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MecSimCalc File Utilities v0.3.0

This library is designed to provide a set of functions for handling and converting various types of data, such as base64 encoded data, Pandas DataFrames, and Pillow images.

General

input_to_file

[Source]

input_to_file(input_file, file_extension = False)

Description:

Converts a base64 encoded string into a file object and file extension

Arguments:

Argument Type Description
input_file str Base64 encoded string (file you get from inputs['file'])
get_file_extension bool (optional) Flag to return the file extension with the file. (Defaults to False)

Raises:

Exception Description
ValueError If the input string doesn't contain ';base64,' to separate metadata and file data.

Returns:

Return Type Description Condition
io.BytesIO The decoded file data (The thing you get when you open a file in Python) get_file_extension is False
(io.BytesIO, str) The decoded file data and its file extension get_file_extension is True

Example:

import io
import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    file, file_extension = msc.input_to_file(input_file, get_file_extension=True)
    return {"file_type": type(file).__name__, "extension": file_extension}

# Expected output:
# {"file_type": "_io.BytesIO", "extension": ".jpg"}

Text

string_to_file

[Source]

string_to_file(
    text
    filename= "myfile",
    download_text = "Download File",
)

Description:

Generates a downloadable text file containing the given text

Arguments:

Argument Type Description
text str Text to be downloaded
filename str (optional) Name of the download file. (Defaults to "myfile")
download_text str (optional) Text to be displayed as the download link. (Defaults to "Download File")

Raises:

Exception Description
TypeError If the input text is not a string.

Returns:

Return Type Description
str HTML download link

Example:

Python

import mecsimcalc as msc

def main(inputs):
    download_link = msc.string_to_file("Hello World!")
    return {"download": download_link}

# Expected output:
# {"download": "<a href='data:text/plain;base64,SGVsbG8gV29ybGQh' download='myfile.txt'>Download File</a>"}

Jinja2

# outputs.downloadLink is the html download link generated by the function
{{ outputs.download }}

Spreadsheets

file_to_dataframe

[Source]

file_to_dataframe(file_data):

Description:

Converts a base64 encoded file data into a pandas DataFrame

Arguments:

Argument Type Description
file_data io.BytesIO An open file (e.g. from input_to_file or file.open())

Raises:

Exception Description
pd.errors.ParserError If the file data cannot be converted to a DataFrame (i.e. file is not an Excel or CSV file or is corrupted)

Returns:

Return Type Description
pd.DataFrame DataFrame created from file data

Example:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    open_file = msc.input_to_file(input_file)
    df = msc.file_to_dataframe(open_file)
    return {"dataframe": df.to_dict()}

# Expected output:
# {"dataframe": {
# "A": {0: "a", 1: "d"},
# "B": {0: "b", 1: "e"},
# "C": {0: "c", 1: "f"}}}

input_to_dataframe

[Source]

input_to_dataframe(file):

Description:

Converts a base64 encoded file data into a pandas DataFrame

Arguments:

Argument Type Description
input_file str Base64 encoded file data (file you get from inputs['file'])
get_file_extension bool If True, the function also returns the file extension (Defaults to False)

Returns:

Return Type Description Condition
pd.DataFrame DataFrame created from file data get_file_extension is False
(pd.DataFrame, str) Tuple containing the DataFrame and the file extension get_file_extension is True

Example:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    df, get_file_extension = msc.input_to_dataframe(input_file, get_file_type=True)
    return {"dataframe": df.to_dict(), "extension": get_file_extension}

# Expected output:
# {"dataframe": {
# "A": {0: "a", 1: "d"},
# "B": {0: "b", 1: "e"},
# "C": {0: "c", 1: "f"}}, "extension": ".csv"}

print_dataframe

[Source]

print_dataframe(
    df,
    download = False,
    download_text = "Download Table",
    download_file_name = "mytable",
    download_file_type = "csv",
):

Description:

Creates an HTML table and a download link for a given DataFrame

Arguments:

Argument Type Description
df pd.DataFrame DataFrame to be converted
download bool (optional) If True, function returns a download link (Defaults to False)
download_text str (optional) Text to be displayed as the download link (Defaults to "Download Table")
download_file_name str (optional) Name of file when downloaded (Defaults to "mytable")
download_file_type str (optional) File type of downloaded file (Defaults to "csv")

Returns:

Return Type Description Condition
str HTML table download is False
Tuple[str, str] (HTML table, HTML download link) download is True

Example:

Python Code:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    df = msc.input_to_dataframe(input_file)
    table, download = msc.print_dataframe(df, download=True, download_file_name="Table", download_text="Download My Table HERE!", download_file_type="xlsx")
    return {"table": table, "download": download}

