diff --git a/mintlify-docs/blogs/Buttons in zero-true.mdx b/mintlify-docs/blogs/Buttons in zero-true.mdx new file mode 100644 index 00000000..c254e93c --- /dev/null +++ b/mintlify-docs/blogs/Buttons in zero-true.mdx @@ -0,0 +1,70 @@ +--- +title: 'Buttons in Zero-True' +--- + +## Creating a Button + +Creating a button in zero-true is very easy. It’s as simple as + +```py +import zero-true as zt +button=zt.Button(id=’btn’) +``` + +![](/blogs/photos/button.png) + +## Button Values + +Buttons return True when clicked and False otherwise. There is no need to write callbacks, simply reference buttons as follows. + +```py +if button.value==True: print("hello") else: print("goodbye") +``` + +## Button Use Cases + +Buttons have a ton of potential use cases in zero-true. The example above uses a button to toggle different printed statements but logic can be used to render more complicated layouts. One of the more common patterns for using buttons in zero-true are gating expensive computations, for example: + +```py +import zero_true as zt +import time + +def expensive_computation(): + time.sleep(30) + +if button.value==True: +expensive_computation() + +else: +print("Press Button to Run Expensive Computation") +``` + +Another use case for buttons in zero-true is getting user confirmation before submitting a form. In the example below we save feedback that a user submits in a text area under a .txt file under their name. + + +![title](/blogs/gifs/button_computation.gif) + +```py +import zero_true as zt + +#function to write feedback to a file under someone's name +def write_feedback(name,text): + with open(name+'.txt','w+') as file: + file.write(text) + +#name input +name_input = zt.TextInput(id='txt_i',label='Write you name') +text_area = zt.TextArea(id='txt_a',label='Write your feedback here') + +#submission button +button=zt.Button(id='btn', label= 'Submit you feedback') + +if button.value==True and name_input.value: +write_feedback(name_input.value, text_area.value) +``` + +![](/blogs/photos/button_form.png) + +## Customizing your button + +You can also add different colors and labels to your button to make things more interesting. Feel free to play around with all the attributes in the documentation. \ No newline at end of file diff --git a/mintlify-docs/blogs/Displaying a Matplotlib Plot in zero-true.mdx b/mintlify-docs/blogs/Displaying a Matplotlib Plot in zero-true.mdx new file mode 100644 index 00000000..97fea7b8 --- /dev/null +++ b/mintlify-docs/blogs/Displaying a Matplotlib Plot in zero-true.mdx @@ -0,0 +1,62 @@ +--- +title: 'Displaying a Matplotlib Plot in zero-true' +--- + +## Displaying a Matplotlib Plot + +Matplotlib is one of the more popular plotting libraries in the python ecosystem, and zero-true has built in integrations for working with matplotlib plots. There is some slight nuance to how to work with matplotlib in zero-true though so take a look at the example below: + +```py +import matplotlib.pyplot as plt +import zero_true as zt + +# Create a figure and an axis +fig, ax = plt.subplots() + +# Plot some data +ax.plot([0, 1, 2, 3], [10, 20, 25, 30]) + +# Add labels and a title +ax.set_xlabel('X Label') +ax.set_ylabel('Y Label') +ax.set_title('Basic Line Plot') + +# Render the plot in zero-true +zt.matplotlib(id='plt',figure=fig,height=300,width=300) +``` + +![][image1] + +Run the cell in your notebook, and watch the line plot appear below\! Matplotlib components require an ID as well as a matplotlib figure passed as arguments to render. Since matplotlib plots are static components in zero-true there are no values for you to access that users interact with. + +## Interactive Matplotlib Plots in Zero-True + +Let’s take the code above and make it a little bit more exciting by interactively setting the last Y value in the plot: + +```py +import matplotlib.pyplot as plt +import zero_true as zt + +#slider for plot +slider = zt.Slider(id='slider',min=0,max=50) + +# Create a figure and an axis +fig, ax = plt.subplots() + +# Plot some data +ax.plot([0, 1, 2, 3], [10, 20, 25, slider.value]) + +# Add labels and a title +ax.set_xlabel('X Label') +ax.set_ylabel('Y Label') +ax.set_title('Basic Line Plot') + +# Get the plot and show it in zero-true +zt.matplotlib(id='plt',figure=fig,height=300,width=300) +``` + +![title](/blogs/gifs/matplotlib.gif) + +Combining