clarity and consistency, consider revising the explanation of the zntrack.outs
method to explicitly mention that it facilitates the storage and retrieval of node
outputs, and how it contributes to the reproducibility of workflows.** [docs/source/_get-started/api_classes.rst [73]](https://github.com/zincware/ZnTrack/pull/757/files#diff-8f4891f3abdf880c05001d7dfc1109226f0e4aa171e7d9d8a9245c5d2e03ea57R73-R73) ```diff -Using the `zntrack.outs` will store results in the Node Working Directory (``nwd``), +Using the `zntrack.outs` method, results are stored in the Node Working Directory (``nwd``), typically set as ``nodes/``. This approach not only organizes output files efficiently but also enhances the reproducibility of workflows by ensuring that outputs are easily accessible and version-controlled. ```

✨ Improve tool usage guide:
**Overview:** The `improve` tool scans the PR code changes, and automatically generates suggestions for improving the PR code. The tool can be triggered [automatically](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools) every time a new PR is opened, or can be invoked manually by commenting on a PR. When commenting, to edit [configurations](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L69) related to the improve tool (`pr_code_suggestions` section), use the following template: ``` /improve --pr_code_suggestions.some_config1=... --pr_code_suggestions.some_config2=... ``` With a [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#working-with-github-app), use the following template: ``` [pr_code_suggestions] some_config1=... some_config2=... ```
Enabling\disabling automation
When you first install the app, the [default mode](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools) for the improve tool is: ``` pr_commands = ["/improve --pr_code_suggestions.summarize=true", ...] ``` meaning the `improve` tool will run automatically on every PR, with summarization enabled. Delete this line to disable the tool from running automatically.
Utilizing extra instructions
Extra instructions are very important for the `improve` tool, since they enable to guide the model to suggestions that are more relevant to the specific needs of the project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify relevant aspects that you want the model to focus on. Examples for extra instructions: ``` [pr_code_suggestions] # /improve # extra_instructions=""" Emphasize the following aspects: - Does the code logic cover relevant edge cases? - Is the code logic clear and easy to understand? - Is the code logic efficient? ... """ ``` Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.
A note on code suggestions quality
- While the current AI for code is getting better and better (GPT-4), it's not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. - Suggestions are not meant to be simplistic. Instead, they aim to give deep feedback and raise questions, ideas and thoughts to the user, who can then use his judgment, experience, and understanding of the code base. - Recommended to use the 'extra_instructions' field to guide the model to suggestions that are more relevant to the specific needs of the project, or use the [custom suggestions :gem:](https://github.com/Codium-ai/pr-agent/blob/main/docs/CUSTOM_SUGGESTIONS.md) tool - With large PRs, best quality will be obtained by using 'improve --extended' mode.
More PR-Agent commands
> To invoke the PR-Agent, add a comment using one of the following commands: > - **/review**: Request a review of your Pull Request. > - **/describe**: Update the PR title and description based on the contents of the PR. > - **/improve [--extended]**: Suggest code improvements. Extended mode provides a higher quality feedback. > - **/ask \**: Ask a question about the PR. > - **/update_changelog**: Update the changelog based on the PR's contents. > - **/add_docs** πŸ’Ž: Generate docstring for new components introduced in the PR. > - **/generate_labels** πŸ’Ž: Generate labels for the PR based on the PR's contents. > - **/analyze** πŸ’Ž: Automatically analyzes the PR, and presents changes walkthrough for each component. >See the [tools guide](https://github.com/Codium-ai/pr-agent/blob/main/docs/TOOLS_GUIDE.md) for more details. >To list the possible configuration parameters, add a **/config** comment.
See the [improve usage](https://github.com/Codium-ai/pr-agent/blob/main/docs/IMPROVE.md) page for a more comprehensive guide on using this tool.
CodiumAI-Agent commented 4 months ago

PR Code Suggestions

πŸ’‘ [enhancement]

Consider using zntrack.Param and zntrack.Out instead of zntrack.params() and zntrack.outs() for better readability and consistency with Python's standard attribute declaration style.

File: docs/source/_get-started/api_classes.rst (22-33)

Example code: ___ Existing code: ```python import zntrack class SumValues(zntrack.Node): """Node to compute the sum of two parameters.""" a = zntrack.params() b = zntrack.params() result = zntrack.outs() def run(self): """Compute the sum of two parameters.""" self.result = self.a + self.b ``` Improved code: ```python import zntrack class SumValues(zntrack.Node): """Node to compute the sum of two parameters.""" a = zntrack.Param() b = zntrack.Param() result = zntrack.Out() def run(self): """Compute the sum of two parameters.""" self.result = self.a + self.b ```

πŸ’‘ [enhancement]

Consider using zntrack.Param and zntrack.Out instead of zntrack.params() and zntrack.outs() for better readability and consistency with Python's standard attribute declaration style.

File: docs/source/_get-started/project.rst (10-24)

Example code: ___ Existing code: ```python import zntrack class AddOne(zntrack.Node): parameter: int = zntrack.params() outputs: int = zntrack.outputs() def run(self): self.outputs = self.parameter + 1 class SubtractOne(zntrack.Node): parameter: int = zntrack.deps() outputs: int = zntrack.outputs() def run(self): self.outputs = self.parameter - 1 ``` Improved code: ```python import zntrack class AddOne(zntrack.Node): parameter: int = zntrack.Param() outputs: int = zntrack.Out() def run(self): self.outputs = self.parameter + 1 class SubtractOne(zntrack.Node): parameter: int = zntrack.Dep() outputs: int = zntrack.Out() def run(self): self.outputs = self.parameter - 1 ```

πŸ’‘ [readability]

Consider splitting the long sentence into shorter ones for better readability.

File: docs/source/index.rst (20-22)

Example code: ___ Existing code: ```python Welcome to ZnTrack, the first developer package from zincware _. We're excited to have you on board! ZnTrack is designed to simplify code sharing and reproducibility. ``` Improved code: ```python Welcome to ZnTrack, the first developer package from zincware _. We're excited to have you on board! ZnTrack has been designed with two main goals in mind. First, to simplify code sharing. Second, to enhance reproducibility. ```

πŸ’‘ [enhancement]

Consider using zntrack.Param and zntrack.Out instead of zntrack.params() and zntrack.outs() for better readability and consistency with Python's standard attribute declaration style.

File: docs/source/index.rst (55-64)

Example code: ___ Existing code: ```python import zntrack class AddNumbers(zntrack.Node): number1 = zntrack.params() number2 = zntrack.params() result = zntrack.outs() def run(self): self.result = self.number1 + self.number2 ``` Improved code: ```python import zntrack class AddNumbers(zntrack.Node): number1 = zntrack.Param() number2 = zntrack.Param() result = zntrack.Out() def run(self): self.result = self.number1 + self.number2 ```