| |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
|
| |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| Filters (Kernels) in ML |
Introduction |
| K-means clustering and PCA for failure analysis |
Introduction |
| Four/five V of big data |
Introduction |
| Apache Flink |
Introduction |
| Facets Overview |
Introduction |
| Trade-offs between fairness and performance |
Introduction |
| Principles of ethical and responsible ML (selection bias, confirmation bias, automation bias, model fairness) |
Introduction |
| Feature engineering in semiconductor manufacturing ML |
Introduction |
| FastText for ML |
Introduction |
| HDFS (Hadoop Distributed File System) |
Introduction |
| Ingesting data in Hadoop (Sqoop, Flume, Kafka, NiFi) |
Introduction |
| Context-free grammar (CFG) |
Introduction |
| Formal grammar |
Introduction |
| Feedforward neural network |
Introduction |
| tf.keras.datasets (e.g. MNIST, CIFAR-10, CIFAR-100, Fashion MNIST) |
Introduction |
| Guess and check algorithm with a combination of a for loop and an if statement |
Introduction |
| Function approximation |
Introduction |
| Fit and Smooth Plotted Curves |
Introduction |
| Precision, Recall, False Positive Rate, and False Negative Rate (Miss Rate or False Negative Proportion) |
Introduction |
| First-order logic (FOL) |
Introduction |
| Analyzing the impact of fabrication conditions on semiconductor wafer fail rates |
Introduction |
| Feature engineering |
Introduction |
| Breadth-First Search (BFS) |
Introduction |
| Depth-first search (DFS) |
Introduction |
| Cost/loss function versus reward function |
Introduction |
| Optimal value function in Markov Decision Process (MDP) |
Introduction |
| Finite-horizon MDP (Markov Decision Process) |
Introduction |
| Q-Learning with Function Approximation (Deep Q-Network - DQN) |
Introduction |
| Model-Free RL and Model-based RL (reinforcement learning) |
Introduction |
| State transition function (probability) in reinforcement learning |
Introduction |
| Locate/find the center of a bright (maximum/highest intensity) spot in an image |
Introduction |
| Machine learning example step-by-step (wafer fail analysis) |
Introduction |
| Find nearest white pixel to a given pixel location on an binary image |
Introduction |
| Extract the least/most frequency/duplicate/occurrence element in a list |
Introduction |
| Functional API to create a Keras model with TensorFlow |
Introduction |
| Find duplicate items in a list |
Introduction |
| Draw smiling face emoji |
Introduction |
| Machine learning for few things |
Introduction |
| Least squares fit |
Introduction |
| Convert strings to number (integers/float) |
Introduction |
| |
|
| .find_element() |
Introduction |
| ◆ |
find_element(By.XPATH, " ") |
Introduction |
| ◆ |
find_element(CSS_SELECTOR, " ") |
Introduction |
| |
|
| tf.function |
Introduction |
| Try a number of times before exception or fail |
Introduction |
| Formats of datasets for classification |
Introduction |
| Put most code into a function or class |
code |
| Create a function called main() to contain the code you want to run |
code |
| Positions and colors of mouse/cursor and features |
Introduction |
| Change the font size for selected text |
Introduction |
| Launch Replace menu from Find menu |
Introduction |
| Move the cursor/mouse to the found, similar spots one-by-one |
Introduction |
| Copy and apply formatting in Word and PowerPoint |
Introduction |
| Find the values of the keys |
Introduction |
| Bring/activate an application/window to most front/foreground |
Introduction |
| Bind Python functions and methods to events (similar to if loops) |
Introduction |
| Term Frequency-Inverse Document Frequency (TF-IDF) |
Introduction |
| Find/predict the best word similarity, e.g. car |
Introduction |
| Immediately invoked function expression |
code |
| Swap the order of arguments in a function |
Introduction |
| Access variable inside and outside a function |
Introduction |
| Numpy: Access the element at the second row, the third entry, access a specific row or a column, access some elements (submatrix), or replace/modify an element in the array, print a transfer of an array, access array under conditions or filtering |
Introduction |
| Pint summary of the statistic data, change data format, sort/group columns |
Introduction |
| Popup windows with frames |
Introduction |
| Find a similar feature and then click it |
Introduction |
| Find minimum and maximum values in a list |
Introduction |
| Computing equations and formulas with Python |
Examples. Numerical integration at code. |