# Expected output:
# {"table": "<table>...</table>",
# "download": "<a href='data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,...' download='Table.xlsx'>Download My Table HERE!</a>"}

Output using Jinja2 Template:

# outputs.table is the HTML table
Displaying Table
{{ outputs.table }}

# outputs.download is the download link
Downloading Table
{{ outputs.download }}

Tables

table_to_dataframe

[Source]

table_to_dataframe(column_headers, rows):

Description:

Create a DataFrame from given rows and column headers

Arguments:

Argument Type Description
column_headers List[str] List of column headers
rows List[List[str]] List of rows to be converted into a DataFrame. Each column is a list of strings

Returns:

Return Type Description
pd.DataFrame DataFrame created from headers and rows

Example:

import mecsimcalc as msc

def main(inputs):
    column_headers = ["A", "B", "C"]
    rows = [["a", "b", "c"], ["d", "e", "f"]]
    df = msc.table_to_dataframe(column_headers, rows)
    return {"dataframe": df.to_dict()}

# Expected output:
# {"dataframe": {
# "A": {0: "a", 1: "d"},
# "B": {0: "b", 1: "e"},
# "C": {0: "c", 1: "f"}}}

print_table

[Source]

print_table(column_headers, rows):

Description:

Creates an HTML table from given rows and column headers

Arguments:

Argument Type Description
column_headers List[str] List of column headers
rows List[List[str]] List of rows to be converted into a table. Each column is a list of strings
index bool (optional) Whether to use the first column as the DataFrame's index. (Defaults to True)

Returns:

Return Type Description
str HTML table created from rows and headers

Example:

Python Code:

column_headers = ["A", "B", "C"]
rows = [["a", "b", "c"], ["d", "e", "f"]]
table = print_table(column_headers, rows)
return {
        "table":table,
    }

Output using Jinja2 Template:

# outputs.table is the HTML table
Displaying Table
{{ outputs.table }}

Images

file_to_PIL

[Source]

file_to_PIL(file):

Description:

Transforms a file into a Pillow Image object

Arguments:

Argument Type Description
file str Decoded file data (returned from input_to_file)

Raises:

Exception Type Description
ValueError If the file does not contain image data

Returns:

Return Type Description
Image Pillow Image object

Example:

Python Code:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    decoded_file = msc.input_to_file(input_file)
    image = msc.file_to_PIL(decoded_file)
    return {"image": image}

# Expected output:
# {"image": <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=...>}

Output using Jinja2 Template:

# outputs.image is the Pillow Image object
Displaying Image
{{ outputs.image }}

input_to_PIL

[Source]

input_to_PIL(input_file, get_file_extension=False):

Description:

Converts a base64 encoded file data into a pillow image

Arguments:

Argument Type Description
input_file str Base64 encoded file data
get_file_extension bool If True, the function also returns the file extension (Defaults to False)

Returns:

Return Type Description Condition
PIL.Image.Image Pillow Image object get_file_extension is False
Tuple[PIL.Image.Image, str] (pillow image, metadata) get_file_extension is True

Example:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    image, file_extension = msc.input_to_PIL(input_file, get_file_extension=True)
    return {"image": image, "file_extension": file_extension}

# Expected output:
# {"image": <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=...>, "file_extension": "jpeg"}

print_image

[Source]

print_image(
    image,
    width = 200,
    height = 200,
    original_size = False,
    download = False,
    download_text = "Download Image",
    download_file_name= "myimg",
):

Description:

Transforms a Pillow image into an HTML image, with an optional download link

Arguments:

Argument Type Description
image PIL.Image.Image Pillow image
width int (optional) Output width of the image in pixels (Defaults to 200)
height int (optional) Output height of the image in pixels (Defaults to 200)
original_size bool (optional) If True, the HTML image will be displayed in its original size (Defaults to False)
download bool (optional) If True, function returns a download link (Defaults to False)
download_text str (optional) The text to be displayed on the download link (Defaults to "Download Image")
download_file_name str (optional) The name of the image file when downloaded (Defaults to "myimg")

Returns:

Return Type Description Condition
str HTML image download is False
Tuple[str, str] (HTML image, download link) download is True

Example:

Python Code:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    image, metadata = msc.input_to_PIL(input_file)
    html_image, download = msc.print_image(image, original_size=True, download=True, download_text="Download Image Here", download_file_name="myimage")
    return {"image": html_image, "download": download}

# Expected output:
# {"image": "<img src='data:image/jpeg;base64,...' width='...' height='...'>",
# "download": "<a href='data:image/jpeg;base64,...' download='myimage.png'>Download Image Here</a>"}

