MecSimCalc File Utilities v0.2.1
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, 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}