| Set the output image to zero everywhere except my mask (color filter), and display red, green, and blue (RGB) channels of an image. |
code, code. |
| Convert jpg format to tif format |
code |
| Find edges of images |
code, Introduction |
| Find the greatest of three numbers |
code1, code2, code3 |
| Get the list of the methods for a function |
Introduction |
| Find elements on a webpage |
Introduction |
| Stability/reliability of find_element(By.xxx, "") |
Introduction |
| Text Format in pptx |
Introduction |
| Find latitude and longitude of a place in a map |
Introduction |
| Find a specific word in a webpage and count occurrences |
Introduction |
| matplotlib.pyplot axis/text color (xticks, rotation, xlabel, ylabel, title, fontsize, grid(), legend(), show()) |
Introduction |
| Find common elements/items between two lists |
Introduction |
| Fill in closed curves |
Introduction |
| Find contours in an image and their areas and coordinates |
Introduction |
| Global access to a variable inside a function from outside of the function |
Introduction |
| Search/extract/find text on an image |
Introduction |
| Break/exit/skip a function/code line after a certain time |
Introduction |
| Change/capitalize the case of the first letter of a string |
Introduction |
| Patterns on wafers commonly reflecting specific process failure information |
Introduction |
| Fault analysis/PFA (Physical Failure Analysis) time and efficiency |
Introduction |
| Wafer map failure pattern recognition (WMFPR) and similarity ranking (SR) |
Introduction |
| Histogram for wafer analysis (e.g. percentage and frequency of grey level in the image) |
Introduction |
| Laplacian filtering |
Introduction |
| Canny filter |
Introduction |
| Few-shot learning |
Introduction |
| Pass variables between functions/from one to another |
Introduction |
| Methods of physical failure analysis (PFA) of ICs |
Introduction |
| Cost (expense) and speed (fastest and slowest) of computation in ML |
Introduction |
| Cumulative Distribution Function (CDF) |
Introduction |
| Mixture of Gaussians (MoG) versus Factor Analysis (FA) |
Introduction |
| Factor Analysis Model |
Introduction |
| Isolation forest algorithm |
Introduction |
| ML example: face recognition algorithm |
Introduction |
| Finding a correct loss (risk, objective) function for a specific problem |
Introduction |
| Number (size) of features in ML |
Introduction |
| (Forward and backward) propagation equations |
Introduction |
| Holidays/Festivals/Vocations (Thanksgiving/Christmas) |
Introduction |
| Finance analysis |
Introduction |
| True Function |
Introduction |
| Deterministic function |
Introduction |
| No Free Lunch Theorems |
Introduction |
| Frequentist approach versus Bayesian approach |
Introduction |
| Kernel tricks and kernel function |
Introduction |
| Mathematical equations, formulas and inequalities used in machine learning |
Introduction |
| Geometric Margin versus Functional Margin |
Introduction |
| Functional margin in ML |
Introduction |
| Feature vector and number of features |
Introduction |
| Fully Connected Layers (FC) in Deep Learning |
Introduction |
| Indicator function |
Introduction |
| Parameters, features and examples in ML |
Introduction |
| Canonical response function/canonical link function |
Introduction |
| Logistic function/sigmoid function |
Introduction |
| Latent features and latent variables |
Introduction |
Comparison between mean squared error (MSE), absolute error (L1 Loss) and fourth-power loss
|
Introduction |
| Exponential Family: Parameter, Sufficient Statistic, Natural Parameter, Base Measure and Log-Partition Function (Bernoulli distribution and Gaussian distribution) |
Introduction |
Probability density function (PDF): comparisons between (normal (gaussian) distribution, uniform distribution, exponential distribution and poisson distribution)
|
Introduction |
| |
|
| Input data (feature) in ML |
Introduction |
| ◆ |
Feature analysis/feature importance analysis/weight of feature |
Introduction |
| ◆ |
Feature importance for Multinomial Naive Bayes algorithm |
Introduction |
| ◆ |
Feature extractions from wafers |
Introduction |
| |
✔ |
Feature extraction using radon transform |
Introduction |
| ◆ |
Categorical features preprocessing layers |
Introduction |
| ◆ |
feature_extraction.text |
(code). (code). (code) |
| ◆ |
Feature ingestion |
Introduction |
| ◆ |
Vertex AI Feature Store |
Introduction |
| |
✔ |
tf.feature_column.bucketized_column |
Introduction |
| |
✔ |
tf.feature_column.categorical_column_with_identity |
Introduction |
| ◆ |