Output using Jinja2 Template:

# outputs.image is the HTML image
Displaying Image
{{ outputs.image }}

# outputs.download is the download link
Downloading Image
{{ outputs.download }}

Plots

print_plot

[Source]

print_plot(
    plot_obj,
    width = 500,
    dpi= 100,
    download= False,
    download_text = "Download Plot",
    download_file_name = "myplot",
)

Description:

Converts a matplotlib.pyplot.axis or matplotlib.figure into an HTML image tag and optionally provides a download link for the image

Arguments:

Argument Type Description
plot_obj axes or figure Matplotlib figure
width int (optional) Output width of the image in pixels (Defaults to 500)
dpi int (optional) Output dpi of the image in pixels (Defaults to 100)
download bool (optional) If True, function returns a download link (Defaults to False)
download_text str (optional) The text to be displayed on the download link (Defaults to "Download Plot")
download_file_name str (optional) The name of the image file when downloaded (Defaults to "myplot")

Returns:

Return Type Description Condition
str HTML image download is False
Tuple[str, str] (HTML image, HTML download link) download is True

Example:

Python Code:

import matplotlib.pyplot as plt
import numpy as np
import mecsimcalc as msc

def main(inputs):
    x = np.linspace(0, 2 * np.pi, 400)
    y = np.sin(x)
    fig, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title('A single plot')
    image, download = msc.print_plot(fig, width=500, dpi=100, download=True, download_text="Download Sin Function Plot", download_file_name="sin(x)")
    return {"image": image, "download": download}

# Expected output:
# {"image": "<img src='data:image/jpeg;base64,...' width='500' height='...'>",
#  "download": "<a href='data:image/jpeg;base64,...' download='sin(x).jpeg'>Download Sin Function Plot</a>"}

Output using Jinja2 Template:

# outputs.image is the HTML image
Displaying Image
{{ outputs.image }}

# outputs.download is the download link
Downloading Image
{{ outputs.download }}

print_animation

[Source]

print_animation(
    ani,
    fps = 30,
    save_dir = "/tmp/temp_animation.gif"):

Description:

Converts a matplotlib animation into an animated GIF. Returns an HTML image tag to display it in your app.

Arguments:

Argument Type Description
ani FuncAnimation The matplotlib animation to be converted.
fps int (optional) Frames per second for the animation. (Defaults to 30)
save_dir str (optional) The directory to temporarily save files. You can only write to the tmp directory in mecsimcalc. Defaults to "/tmp/temp_animation.gif"

Returns:

Return Type Description
str The HTML image tag as a string.

Example:

import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import numpy as np
import mecsimcalc as msc

def main(inputs):
    fig, ax = plt.subplots()
    x = np.linspace(0, 2*np.pi, 100)
    y = np.sin(x)
    line, = ax.plot(x, y)
    def update(frame):
        line.set_ydata(np.sin(x + frame / 10))
        return line,
    ani = FuncAnimation(fig, update, frames=100)
    animation = msc.print_animation(ani)
    return {"animation": animation}

# Expected output:
# {"animation": "<img src='data:image/gif;base64,...'>"}

animate_plot

[Source]

animate_plot(
    x,
    y,
    duration = 3,
    fps = 15,
    x_label = "x",
    y_label = "y",
    title = "y = f(x)",
    show_axes = True,
    follow_tip = False,
    save_dir = "/tmp/temp_animation.gif",
    follow_tip = False,
    hold_last_frame = 1.0,
)

Description:

Creates an animated plot from given x and y data and returns it as an HTML image tag.

Arguments:

Argument Type Description
x np.ndarray The x-coordinates of the data points.
y np.ndarray The y-coordinates of the data points.
duration float (optional) The duration of the animation in seconds. Defaults to 3.
fps float (optional) Frames per second for the animation. Defaults to 15.
x_label str (optional) The label for the x-axis. Defaults to "x".
y_label str (optional) The label for the y-axis. Defaults to "y".
title str (optional) Title of the plot. Defaults to "y = f(x)".
show_axes bool (optional) Whether to show the x and y axes. Defaults to True.
follow_tip bool (optional) Whether to follow the tip of the line as it moves along the x-axis. Defaults to False.
hold_last_frame float (optional) The duration to hold the last frame in seconds. Defaults to 1.0.
save_dir str (optional) The directory to temporarily save files. You can only write to the tmp directory in mecsimcalc. Defaults to "/tmp/temp_animation.gif"

Returns:

Return Type Description
str The HTML image tag containing the animated plot.

