Mecsimcalc v0.1.6 documentation
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
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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 mecsimcalc as msc
def main(inputs):
input_file = inputs['file']
file, metadata = msc.input_to_file(input_file, metadata = True)
print(metadata)
print(type(file))
return {"file":file}
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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)
print(metadata)
download_file_type = msc.metadata_to_filetype(metadata)
print(download_file_type)
return {"file":file}
Text
string_to_file
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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:
Code step:
import mecsimcalc as msc
def main(inputs):
download_link = msc.string_to_file("Hello World!")
return {"download":download_link}
Outputs step:
Spreadsheets
file_to_dataframe
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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)
print(df)
return {"df":df}
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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)
print(df)
print(file_type)
return {"df":df}
print_dataframe
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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:
Code step:
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="FunkyTable", download_text="Download My Funky Table HERE!", download_file_type="xlsx")
return {
"table":table,
"download":download,
}
Outputs step:
Displaying Table
{{ outputs.table }}
Downloading Table
{{ outputs.download }}
Tables
table_to_dataframe
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table_to_dataframe(column_headers, rows) -> pd.DataFrame:
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)
print(df)
return {"df":df}
print_table
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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:
Code step:
import mecsimcalc as msc
def main(inputs):
column_headers = ["A", "B", "C"]
rows = [["a", "b", "c"], ["d", "e", "f"]]
table = msc.print_table(column_headers, rows)
return {"table":table}
Outputs step:
Displaying Table
{{ outputs.table }}
Images
file_to_PIL
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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:
Code step:
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}
Outputs step:
Displaying Image
{{ outputs.image }}
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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)
print(file_type)
print(type(image))
return {"image":image}
print_image
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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:
Code step:
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,
}
Outputs step:
Displaying Image
{{ outputs.image }}
Downloading Image
{{ outputs.download }}
Plots
print_plot
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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:
Code step:
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,
}
Outputs step:
Displaying Image
{{ outputs.image }}
Downloading Image
{{ outputs.download }}
append_to_google_sheet
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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 = {
}
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)
send_gmail
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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]
]
msc.send_gmail(sender_email, receiver_email, subject, app_password, values)