Feature and feature vector/Featurization |
Introduction |
| ◆ |
Outlier of feature |
(code) |
| ◆ |
Feature selection |
Introduction |
| |
✔ |
Forward Search method of feature selection |
Introduction |
| |
✔ |
Feature selection: removing unnecessary (constant & quasi constant) features |
Introduction |
| |
✔ |
Feature selection: removing multicollinearity |
Introduction |
| |
✔ |
Feature selection: Univariate feature selection |
Introduction |
| |
✔ |
Feature Selection: Chi Square to select dependent and independent variables |
Introduction |
| |
|
| |
|
| |
|
|
|
|
|
|
|
| Convex optimization, convexity of loss functions, convex functions and convex sets |
Introduction |
| Loss (risk, cost, objective) function |
Introduction |
| Finite Hypothesis Class versus Infinite Hypothesis Class |
Introduction |
| Natural Language Processing (NLP) approaches in addressing the Failure Analysis (FA) search problem |
Introduction |
| Percentages of information received through different senses (eye, nose, ear and hand feeling) |
Introduction |
| Variance Inflation Factors (VIFs) |
Introduction |
| Hypothesis class/hypothesis family/predictor class/model class/hypothesis family/predictor family/model family (h) |
Introduction |
| Parameterized family and model parameter |
Introduction |
| Brute force discretization |
Introduction |
| Finite Hypothesis Class/finite Hypothesis Analysis |
Introduction |
| Combine multiple images into a single multi-page/frame image or vice versa (split a single multi-page image to multiple images) |
Introduction |
| Read outlook messages in .msg format |
Introduction |
| Summary/templates of plotting graphs/figures |
Introduction |
| Fréchet Inception Distance (FID) coefficient |
Introduction |
| Format strings |
Introduction |
| Send a variable from one script (back) to another script with a function |
Introduction |
| Extract the first or last N letters from a string |
Introduction |
| String template class for formating strings (F-strings (for calculation) (f"{}"), format() method ({}), %s, %d, Template ($)) |
Introduction |
| Remove/reload/unload an imported module/function/script |
Introduction |
| |
|
| Plot multiple images on the same figure by hiding x- and y-labels |
Introduction |
| |
|
| Insert paragraphs of texts into Python script (f"""/f''') |
Introduction |
| Automatically restart script execution after it breaks/fails/error |
Introduction |
| Count the number of the pages in a single multi-page/frame image |
Introduction |
| Random (Bootstrap) Forests |
Introduction |
| |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| K-Fold Cross-Validation |
Introduction |
| Fairness Analysis and Python Libraries |
Introduction |
| Summary/templates/examples of pptx and PowerPoint format |
Introduction |
Continue script execution no matter whether some try fails or not (finally)
|
Introduction |
| Calculating the area fraction of each circle overlapped by a square grid and build wafer map |
Introduction |
| Get the frequency of occurrence of a string in a column DataFrame |
Introduction |
| Trick: return True and return False |
Introduction |
| |
|
| Folder |
|
| ◆ |
Get the current directory/folder path |
Introduction |
| ◆ |
Count how many (number) files and folders in a directory |
Introduction |
| ◆ |
Check if a directory is empty; find the position/index of a particular file/folder in a file directory/path; remove folder or file level by level (layer by layer) from its directory/path |
Introduction |
| ◆ |
Monitor multiple changed of folder and files |
Introduction |
| ◆ |
Monitor the current folder |
Introduction |
| ◆ |
Move(remove) all files from original folder in a directory to a new directory |
Introduction |
| ◆ |
Delete the entire directory and/or all the files in the directory/folder |
Introduction |
| ◆ |
Check if a file/folder exists or not (Cannot find a specific file/folder? a specific folder in the path? select specific folders to form a string, split a dos path into its components, and then print the list, or check files with extension) |
Introduction |
| ◆ |
Randomly open an image/file in a specific folder |
Introduction |
| ◆ |
Work with (e.g. open) all/every files and subfolders/subdirectory in a folder (does not include any files or include all files in subfolders) |
Introduction |
| ◆ |
Open folders and explorer |
Introduction |
| ◆ |
Copy images to a different folder/Save an image in a new folder |
code, code. code. code. |
| ◆ |
Select/input a folder/directory/path for later to be called to use |
Introduction |
| ◆ |
Folder for saving images from screenshot obtained by Snipping Tool on windows |
