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Added docstrings to several undocumented functions.
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@ -55,6 +55,12 @@ That being said, most of the examples do work as expected. If you face any troub
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def generate_code_block(statements, output):
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"""
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Generates a code block that executes the given statements.
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:param statements: The list of statements to execute.
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:type statements: list(str)
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"""
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global sequence_num
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result = {
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"type": "code",
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@ -67,6 +73,9 @@ def generate_code_block(statements, output):
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def generate_markdown_block(lines):
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"""
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Generates a markdown block from a list of lines.
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"""
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global sequence_num
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result = {
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"type": "markdown",
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@ -85,6 +94,12 @@ def is_interactive_statement(line):
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def parse_example_parts(lines, title, current_line):
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"""
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Parse the given lines and return a dictionary with two keys:
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build_up, which contains all the text before an H4 (explanation) is encountered,
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and
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explanation, which contains all the text after build_up until --- or another H3 is encountered.
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"""
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parts = {
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"build_up": [],
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"explanation": []
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@ -191,6 +206,14 @@ def remove_from_beginning(tokens, line):
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def inspect_and_sanitize_code_lines(lines):
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"""
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Remove lines from the beginning of a code block that are not statements.
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:param lines: A list of strings, each representing a line in the code block.
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:returns is_print_present, sanitized_lines: A boolean indicating whether print was present in the original code and a list of strings representing
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sanitized lines. The latter may be an empty list if all input lines were removed as comments or whitespace (and thus did not contain any statements).
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This function does not remove blank lines at the end of `lines`.
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"""
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tokens_to_remove = STATEMENT_PREFIXES
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result = []
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is_print_present = False
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@ -203,6 +226,23 @@ def inspect_and_sanitize_code_lines(lines):
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def convert_to_cells(cell_contents, read_only):
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"""
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Converts a list of dictionaries containing markdown and code cells into a Jupyter notebook.
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:param cell_contents: A list of dictionaries, each
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dictionary representing either a markdown or code cell. Each dictionary should have the following keys: "type", which is either "markdown" or "code",
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and "value". The value for type = 'markdown' is the content as string, whereas the value for type = 'code' is another dictionary with two keys,
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statements and output. The statements key contains all lines in between ```py\n``` (including) until ```\n```, while output contains all lines after
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```.output py\n```.
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:type cell_contents: List[Dict]
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:param read_only (optional): If True then only print outputs are included in converted
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cells. Default False
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:type read_only (optional): bool
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:returns A Jupyter notebook containing all cells from input parameter `cell_contents`.
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Each converted cell has metadata attribute collapsed set to true if it's code-cell otherwise None if it's markdow-cell.
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"""
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cells = []
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for stuff in cell_contents:
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if stuff["type"] == "markdown":
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@ -269,6 +309,9 @@ def convert_to_cells(cell_contents, read_only):
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def convert_to_notebook(pre_examples_content, parsed_json, post_examples_content):
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"""
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Convert a JSON file containing the examples to a Jupyter Notebook.
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"""
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result = {
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"cells": [],
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"metadata": {},
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@ -13,6 +13,10 @@ file_path = join(dirname(dirname(realpath(__file__))), "content.md")
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def fetch_updated_doc():
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"""
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Fetch the latest version of the file at `url` and save it to `file_path`.
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If anything goes wrong, do nothing.
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"""
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try:
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print("Fetching the latest version...")
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urlretrieve(url, file_path)
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