ops

Miscellaneous operations.

General usage

confirmed([prompt, confirmation_required, resp])	Prompt user for confirmation to proceed.
get_obj_attr(obj[, col_names, as_dataframe])	Retrieve main attributes of an object.
eval_dtype(str_val)	Convert a string representation to its intrinsic data type.
hash_password(password[, salt, salt_size, ...])	Hash a password using hashlib.pbkdf2_hmac (PBKDF2 algorithm with HMAC-SHA256).
verify_password(password, salt, key[, ...])	Verify if a password matches the provided salt and key.
func_running_time(func)	Decorator to measure the execution time of a function or class method.

Basic computation / conversion

gps_time_to_utc(gps_time)	Convert GPS time to UTC time.
parse_size(size[, binary, precision])	Parse size into human-readable format or vice versa.
get_number_of_chunks(file_or_obj[, ...])	Get the total number of chunks of a data file, given a minimum chunk size limit.
get_extreme_outlier_bounds(num_dat[, k])	Get the upper and lower bounds for extreme outliers using the interquartile range method.
interquartile_range(num_dat)	Calculate the interquartile range (IQR) of numerical data.
find_closest_date(date, lookup_dates[, ...])	Find the closest date to a given date from a list of dates.

Basic data manipulation

Iterable

loop_in_pairs(iterable)	Generate pairs of consecutive elements from the given iterable.
split_list_by_size(lst, sub_len)	Split a list into evenly sized sub-lists.
split_list(lst, num_of_sub)	Split a list into a specified number of equally-sized sub-lists.
split_iterable(iterable, chunk_size)	Split an iterable into evenly sized chunks.
update_dict(dictionary, updates[, inplace])	Update a (nested) dictionary with another dictionary.
update_dict_keys(dictionary[, replacements])	Update keys in a (nested) dictionary based on a given replacements dictionary.
get_dict_values(key, dictionary)	Retrieve all values in a (nested) dictionary for a given key.
remove_dict_keys(dictionary, *keys)	Remove multiple keys from a dictionary.
compare_dicts(dict1, dict2)	Compare the differences between two dictionaries.
merge_dicts(*dicts)	Merge multiple dictionaries into a single dictionary.

Tabular data

detect_nan_for_str_column(data_frame[, ...])	Detect if a column with string type contains NaN values for a given dataframe.
create_rotation_matrix(theta)	Create a 2D rotation matrix for counterclockwise rotation.
dict_to_dataframe(input_dict[, k, v])	Convert a dictionary to a dataframe.
parse_csr_matrix(path_to_csr[, verbose])	Load in a compressed sparse row (CSR) or compressed row storage (CRS).
swap_cols(array, c1, c2[, as_list])	Swap positions of two columns in an array.
swap_rows(array, r1, r2[, as_list])	Swap positions of two rows in an array.
np_shift(array, step[, fill_value])	Shift an array by a desired number of rows.
cmap_discretisation(cmap, n_colours)	Create a discrete colour ramp.
colour_bar_index(cmap, n_colours[, labels])	Create a colour bar with correctly aligned labels.

Graph plotting

cmap_discretisation(cmap, n_colours)	Create a discrete colour ramp.
colour_bar_index(cmap, n_colours[, labels])	Create a colour bar with correctly aligned labels.

Web data manipulation

is_network_connected()	Check whether the current machine is connected to the Internet.
is_url(url[, partially])	Check if url is a valid URL.
is_url_connectable(url)	Check if the current machine can connect to the given URL.
is_downloadable(url[, request_field])	Check if a URL leads to a webpage where downloadable content is available.
init_requests_session(url[, max_retries, ...])	Instantiate a requests session with configurable retry behaviour.
load_user_agent_strings([shuffled, ...])	Load user-agent strings for popular web browsers.
get_user_agent_string([fancy])	Get a random user-agent string for a specified browser.
fake_requests_headers([randomized])	Generate fake HTTP headers for requests.get.
download_file_from_url(url, path_to_file[, ...])	Download a file from a valid URL.

GitHubFileDownloader(repo_url[, ...])

Download files from GitHub repositories.