Python Expression

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Overview

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The Special _ Variable

1. First Step Input: In the first step of a task, _ contains the execution input:

# If task is executed with input `{"topic": "AI"}`
- evaluate:
    topic: $ _.topic  # Accesses the input "AI"

2. Previous Step Output: In any subsequent step, _ contains the output from the previous step:

- evaluate:
    results: $ _.split('\n')  # Splits previous step's output into lines

3. Iterator Value: In foreach and map steps, _ represents the current item being iterated.

# If the task is executed with input `{"questions": ["What is AI?", "What is Julep?"]}`
- foreach:
    in: $ _.questions
    do:
      - wait_for_input:
          info:
            "message": $ _  # _ is each question

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The Special $ Variable

- evaluate:
    topic: $ _.topic  # Accesses the input "AI"

- prompt:
    - role: user
      content: |-
        $ f'''
        Please answer the following question:
        {_.question} 
        '''

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Where Python Expressions Are Used

• evaluate steps
• Tool arguments
• if conditions
• foreach and map iterations

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Available Functions and Libraries

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Basic Python Builtins

• abs, all, any, bool, dict, enumerate
• float, int, len, list, map, max, min
• round, set, str, sum, tuple, zip, reduce

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Safe Versions of Functions

• range: def safe_range(*args) Safely creates a range object with size limits (max 1,000,000 elements).
• load_json: def safe_json_loads(s: str) -> Any (Deprecated in favor of json.loads) Safely parses a JSON string with size limits.
• load_yaml: def safe_yaml_load(s: str) -> Any (Deprecated in favor of yaml.safe_load) Safely parses a YAML string with size limits.
• dump_json: def dump_json(obj: Any, *, **kwargs) -> str (Deprecated in favor of json.dumps) Safely serializes an object to a JSON string.
• dump_yaml: def dump_yaml(obj: Any, **kwargs) -> str (Deprecated in favor of yaml.dump) Safely serializes an object to a YAML string.
• extract_json: def safe_extract_json(string: str) -> Any Safely extracts and parses JSON from text.

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Regex and NLP Functions

• search_regex: def search_regex(pattern: str, string: str) -> Optional[re2.Match] Searches for a regex pattern in a string.
• match_regex: def match_regex(pattern: str, string: str) -> bool Checks if a regex pattern matches a string.
• chunk_doc: def chunk_doc(string: str) -> list[str] Chunks a string into sentences.
• nlp pipelines.

- evaluate:
    # Parse JSON string with size limit of 1MB
    data: $ json.loads(_.json_string)
    
    # Parse YAML string with size limit of 1MB
    config: $ yaml.safe_load(_.yaml_string)
    
    # Extract JSON from text that might contain markdown code blocks
    extracted_content: $ extract_json('Here is some JSON: ```json\n{"key": "value"}\n```')