Introduction |
| ◆ |
Get/list immediate subdirectories/subfolders |
Introduction |
| ◆ |
Create a temporary file or directory/folder |
Introduction |
|
|
|
| File |
|
| ◆ |
Cheatsheet of folder and file |
Introduction |
| ◆ |
Time and date used as a file/folder name stamp (e.g. duplicate a file in the same folder) |
Introduction |
| ◆ |
Modify file path/directory by changing folder names by merging a list |
Introduction |
| ◆ |
Check/find/get a file name/all file names or the last folder name (e.g. from a path/directory) |
Introduction |
| ◆ |
Check whether or not a cell value in a column of a CSV file matchs a value in a column of another CSV file, then do something: e.g. add a value to another column of a csv file |
Introduction |
| ◆ |
Close file after reading a file: avoid file locking |
Introduction |
| ◆ |
With a default folder |
code1 and code2 |
| ◆ |
Delete a single file |
Introduction |
| ◆ |
Creat a file name, folder name. {}{}....format. Manipulation of file and folder names (rename file name and folder name): i) Rename the file, and then open the file. If the folder exists, then no file will be copied, but the file will still be opened. ii) Print and export the folder names and file names (with or without extensions) from a folder into a text file. iii) csv2image filename |
Introduction |
| ◆ |
Get the latest/newest/most recent file in a folder |
Introduction |
| ◆ |
Collect the file list in a folder into a csv file |
Introduction |
| ◆ |
Check updated new files in a folder |
Introduction |
| ◆ |
(Find) file size/find the largest file in a directory/folder |
Introduction |
| ◆ |
Write special/certain rows (row-by-row) of one csv file to another csv file |
Introduction |
| ◆ |
FileExistsError |
Introduction |
| ◆ |
Check existence of phrase on text file line-by-line |
Introduction |
| ◆ |
Check if a file exists again (double check) |
Introduction |
| ◆ |
Remove duplicate cell values from a csv file/dataframe (keeping the first/top one) |
Introduction |
| ◆ |
Create a Batch File to Run a Python Script |
Introduction |
| ◆ |
Read a frequently updated file periodically (similar to watchdog) |
Introduction |
| ◆ |
Read a frequently updated file periodically (similar to watchdog) |
Introduction |
| ◆ |
Plot graph/figure/image from CSV file |
Introduction |
| ◆ |
Plot graph/figure/image from CSV file/DataFrame by removing/hiding blank/empty cells with axis range (plt.xlim()) |
Introduction |
| ◆ |
Plot data into the same graph/figure/image from different csv files |
Introduction |
| ◆ |
Plot data into the same graph/figure/image from different csv files |
Introduction |
| ◆ |
Compare/check if two text files have the same contents |
Introduction |
| ◆ |
Compute the similarity between two text documents/files |
Introduction |
| ◆ |
Print the files and keyword occurrence which have been searched from a ppt file |
Introduction |
| ◆ |
Extract text/check specific text from multiple powerpoint/pptx files |
Introduction |
| ◆ |
Merge/combine two pptx files into one |
Introduction |
| ◆ |
Count number of lines in a text file |
Introduction |
| ◆ |
Count occurrence/nubmer of words/phrase in a text file |
Introduction |
| ◆ |
Convert a text file to a string |
Introduction |
| ◆ |
Convert PDF file to text file |
Introduction |
| ◆ |
Write/save content to a text file/append a string into a text file. |
Introduction |
| ◆ |
Extract pdf pages to form new pdf files |
Introduction |
| ◆ |
Generate text file with the bank of collecting all words, characters and strings from news |
Introduction |
| ◆ |
Remove \n in string or new line in txt/text file |
Introduction |
| ◆ |
Find and remove duplicate/same lines in a text file |
Introduction |
| ◆ |
Add/insert a column into an existing csv file |
Introduction |
| ◆ |
Copy a file or all files (with os.mkdir) to save to somewhere (create a directory first if it does not exist) |
Introduction |
| ◆ |
Monitor specific new files and execute the file |
Introduction |
| ◆ |
Watchdog for monitoring specific file or files with specific extension, and then run another file from watchdog |
Introduction |
| ◆ |
Find and convert the file time/date and compare with the current time |
Introduction |
| ◆ |
Check if both files are the same file, e.g. symbolic link, shortcut |
Introduction |
| ◆ |
Check whether a file is empty or not |
Introduction |
| ◆ |
Run multiple Python files/scripts one after another |
Introduction |
| ◆ |
Create CSV files (e.g. with headers only) |
Introduction |
| ◆ |
Remove duplicate cell values from a csv file |
