File Utilities

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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.

• GitHub Repository
• PyPi Page

General

input_to_file

[Source]

input_to_file(input_file, metadata = False)

Description:

Converts a base64 encoded string into a file object and metadata

Arguments:

Argument	Type	Description
input_file	str	Base64 encoded string, prefixed with metadata
metadata	bool (optional)	Flag to return metadata 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)	metadata is False
(io.BytesIO, str)	The decoded file data and its metadata	metadata is True

Example:

import io
import mecsimcalc as msc

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

# Expected output:
# {"file_type": "_io.BytesIO", "metadata": "data:image/jpeg;base64,"}

metadata_to_filetype

[Source]

metadata_to_filetype(metadata):

Description:

Extracts the file type from the metadata

Arguments:

Argument	Type	Description
metadata	str	The metadata string in the form "Data:(MIME type);base64,"(returned from input_to_file)

Returns:

Return Type	Description
str	The file type (e.g. "jpeg")

Example:

import mecsimcalc as msc

def main(inputs):
    input_file = inputs['file']
    file, metadata = msc.input_to_file(input_file, metadata=True)
    download_file_type = msc.metadata_to_filetype(metadata)
    return {"file_type": download_file_type}

# Expected output:
# {"file_type": "jpeg"}

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	Decoded file data (e.g. from input_to_file)

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']
    decoded_file = msc.input_to_file(input_file)
    df = msc.file_to_dataframe(decoded_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
get_file_type	bool	If True, the function also returns the file type (Defaults to False)

Returns:

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

Example:

import mecsimcalc as msc

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

# Expected output:
# {"dataframe": {
# "A": {0: "a", 1: "d"},
# "B": {0: "b", 1: "e"},
# "C": {0: "c", 1: "f"}}, "file_type": "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_type=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_type	bool	If True, the function also returns the file type (Defaults to False)

Returns:

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

Example:

import mecsimcalc as msc

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

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

print_image

[Source]

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

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")
download_file_type	str (optional)	The file type of the image when downloaded (Defaults to "png")

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", download_file_type="jpeg")
    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.jpeg'>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}