matplotlib’s awesome capabilities with zero-true’s interactive notebook and UI can help take your visualization game to the next level. + +[image1]: \ No newline at end of file diff --git a/mintlify-docs/blogs/Displaying a Pandas DataFrame in zero-true.mdx b/mintlify-docs/blogs/Displaying a Pandas DataFrame in zero-true.mdx new file mode 100644 index 00000000..738acee7 --- /dev/null +++ b/mintlify-docs/blogs/Displaying a Pandas DataFrame in zero-true.mdx @@ -0,0 +1,48 @@ +--- +title: 'Displaying a Pandas DataFrame in zero-true' +--- + +## Displaying a DataFrame + +Pandas is one of the most popular python libraries for data analysis so sooner or later you are bound to use one of their “DataFrames” within your zero-true notebook. Once you have a dataframe that you’d like to display in zero-true, actually getting it to render on the frontend is simple. Take a look at the code snippet below where we load a dataframe from wikipedia and then display it with zero-true (readhtml will require you to have the library lxml installed in the same environment): + +```py +import pandas as pd +import zero_true as zt + +#read dataframe from wikipedia +novels_df = pd.read_html("https://en.wikipedia.org/w/index.php?title=Science_Fiction:_The_100_Best_Novels&oldid=1091082777", match='The 100 Best Novels')[0] + +#display dataframe with zero-true +zt.dataframe(id='df',df=novels_df) +``` + +![][image1] + +Run the cell in your notebook, and watch the dataframe appear below\! Like all other zero-true components, dataframes require an ID as well as a pandas df passed as arguments to render. Since dataframes are static components in zero-true there are no values for you to access that users interact with. + +## Filtering a DataFrame in Zero-True + +Let’s take the code above and make it a little bit more exciting by interactively filtering the dataframe with a slider in zero-true: + +```py +import pandas as pd +import zero_true as zt + +novels_df = pd.read_html("https://en.wikipedia.org/w/index.php?title=Science_Fiction:_The_100_Best_Novels&oldid=1091082777", match='The 100 Best Novels')[0] + +#define a slider in zero-true to filter the data +slider=zt.Slider(id='slider',min=1, max=100,label='Move the Slider to Filter the DataFrame') +#set the first value to 100 to keep all the novels in there +if not slider.value: + slider.value=100 + +#display the dataframe with zero-true +zt.dataframe(id='df',df=novels_df[0:slider.value]) +``` + +![title](/blogs/gifs/dataframe.gif) + +This will display the “top n books" where n is the value that the user selects using the slider. Dataframes can be useful when you have a range of text and numbers and more standard visualizations like plots fail to capture the entire story. + +[image1]: \ No newline at end of file diff --git a/mintlify-docs/blogs/Displaying a Plotly Plot in zero-true.mdx b/mintlify-docs/blogs/Displaying a Plotly Plot in zero-true.mdx new file mode 100644 index 00000000..721998c3 --- /dev/null +++ b/mintlify-docs/blogs/Displaying a Plotly Plot in zero-true.mdx @@ -0,0 +1,66 @@ +--- +title: 'Displaying a Plotly Plot in zero-true' +--- + +## Displaying a Plotly Plot + +Plotly is one of the most popular plotting libraries in the python ecosystem, and zero-true has built in integrations for working with it. There is some slight nuance to how to work with plotly in zero-true though so take a look at the example below: + +```py +import plotly.graph_objects as go +import zero_true as zt + +# Create a basic line plot in Plotly +fig = go.Figure() + +# Add data to the plot +fig.add_trace(go.Scatter(x=[0, 1, 2, 3], y=[10, 20, 25, 30], mode='lines', name='Data Line')) + +# Add labels and a title +fig.update_layout( + title='Basic Line Plot', + xaxis_title='X Label', + yaxis_title='Y Label') + +# Render the plot in zero-true +zt.plotlyComponent(id='plt', figure=fig) +``` + +![][image1] + +Run the cell in your notebook, and watch the line plot appear below\! Plotly components require an ID as well as a plotly figure passed as arguments to render. Since plotly plots are static components in zero-true there are no values for you to access that users interact with. However you can set interactivity into the plot by using things like hovertext etc that are built into the plotly