CSV: Introduction |
| ◆ |
Upload files to webpages |
Introduction |
| ◆ |
Open and close specific files |
Introduction |
| ◆ |
Move file(s) from one directory to another |
Introduction |
| ◆ |
Watchdog for monitoring specific file or files with specific extension |
Introduction |
| ◆ |
Simple ways to execute another python file when a new file has been uploaded |
Introduction |
| ◆ |
List all files and directories which has specific files or files with specific extensions |
Introduction |
| ◆ |
Sort a text file |
Introduction |
| ◆ |
Call and then run your own functions and modules in different/other Python files; Python run another Python script |
Introduction |
| ◆ |
Keyword search function/check whether or not a string is within another string (a space is included as a string character) |
Introduction |
| ◆ |
Merge/combine two text files into a new text file, add a new line to the beginning of a text file |
Introduction |
| ◆ |
watchdog to look for filesystem changes |
Introduction |
| ◆ |
Launch file menu |
Introduction |
| ◆ |
Save files |
Introduction |
| ◆ |
Create an executable (.exe) file from a Python script |
Introduction |
| ◆ |
Set default programs by file extensions and by file types and programs on Windows |
Introduction |
| ◆ |
Open any files, e.g. text (.txt), image files, and so on. .txt file will be opened in Python program, e.g. IDLE shell |
code |
| ◆ |
Open an image to file from URL (webpage), then it can be saved in PC |
code, code. open with color changed |
| ◆ |
Choose a file with simple dialog |
Code. code. code |
| ◆ |
Copy text into clipboard and then you can paste it a webpage, text/txt, word or powerpoint file automatically |
code |
| ◆ |
Save the image in clipboard to an image file |
Introduction |
| ◆ |
Save the text in clipboard to a txt file |
Introduction |
| ◆ |
Save contents (download pdf files) in the webpages obtained by Google search into a text file |
Introduction |
| ◆ |
datatable.Frame.to_csv(): Write the contents of the Frame into a CSV file. If no path is given, then the Frame will be serialized into a string, and that string will be returned. |
|
| ◆ |
DataFrame.from_csv(): from_csv(path, header=0, sep=', ', index_col=0, parse_dates=True, encoding=None, tupleize_cols=False, infer_datetime_format=False): Read CSV file. It is preferable to use the more powerful pandas.read_csv() for most general purposes, but from_csv makes for an easy roundtrip to and from a file, especially with a DataFrame of time series data. |
|
| ◆ |
class watchdog.events.FileSystemEvent(src_path): Immutable type that represents a file system event that is triggered when a change occurs on the monitored file system.
event_type = None ::
The type of the event as a string.
is_directory = False ::
True if event was emitted for a directory; False otherwise.
src_path ::
Source path of the file system object that triggered this event. |
|
| ◆ |
g.fileopenbox |
Code |
| ◆ |
filepath_or_buffer: Either a string path to a file, URL (including http, ftp, and S3 locations), or any
object with a read method (such as an open file or StringIO). |
|
| ◆ |
class watchdog.events.FileSystemMovedEvent(src_path, dest_path): watchdog.events.FileSystemEvent :: File system event representing any kind of file system movement. dest_path ::
The destination path of the move event. |
|
| ◆ |
Fabric: Is a command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. With it, you can execute local or remote shell commands, upload/download files, and even prompt running user for input, or abort execution. |
|
| ◆ |
FileSystemEventHandler. (code). |
|
| ◆ |
class watchdog.events.FileMovedEvent(src_path, dest_path): Bases: watchdog.events.FileSystemMovedEvent :: File system event representing file movement on the file system. |
|
| ◆ |
class watchdog.events.FileModifiedEvent(src_path): Bases: watchdog.events.FileSystemEvent :: File system event representing file modification on the file system. |
|
| ◆ |
class watchdog.events.FileCreatedEvent(src_path): Bases: watchdog.events.FileSystemEvent :: File system event representing file creation on the file system. |
|
| ◆ |
class watchdog.events.FileDeletedEvent(src_path): Bases: watchdog.events.FileSystemEvent :: File system event representing file deletion on the file system. |
|
| ◆ |
class watchdog.events.FileSystemEventHandler: Base file system event handler that you can override methods from. |
|
| ◆ |
watchdog.events.FileSystemEventHandler: Matches given patterns with file paths associated with occurring events. |
|
| ◆ |