Example:

import numpy as np
import mecsimcalc as msc

def main(inputs):
    x = np.linspace(0, 10, 100)
    y = np.sin(x)
    animation_html = msc.animate_plot(x, y, duration=4, title="Sine Wave", show_axes=True)
    return {"animation": animation_html}

# Expected output:
# {"animation": "<img src='data:image/gif;base64,...'>"}

plot_slider

[Source]

plot_slider(
    f_x,
    x_range,
    y_range = None,
    title = "",
    x_label = "x",
    y_label = "y",
    num_points = 250,
    initial_value = 1,
    step_size = 0.1,
    slider_range = (-10, 10),
):

Description:

Creates an interactive plot with a slider using Plotly, allowing the user to dynamically update the plot based on a parameter.

Arguments:

Argument Type Description
f_x Callable[[float, np.ndarray], np.ndarray] A function that takes a float and an array of x-values, and returns an array of y-values.
x_range Tuple[float, float] A tuple defining the range of x-values (start, end) for the plot.
y_range Tuple[float, float] (optional) A tuple defining the range of y-values (start, end) for the plot. Defaults to None.
title str (optional) Title of the plot. Defaults to "".
x_label str (optional) Label for the x-axis. Defaults to "x".
y_label str (optional) Label for the y-axis. Defaults to "y".
num_points int (optional) Number of points to plot (line resolution). Defaults to 250.
initial_value float (optional) Initial value of the slider. Defaults to 1.
step_size float (optional) Step size for the slider. Defaults to 0.1.
slider_range Tuple[float, float] (optional) Range for the slider values (start, end). Defaults to (-10, 10).

Returns:

Return Type Description
str The HTML string containing the Plotly interactive plot.

Example:

import mecsimcalc as msc

def parabola(a, x):
    return a * x ** 2

def main(inputs):
    plot_html = msc.plot_slider(parabola, x_range=(-10, 10), y_range=(-100, 100))
    return {"plot": plot_html}

# Expected output:
# The `plot_html` can be used in a web page to display the interactive plot.

Quiz Toolkit

append_to_google_sheet

[Source]

append_to_google_sheet(
    service_account_info = {...},
    spreadsheet_id = "123abc...",
    values = [["name", 12837, ...]],
    range_name = "Sheet1!A1",
    include_timestamp = True
)

Description:

This function appends given values to a specified Google Sheet and optionally includes a current timestamp with each entry. It transforms data into a Google Sheets document, facilitating dynamic data entry directly from your application.

Arguments:

Argument Type Description
service_account_info dict The service account credentials used for Google Sheets API authentication.
spreadsheet_id str The unique identifier of the target Google Spreadsheet.
values list of lists The data to append. Each list element represents a row of data.
range_name str (optional) The A1 notation of the range to start appending data. Defaults to "Sheet1!A1".
include_timestamp bool (optional) If True, appends the current timestamp to each row of data. Defaults to True.

Returns:

Return Type Description
dict The response from the Google Sheets API, containing details of the append operation.

Example:

Code step:

import mecsimcalc as msc

def main(inputs):
    service_account_info = {
        # Your service account info here
    }
    spreadsheet_id = 'your_spreadsheet_id_here'
    values = [
        [inputs['input_1'], inputs['input_2'], inputs['input_3']],
    ]
    result = msc.append_to_google_sheet(service_account_info, spreadsheet_id, values)
    return {"result": result}

# Expected output:
# {"result": {"spreadsheetId": "your_spreadsheet_id_here",
#  "updatedRange": "Sheet1!A1:C1",
#  "updatedRows": 1, "updatedColumns": 3, "updatedCells": 3}}

send_gmail

[Source]

send_gmail(
    sender_email='sender@example.com',
    receiver_email='receiver@example.com',
    subject="Quiz",
    app_password = "xxxx xxxx xxxx xxxx",
    values = [
    ["name", "grade"]
    ]
)

Description:

This function sends an email with specified values formatted in the message body, utilizing a service account for authentication.

Arguments:

Argument Type Description
sender_email str The email address of the sender.
receiver_email str The email address of the receiver.
subject str The subject line of the email.
app_password str The app-specific password for the sender's email account.
values list A list of lists. Each list contains data to be included in the email body.

Returns:

Return Type Description
bool Returns True if the email was sent successfully, otherwise False.

Example Usage:

import mecsimcalc as msc

def main(inputs):
    sender_email = 'sender@example.com'
    receiver_email = 'receiver@example.com'
    subject = 'Test Email'
    app_password = 'your_app_password_here'

    name = inputs['name']
    grade = inputs['grade']

    values = [
        [name, grade]
    ]

    result = msc.send_gmail(sender_email, receiver_email, subject, app_password, values)
    return {"result": result}

# Expected output:
# {"result": True}

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