library\! + +## Interactive Plotly Plots in Zero-True + +Let’s take the code above and make it a little bit more exciting by interactively setting the last Y value in the plot: + +```py +import plotly.graph_objects as go +import zero_true as zt + +slider=zt.Slider(id='slider',min=0,max=50) + +# Create a basic line plot in Plotly +fig = go.Figure() + +# Add data to the plot +fig.add_trace(go.Scatter(x=[0, 1, 2, 3], y=[10, 20, 25, slider.value], mode='lines', name='Data Line')) + +# Add labels and a title +fig.update_layout( + title='Basic Line Plot', + xaxis_title='X Label', + yaxis_title='Y Label') + +# Render the plot in zero-true +zt.plotlyComponent(id='plt', figure=fig) + +``` + +![title](/blogs/gifs/plotly.gif) + +Combining plotly’s incredible plotting capabilities with zero-true’s interactive notebook and UI can help take your visualization game to the next level. + +[image1]: + +[image2]: \ No newline at end of file diff --git a/mintlify-docs/blogs/Range Sliders in zero-true.mdx b/mintlify-docs/blogs/Range Sliders in zero-true.mdx new file mode 100644 index 00000000..cd41d95b --- /dev/null +++ b/mintlify-docs/blogs/Range Sliders in zero-true.mdx @@ -0,0 +1,57 @@ +--- +title: 'Range Sliders in zero-true' +--- + +## Creating a Range Slider + +Creating a rage slider in zero-true is simple. Type: + +```py +import zero-true as zt +range_slider=zt.RangeSlider(id='slider') +``` + +![][image1] + +Run the cell in your notebook, and watch the range slider appear below. + +## Range Slider Settings and Values + +Range Sliders have a minimum, maximum, and step in zero-true. The default values for min and max are 0 and 100 and the step is 1 but you can set them to whatever you’d like. The range slider value will return a list structured as follows \[min,max\]. Here is a little snippet to show you how to access the min and max values from your range slider. + +```py +max = range_slider.value[0] +min = range_slider.value[1] + +print("Min val is "+str(min)+ " and max val is "+str(max)) +``` + +## ![][image2] + +## Range Slider Use Cases + +Sliders can be used to capture any numeric input. Here is a more fleshed out example including filtering a dataframe: + +```py +import pandas as pd +import zero_true as zt + +novels_df = pd.read_html("https://en.wikipedia.org/w/index.php?title=Science_Fiction:_The_100_Best_Novels&oldid=1091082777", match='The 100 Best Novels')[0] + +#define a slider in zero-true to filter the data +range_slider=zt.RangeSlider(id='range_slider',min=1, max=100,label='Move the Slider to Filter the DataFrame') +if not range_slider.value: + range_slider.value=[0,100] +zt.dataframe(id='df',df=novels_df[range_slider.value[0]:range_slider.value[1]]) +``` + +![title](/blogs/gifs/range slider.gif) + + +## Customizing your Range Slider + +You can also add different colors and labels to your slider to make it to your liking. Feel free to check out the full range of options with the api reference for a slider. + +[image1]: + +[image2]: \ No newline at end of file diff --git a/mintlify-docs/blogs/Sliders in zero-true.mdx b/mintlify-docs/blogs/Sliders in zero-true.mdx new file mode 100644 index 00000000..abec1a58 --- /dev/null +++ b/mintlify-docs/blogs/Sliders in zero-true.mdx @@ -0,0 +1,59 @@ +--- +title: 'Sliders in zero-true' +--- + + +## Creating a Slider + +Creating a slider in zero-true is simple. Type: + +```py +import zero-true as zt +slider=zt.Slider(id='slider') +``` + +![][image1] + +Run the cell in your notebook, and watch the slider appear below. + +## Slider Settings and Values + +Sliders have a minimum, maximum, and step in zero-true. The default values are 0 and 100 but you can set them to whatever you’d like. The slider value will return an integer or a float depending on what it is set to. + +```py +print("The slider value divided by 2 is:"+str(slider.value/2.0)) +``` + +![][image2] + +## Slider Use Cases + +Sliders can be used to capture any numeric input. Here is a more fleshed out example including filtering a dataframe: + +```py +import pandas as pd +import zero_true as zt + +novels_df = pd.read_html("https://en.wikipedia.org/w/index.php?title=Science_Fiction:_The_100_Best_Novels&oldid=1091082777", match='The 100 Best Novels')[0] + +#define a slider in zero-true to filter the data +slider=zt.Slider(id='slider',min=1, max=100,label='Move the Slider to Filter the DataFrame') +#set the first value to 100 to keep all the novels in there +if not slider.value: + slider.value=100 + +#display the dataframe with zero-true +zt.dataframe(id='df',df=novels_df[0:slider.value]) +``` + +![title](/blogs/gifs/slider.gif) + +## Customizing your slider + +You can also add different colors and labels to your slider to make it to your liking. Feel free to check out the full range of options with the api reference for a slider. + +[image1]: + +[image2]: + +[image3]: \ No newline at end of file diff --git a/mintlify-docs/blogs/Text Areas in zero-true.mdx b/mintlify-docs/blogs/Text Areas in zero-true.mdx new file mode 100644 index 00000000..144cb714 --- /dev/null +++ b/mintlify-docs/blogs/Text Areas in zero-true.mdx @@ -0,0 +1,50 @@ +--- +title: 'Text Areas in zero-true' +--- + +## Creating a Text Area + +Creating a text area in zero-true is simple. Type: + +```py +import zero-true as zt +text_area=zt.TextArea(id='txt') +``` + +![][image1] + +Run the cell in your notebook, and watch the text area appear below. + +## Text Area Settings and Values + +Text areas have a range of settings. For example you can add a label to your text area to clarify what you are asking of a user. To access the value they provide you simply use the “value” attribute on the component to access the string they typed: + +```py +print("The user just wrote "+text_area.value) +``` + +![][image2] + +## Text Area Use Cases + +Text inputs are useful when you want the user to input long form text. For example in this use case we ask for a user’s feedback. If we only gave them a TextInput they would have limited space to type but with a TextArea you can receive entire paragraphs of feedback: + +```py +import zero_true as zt + +#feedback area +feedback_area = zt.TextArea(id='txt_a',label= 'Submit you feedback') +``` + +![][image3] + +This works great for longer texts. For shorter texts we recommend that you use our TextInput component. + +## Customizing your Text Area + +You can also add different colors and labels to your text area to make it to your liking. Feel free to check out the full range of options with the api reference for our text area. + + +[image1]: + +[image2]: \ No newline at end of file diff --git a/mintlify-docs/blogs/Text Inputs in zero-true.mdx b/mintlify-docs/blogs/Text Inputs in zero-true.mdx new file mode 100644 index 00000000..eb8644f5 --- /dev/null +++ b/mintlify-docs/blogs/Text Inputs in zero-true.mdx @@ -0,0 +1,51 @@ +--- +title: 'Text Inputs in zero-true' +--- + +## Creating a Text Input + +Creating a text input in zero-true is simple. Type: + +```py +import zero-true as zt +text_input=zt.TextInput(id='txt') +``` + +![][image1] + +Run the cell in your notebook, and watch the text input appear below. + +## Text Input Settings and Values + +Text inputs have a range of settings. For example you can add a label to your text input to clarify what you are asking of a user. To access the value they provide you simply use the “value” attribute on the component to access the string they typed: + +```py +print("The user just wrote "+text_input.value) +``` + +![][image2] + +## Text Input Use Cases + +Text inputs are useful when you want the user to input a text value where the possible values are unknown or the number of options is too large to store in a list. For example in this use case we ask for a user’s name. Because we don’t have a list of users we can pull from we ask them to type it in themselves: + +```py +import zero_true as zt + +#name input +name_input = zt.TextInput(id='txt_i',label='Write you name') +``` + +![title](/blogs/gifs/text_input.gif) + +This works great for shorter texts. For longer texts we recommend that you use our TextArea component. + +## Customizing your Text Input + +You can also add different colors and labels to your text input to make it to your liking. Feel free to check out the full range of options with the api reference for our text inputs. + +[image1]: + +[image2]: + +[image3]: \ No newline at end of file diff --git a/mintlify-docs/blogs/What is Zero-True.mdx b/mintlify-docs/blogs/What is Zero-True.mdx new file mode 100644 index 00000000..1006f82b --- /dev/null +++ b/mintlify-docs/blogs/What is Zero-True.mdx @@ -0,0 +1,60 @@ +--- +title: 'What is zero-true?' +--- + +Zero-True is an open source python+sql notebook that was built to help individuals and teams collaborate on applications ranging from data visualization to building complex ML models. This project was started based on our own extensive experience with the current notebook ecosystem and frustration with existing solutions. Converting code and outputs from notebooks into snackable and remixable formats for other developers and non-technical audiences has never been as important as it is today. Data products require fast iteration with subject matter experts, a process that often starts in data notebooks but then requires an expensive translation process into dashboards and frontends. This should not be as complicated as it is today. We’ve been building zero-true to simplify sharing notebooks for almost 18 months now responding closely to feedback from teams actually working on ML products. + +To this end we have our own reactive notebook that will automatically parse your code to rerun cells based on changes in parent cells upstream (similar to Observable). This approach ensures your notebook stays consistent and solves some of the known issues with current iPython notebook based workflows. Zero-true includes an integrated UI library and streamlined deployment to help you share your work as a full fledged application. This means you can take what were previously ad-hoc workflows and transform them into deployable scripts with an integrated frontend. We are also working on features to help deploy your notebook as a part of ETL pipelines like chronjobs etc. + +If you’re just starting out with zero-true, this blog has some useful things to know. + +## Cells run top to bottom + +One of the first things you should know about zero-true is that your notebook runs top to bottom. You will not be able to reference variables that are defined below the cell you are currently in. This makes your code more readable to others you’re working with, as they don’t have to deal with non-linear code flows and can even help you reorient yourself faster when you come back to your own notebooks. + +![](/blogs/gifs/top_to_bottom.gif) + +## No hidden state + +Zero-True has no hidden state. This means rerunning code multiple times will give you consistent results each time. Take the example below: + +Cell 1: + +```py +my_list = [] +``` + +Cell 2: + +```py +my_list.append(1) +print(my_list) +``` + +If you want to know what the output will be in zero-true the answer is easy: It’s ‘\[1\]’ every time. You can see in the gif below that in zero-true, no matter how many times I rerun cell 2, I get the same answer. + +![](/blogs/gifs/no_hidden_state.gif) + +In current Ipython notebooks on the other hand you get a different answer each time (Google colab pictured below). Every time you rerun cell 2 you append to the same list and get a different answer. + +![](/blogs/gifs/jupyter_hidden_state.gif) + +## Related Cells Rerun Reactively + +We parse what cells are related in your notebook and automatically rerun downstream cells so that your notebook stays consistent. This helps you catch errors before they happen and provides an interactive coding experience. + +![](/blogs/gifs/reactive updates.gif) + +## Integrated UI library + +Our notebook includes an integrated UI library. Intuitive low code syntax allows you to add user inputs to your work and transform your experimentation into an actual application. This means that with one line of code, you can add buttons, sliders and text input components that integrate natively with our application. You can read more about that in a dedicated blogpost about our UI components. + +![](/blogs/gifs/iris_gif.gif) + +## Transforms Into an App + +You can preview what your work would look like deployed as an application directly from your notebook. For users that have been moved off of our waitlist, you can also publish to a live URL directly from your notebook. When you publish an app users can interact with UI components and optionally view the code you’ve written. If you’re interested in doing that contact us here\! + +![](/blogs/gifs/notebook_to_app.gif) + +We hope that this was a helpful introduction to zero-true\! 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