watchdog.events.FileSystemEventHandler: Matches given regexes with file paths associated with occurring events. |
|
| ◆ |
files_created: List of files that were created. |
|
| ◆ |
files_deleted: List of files that were deleted. |
|
| ◆ |
files_modified: List of files that were modified. |
|
| ◆ |
import fileinput |
code |
| ◆ |
|
|
| ◆ |
Automatically run a file in an application |
Introduction |
| ◆ |
PermissionError (E.g. file cannot be written when it is open/locked) |
Introduction |
| ◆ |
FileNotFoundError |
Introduction |
| ◆ |
File names |
|
| ✔ |
Get directory/path/file name partially |
Introduction |
| ✔ |
Print and set file path as a variable (e.g. convert all characters in the pathname to lowercase) |
Introduction |
| ✔ |
Find/search birthyear by name . code. Check file existence with partial filename |
Introduction |
| ✔ |
Find files with a specific file extension/type or with file names ending with specific characters |
Introduction |
| ✔ |
Find the file names of the images in a pptx, (and then save/extract the image as a file) |
Introduction |
| ✔ |
split(): Split a string by dots, split a file name by dots, split a file name from its extension. code. (code). |
Introduction |
| ✔ |
from tkinter.filedialog import askopenfilename |
code. code |
| ✔ |
filename (format) |
code |
| ✔ |
Get the name of the current/most front window |
Introduction |
| ✔ |
FindWindow(): FindWindow(className, windowName ): Searches for the specified top-level window. Parameters:
className is a string, which is the window class name to find, else None; The
windowName is also a string, which is the window name (ie, title) to find, else None |
Introduction |
| |
|
|
| Truth (True) and False Table |
Introduction |
| Change date/month/year format |
Introduction |
| Check if a string can be converted to float |
Introduction |
| Find the same elements in columns in two separate dataframes and then merge them |
Introduction |
| Remove the substring after the first or last character "::" in a given string, or extract the substring between the first and last "::" |
Introduction |
| .find(sub[start, [end]]): find the index. code. "-1" is given if the letter is not found. |
Introduction |
| |
|
| FloatingPointError |
Introduction |
| ◆ |
find_element_by_id(): Use this when the id attribute of the element known, e.g.:
<html>
<body>
<form id="loginForm">
<input name="username" type="text" />
<input name="password" type="password" />
<input name="Submit" type="Submit" value="Login" />
</form>
</body>
</html>
Then, the form element can be:
MyLogin = driver.find_element_by_id('loginForm')
(code). |
Introduction |
| ◆ |
find_element_by_name(): Use this when the name attribute of the element is known, e.g.:
<html>
<body>
<form id="loginForm">
<input name="username" type="text" />
<input name="password" type="password" />
<input name="continue" type="submit" value="Login" />
<input name="continue" type="button" value="Clear" />
</form>
</body>
</html>
Then, the username & password elements can be:
username = driver.find_element_by_name('username')
password = driver.find_element_by_name('password')
continue = driver.find_element_by_name('continue')
(code). |
Introduction |
| ◆ |
find_element_by_xpath(): XPath is the language used for locating nodes in an XML document. One of the main reasons of using XPath is when you don’t have a suitable id or name attribute for the element.
<html>
<body>
<form id="loginForm">
<input name="username" type="text" />
<input name="password" type="password" />
<input name="continue" type="submit" value="Login" />
<input name="continue" type="button" value="Clear" />
</form>
</body>
</html>
The first form elements can like this:
login_form = driver.find_element_by_xpath("/html/body/form[1]")
login_form = driver.find_element_by_xpath("//form[1]")
login_form = driver.find_element_by_xpath("//form[@id='loginForm']")
The second element (username) can be like this:
username = driver.find_element_by_xpath("//form[input/@name='username']")
username = driver.find_element_by_xpath("//form[@id='loginForm']/input[1]")
username = driver.find_element_by_xpath("//input[@name='username']")
The third element (Clear Button) can be like this:
clear_button = driver.find_element_by_xpath("//input[@name='continue'][@type='button']")
clear_button = driver.find_element_by_xpath("//form[@id='loginForm']/input[4]")
(code). |
Introduction |
| ◆ |
find_element_by_tag_name()Use this, when you want to locate an element by tag name, e.g.:
<html>
<body>
<h1>Welcome</h1>
<p>Site content goes here.</p>
</body>
</html>
The heading (h1) element can be like this:
heading1 = driver.find_element_by_tag_name('h1')