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CSV Functions

• reader: def reader(data: str, dialect="excel", delimiter: str = ",", quotechar: str | None = '"', escapechar: str | None = None, doublequote: bool = True, skipinitialspace: bool = False, lineterminator: str = "\r\n", quoting=0, strict: bool = False) -> csv._reader Creates a CSV reader.
• writer: def writer(data: str, dialect="excel", delimiter: str = ",", quotechar: str | None = '"', escapechar: str | None = None, doublequote: bool = True, skipinitialspace: bool = False, lineterminator: str = "\r\n", quoting=0, strict: bool = False) -> csv._writer Creates a CSV writer.
• DictReader: class DictReader(data: str, fieldnames=None, restkey=None, restval=None, dialect="excel", *args, **kwds) Create an object that operates like a regular reader but maps the information in each row to a dict.
• DictWriter: class DictWriter(data: str, fieldnames, restval="", extrasaction="raise", dialect="excel", *args, **kwds) Create an object which operates like a regular writer but maps dictionaries onto output rows.
• register_dialect: def register_dialect(name: str, dialect: type[Dialect] = ..., *, delimiter: str = ",", quotechar: str | None = '"', escapechar: str | None = None, doublequote: bool = True, skipinitialspace: bool = False, lineterminator: str = "\r\n", quoting: _QuotingType = 0, strict: bool = False) -> csv._reader Associate dialect with name.
• unregister_dialect: def unregister_dialect(name: str) -> None Delete the dialect associated with name from the dialect registry.
• get_dialect: def get_dialect(name: str) -> Dialect Return the dialect associated with name.
• list_dialects: def list_dialects() -> list[str] Return the names of all registered dialects.
• field_size_limit: def field_size_limit(new_limit: int = ...) -> int Returns the current maximum field size allowed by the parser.
• Dialect: class Dialect() The Dialect class is a container class whose attributes contain information for how to handle doublequotes, whitespace, delimiters, etc.
• excel: class excel() The excel class defines the usual properties of an Excel-generated CSV file.
• excel_tab: class excel_tab() The excel_tab class defines the usual properties of an Excel-generated TAB-delimited file.
• unix_dialect: class unix_dialect() The unix_dialect class defines the usual properties of a CSV file generated on UNIX systems, i.e. using ‘\n’ as line terminator and quoting all fields.
• Sniffer: class Sniffer The Sniffer class is used to deduce the format of a CSV file.
• QUOTE_ALL - Instructs writer objects to quote all fields.
• QUOTE_MINIMAL - Instructs writer objects to only quote those fields which contain special characters such as delimiter, quotechar or any of the characters in lineterminator.
• QUOTE_NONNUMERIC - Instructs writer objects to quote all non-numeric fields. Instructs reader objects to convert all non-quoted fields to type float.
• QUOTE_NONE - Instructs writer objects to never quote fields.
• QUOTE_NOTNULL - Instructs writer objects to quote all fields which are not None.
• QUOTE_STRINGS - Instructs writer objects to always place quotes around fields which are strings.
• Error: class Error() Raised by any of the functions when an error is detected.

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Example Usage

name: Data Processing Task

main:
  # Using _ as input
  - evaluate:
      csv_data: $ [row for row in csv.reader("a,b,c\n1,2,3")]

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Standard Library Modules

• re: Regular expressions (using re2)
• json: JSON operations
• yaml: YAML operations
• string: String constants and operations
• datetime: Date and time operations
• math: Mathematical functions
• statistics: Statistical operations
• base64: Base64 encoding/decoding
• urllib.parse: URL parsing operations
• random: Random number generation
• time: Time operations
• csv: CSV operations

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Example Usage

name: Data Processing Task

main:
  # Using _ as input
  - evaluate:
      topics: $ _.topics  # Access input topics

  # Using _ as previous output
  - evaluate:
      filtered_topics: $ [t for t in _.topics if len(t) > 3]

  # Using _ in foreach
  - foreach:
      in: $ _.filtered_topics
      do:
        - tool: web_search
          arguments:
            query: $ 'Latest news about ' + _ # _ is each topic

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Custom Implementations

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Humanization (Alpha)

• Back-translation.
• Rewriting using non-public LLMs.
• Stylistic modifications such as homoglyphs and em dashes.

• text: The text to be humanized.
• threshold: The threshold for the humanization (0-100).
• src_lang: The source language of the original text.
• target_lang: The target language used in the back-translation technique.
• use_homoglyphs: Whether to use homoglyphs, a technique that replaces certain characters with similar looking characters to trick AI detection classifiers.
• use_em_dashes: Whether to use em dashes, i.e. adding dashes between longer words to break the tokens.
• grammar_check: Whether to run another prompt after back-translation to check for correct grammar.
• max_tries: The maximum number of tries to humanize the text.

- evaluate:
    humanized_text: $ humanize_text_alpha(_.text, threshold=30, target_lang="german")

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Markdown to HTML

• markdown_text: The markdown text to be converted to HTML.

- evaluate:
    html_text: $ markdown_to_html(_.markdown_text)

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HTML to Markdown

• html_text: The HTML text to be converted to markdown.

- evaluate:
    markdown_text: $ html_to_markdown(_.html_text)

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Security

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Support

• Join our Discord community
• Check the GitHub repository
• Contact support at hey@julep.ai