(code). |
Introduction |
| ◆ |
find_element_by_class_name(): Use this, when you want to locate an element by class name, e.g.:
<html>
<body>
<p class="content">Site content goes here.</p>
</body>
</html>
The “p” element can be like this:
content = driver.find_element_by_class_name('content')
(code). |
Introduction |
| ◆ |
files_moved: Each event is a two-tuple the first item of which is the path that has been renamed to the second item in the tuple. |
|
| ◆ |
driver.findElement(By.linkText("NextPage")).click();
driver.findElement(By.id("")).sendKeys("")
driver.findElement(By.xpath("")).click()
driver.findElement(By.xpath("").sendKeys("")
driver.findElement(By.id(""))
chooseFile.sendKeys("")
driver.findElement(By.name("q")).sendKeys ("")
dom =document.getElementById("")
driver.FindElement(By.CssSelector(""))
driver.findElement(By.className(""))
driver.findElement(By.tagName("select")).Click()
driver.findElement(By.partialLinkText(" NextP")).click() |
Introduction |
| ◆ |
driver.find_element(By.linkText("NextPage")).click();
driver.find_element(By.id("")).sendKeys("")
driver.find_element(By.xpath("")).click()
driver.find_element(By.xpath("").sendKeys("")
driver.find_element(By.id(""))
chooseFile.sendKeys("")
driver.find_element(By.name("q")).sendKeys ("")
dom =document.getElementById("")
driver.find_element(By.CssSelector(""))
driver.find_element(By.className(""))
driver.find_element(By.tagName("select")).Click()
driver.find_element(By.partialLinkText(" NextP")).click() |
Introduction |
| Plot a figure with a colored arrow between text lines/steps |
Introduction |
| Estimate the file size in memory before saving to PC |
Introduction |
| Built-in functions in Python |
Introduction |
| filter() |
Introduction |
| Check if all/any values are true or false in a range of data |
Introduction |
| Optimizing failure analysis processes in semiconductor labs using machine learning |
Introduction |
| ML for failure analysis in the semiconductor industry |
Introduction |
| Convert a floating-point number (decimal) to exponential format |
Introduction |
| Apply a formatting function to all cells in a DataFrame |
Introduction |
| Font size of tick labels in plot |
Introduction |
| Font size of a (single/multiple) cell in table in PowerPoint |
Introduction |
| Only use the first 4 characters in the headers of the table for pptx/dataframe |
Introduction |
| Comparative overview of multivariate statistical methods (Correlation Analysis, Regression Analysis, Factor Analysis, Cluster Analysis, Principal Component Analysis (PCA), Canonical Correlation Analysis, Discriminant Analysis, Path Analysis, Structural Equation Modeling (SEM), Multivariate Analysis of Variance (MANOVA), Analysis of Covariance (ANCOVA) ): purposes, variables, and outputs |
Introduction |
| Fail rate generator in wafers |
Introduction |
| Overcoming automation challenges and forward-looking suggestions |
Introduction |
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| float_precision |
CSV: string, default None. Specifies which converter the C engine should use for floating-point values. The options are None for the ordinary converter, ‘high’ for the high-precision converter, and ‘round_trip’ for the round-trip converter. |
| .fillna() |
Replace empty cells with anything. (code) |
| from typing import List, Dict |
CSV: code. |
| |
|
| false_values |
CSV: list of strings to recognize as False |
| float_format |
CSV: Format string for floating point numbers |
| f1_score()/F1-score() |
f1_score: float or array of float, shape = [n_unique_labels]
F1 score of the positive class in binary classification or weighted average of the F1 scores of each class for the multiclass task. Introduction. |
| fit_transform() |
Introduction |
| .fit() |
Introduction. |
| |
|
| |
|
| |
|
find_element_by_link_text()
find_element_by_partial_link_text() |
Use those when the link text used within an anchor tag is known: the first element with the link text matching the provided value will be returned, e.g.:
<html>
<body>
<p>Are you sure you want to do this?</p>
<a href="continue.html">Continue</a>
<a href="cancel.html">Cancel</a>
</body>
</html>
The continue.html link can be like this:
continue_link = driver.find_element_by_link_text('Continue')
continue_link = driver.find_element_by_partial_link_text('Conti')
(code) (code). Introduction. |
| |
|
| |
|
| find_element_by_css_selector() |
Use this, when you want to locate an element using CSS selector syntax, e.g.:
<html>
<body>
<p class="content">Site content goes here.</p>
</body>
</html>
The “p” element can be like this:
content = driver.find_element_by_css_selector('p.content')
(code). Introduction. |
| F1 |
(Code) |
| F2 |
(Code) |
| F3 |
(Code) |
| F4 |
Introduction |
| F5 |
Introduction |
| F6 |
(Code) |
| F7 |
(Code) |
| F8 |
(Code) |
| F9 |
(Code) |
| F10 |
(Code) |
| F11 |
(Code) |
| F12 |
(Code) |
| from |
|
| from <library nmae> import <function number> |
This is used if only one part of the fuctions in the library is needed. |
| from ... import * |
Import everything from ... module. code. |
| for |
for loop. The for
construct is generally used for lists, tuples, strings, etc. E.g. repeating a Process with for, code, code. With for, you generally get a fixed number of loops, one for each item in a
range or one for each item in a list. With a while loop, the loop keeps going as long
as (while) some condition is true. copy method. for loop can be rewitten as a while loop with a counter. |
| for ... in ... |
Introduction. Print all iterms in a list in a seperate line: string list1. string list2. string list3. dictionary. remove items/keys/values in a dictionary. for row in csvreader. code. |
| for ... in rang() |
rang (a), rang (a, b), rang (a, b, c). code, code. code. repeating action. |
| for ... in rang() in csv |
Introduction |
| for(;;) |
Introduction |
| Loop through a list (e.g. for loop) |
Introduction |
| Loops (e.g. for loop) for 2D (two-dimensional) plot |
Introduction |
| textwrap.fill |
code. |
| |
|
| Frame() |
Introduction |
| iframe in webpage |
<Introduction> |
| fill=tk.X |
(code) |
| from functools import reduce |
Reduce the list sign to "|". Introduction |
| |
|
| format() |
Formats the specified value(s) and insert them inside the string's placeholder. code. |
| finally |
|
| .font |
(code) |
| __float__ |
|
| __floor__ |
|
| __floordiv__ |
|
| __format__ |
|
| '{:,}'.format |
>>> x = '{:,}'.format(188899660)
>>> print (x)
Output: 188,899,660 |
F-string/f'()/f"() |
In F-string (f"), all you need is a lowercase or uppercase f followed immediately by some text or expressions enclosed in quotation marks. Introduction. Code. |
| math.floor() |
The floor of a given number is the nearest integer smaller than or
equal to that number. For example the floor of 4.68 is 4 and that of 4 is also 4. |
| math.factorial() |
Factorial: The factorial of a number x is defined as the continued product of
the numbers from 1 to that value. code. |
| math.fabs() |
The absolute value of a number |
| sys.stderr.flush() |
(code) |
| __format__ |
|
| from_bytes |
|
| |
|
| |
|
Integer/fractions/round /decimal/digits/floating
/ceil/floor |
It does not have any fractional part. Introduction. int: Example code. |
| Floating Point |
It can store number with a fractional part |
| float() |
Returns a floating point number constructed from a number or string |
| datetime.__format__(format) |
Same as datetime.strftime() (code) |
| scipy.linalg.fiedler |
Create a symmetric Fiedler matrix. |
| scipy.linalg.fiedler_companion |
Create a Fiedler companion matrix. |
| ft.fft2d |
Code. |
| ft.fftshift |
Code. |
| skimage.measure.find_contours(array, level) |
Find iso-valued contours in a 2D array for a given level value. |
| fillna() |
(code) |
| bokeh.plotting.figure.circle() |
|
| figsize |
Size of figure to create as tuple |
| **fig_kw |
Additional keywords to subplots are used when creating the figure, such as plt.subplots(2, 2,
figsize=(8, 6)) |
| np.full_like |
Return a full array with the same shape and type as a given array. Code. |
| Flask |
A web framework, Flask is built with a small core and many extensions. |
|
|
| .forward() |
(code) |
| .fillcolor() |
“fillcolor”: color-string or color-tuple. (code) |
| .activate() |
Activate a window: with the active cursor in the window and the window is brought to the most front on the monitor. (code) |
| |
|
| FLAT, RAISED, SUNKEN, GROOVE and RIDGE in Tkinter button relief styles |
Introduction |
| foreground= |
(code) |
| |
|
| warnings.filterwarnings |
(code). |
| |
|
| FlexForm() |
(code). |
| |
|
| |
|
| driver.navigate().forward() |
Navigate forwards in browser history |
| pyautogui.FAILSAFE |
"pyautogui.FAILSAFE = True": moving the mouse cursor to the
upper-left corner of the screen will cause PyAutoGUI to raise the pyautogui
.FailSafeException exception. "pyautogui.FAILSAFE = False": disable this feature. |
| .format.line |
(code) |
| soup.find() and soup.find_all() |
Introduction |
| .fromtimestamp() |
(code) |
| os.path.normpath(): Normalize/format the path string into a proper string for the OS |
(code) |
| go.Figure |
(Code) |
| .filter2D() |
(Code) |
| |
|
