Metadata-Version: 2.1
Name: jtools
Version: 1.1.5
Summary: A Python module that aids filtering, formatting, and transforming JSON-like objects
Home-page: https://github.com/BlendingJake/JTools-Py
Author: Jacob Morris
Author-email: blendingjake@gmail.com
License: UNKNOWN
Description: # JTools
        
        >JTools is a robust library for interacting with JSON-like objects:
        >providing the ability to quickly query, format, and filter JSON-like data.
        >
        >JTools is available in Python and JavaScript
        >
        >There are three main components:
        
        * `Query`: Extract and transform the values of nested fields.
          * `Query("data.timestamp.$parse_timestamp.$attr('year')").many(items)`
        * `Filter`: Combine the querying capabilities of `Query` with the ability
         to define filtering conditions to find just the elements you want.
          * `Filter(Key("data.timestamp.$parse_timestamp.$attr('year')").gt(2015)).many(data)`
        * `Formatter`: Take multiple queries and format them into a string
          * `Formatter("Item @data.id was released in @data.timestamp.$parse_timestamp.$call('year')").single(data[0])`
        
        JTools exists in two different langauges with almost identical names and capabilities to allow you to move between the packages seamlessly. 
        
        ## Python - [jtools](https://pypi.org/project/jtools/)
        
        ## JavaScript - [@blending_jake/jtools](https://www.npmjs.com/package/@blending_jake/jtools)
        >Written in TypeScript and distributed as an ES6 style module with type
        declaration files. 
        
        ### Differences
        
         * In JTools-Py, the `==` and `===` filter operators will behave the same, as well as `!=` and `!==`. 
         * JTools-Py uses the `datetime` package for time related queries, while JavaScript uses `moment`
         * JTools-Py replicates JavaScript's lack of differentiation between `item[0]` and `item["0"]` by default. 
         However, this can be changed in the Python version by setting `Query(..., convert_ints=False)`. 
         If that argument is set to `False` in Python, then `item.0` would work on `{"item": {"0": ...}}`, 
         but not on `{"item": {0: ...}}`. The JavaScript version essentially always has `convert_ints=True`.
        
        ## Recent Changes
         * `1.1.5`
           * Unify `README` between Python and JavaScript versions
           * Expand documentation
        
         * `1.1.4`
           * Added `$value_map`, which allows the values on an map/dict/object to be modified with a special, either in-place
           or on a duplicate
           * Exposed `context` so additional fields can manually be put into the current query space. This was already 
           being used by `$store_as`. `context` can be passed to any `.single()` or `.many()` call.
           * Additionally, `Filter.many()` is now placing `INDEX` into the query space to allow
           items to be filtered by their 0-based index
           * Exposed many of the internal TypeScript types
          
        ## Glossary
         * [`Installation`](#install)
         * [`JQL`](#jql)
         * [`Query`](#query)
           * [`Context`](#context)
           * [`Specials`](#specials)
         * [`Filter`](#filter)
           * [`Key`](#key)
           * [`Condition`](#condition)
         * [`Formatter`](#formatter)
         * [`Performance`](#performance)
         * [`Changelog`](#changelog)
           
        ## <a name="install">Installation</a>
        
        ### Python
        `pip install jtools`
        ```python
        # import
        from jtools import Query, Filter, Key, Condition, Formatter
        ```
        
        ### JavaScript
        `npm i @blending_jake/jtools`
        ```javascript
        // import
        import { Query, Filter, Key, Condition, Formatter } from "@blending_jake/jtools";
        ```
        
        ## <a name="jql">`JQL`</a>
        >`JQL` or the `JSON Query Language` is a custom built query language for `JTools` which supports powerful features
        >like accessing nested fields, transforming values, and even using nested queries as arguments. 
        >The basic format of the language is: 
        ```
        (<field> | $<special>) (. (<field> | $<special>))*
        EX: 'data', 'data.timestamp', 'data.$split', '$split.0'
        ```
        #### field
        A field is just a value that can be used as an index, like a string or integer key for a map/dict or an integer for an array. JavaScript has very loose type-checking between strings
        and integers, so either can essentially work in place of the other when indexing.
        
        Fields can only contain the following characters: `[-a-zA-Z0-9_]`. However, fields with prohibited characters can still
        be indexed by using the `$index` special, so to index `range[0]` use `$index("range[0]")`.
        
        #### $special
        A special is a function that is applied to the value that has been queried so far. There is a complete list of specials
        [here](#specials). These specials can be passed arguments, which is one of the most powerful features
        of `JQL`. The syntax is similar to most programming languages: `$<special>(<value>(, <value>)*)`. Just to note, `$<special>()`
        is valid, as is `$<special>`. Many of the specials don't require any arguments, or have default values, allowing
        the parenthesis to be left off.
        
        ##### value
        A `<value>` can be:
        ```
        [] or [<value>(, <value>)*] - List
        {} or {<value>(, <value>)*} - Set
        {:} or {<key>: <value>(, <key>: <value>)*} - Map/Dict/Object (see below for <key> spec)
        Integer
        Float
        String w/ '' or ""
        true
        false
        null
        @<query> - Yep! Nested queries!
        
        <key>:
            @<query>    
            Integer
            Float
            String
            true
            false
            null
        ``` 
        As shown above, values and queries can be nested, so `[[1, 2], ["bob"], {"Ann", 'Ralph'}, {'key': 4, 23: 5}]`
        is valid. Additionally, the support for nesting queries is extremely powerful and allows for queries like:
        `item.tag.$lookup(@table.colors)`, which, for `{"item": {"tag": "product"}, "table": {"colors": {"product": "red"}}}`
        results in `"red"`
        
        ## <a name="query">Query</a>
        >`Query` takes the power of `JQL` and puts it into practice querying and transforming values
        >in JSON-like data. 
        
        ### `Query(query, fallback=null, [convert_ints=true (if Python)])`
        * `query`: `str | List[str]` The field or fields to query
        * `fallback`: The value that will result if a non-existent field is queried
        * `convert_ints`: Whether or not to convert any digit-only fields to integers
        
        #### `.single(item, context={})`
        * `item`: The item to query
        * `context`: See [`Context`](#context) for more details
        
        >Take a single item and query it using the query(ies) provided
        >
        >`Query(field).single(...) -> result`
        >
        >`Query([field, field, ...]).single(...) -> [result, result, ...]`
        
        #### `.many(items, context={})`
        * `items`: The items to query
        * `context`: See [`Context`](#context) for more details
        
        >Take a list of items, and query each item using the query(ies) provided
        >
        >`Query(field).many(...) -> [result, result, ...]`
        >
        >`Query([field, field, ...]).many(...) -> [[result, result, ...], [result, result, ...], ...]`
        
        ### Notes
         * Fields can be indexed after specials, so `$split.0` is completely valid
         
         * You don't have to use `()` at the end of a special if there aren't any 
         arguments, or the default arguments are acceptable.
         
         * More specials can be added by using the class method `.register_special()` 
         like so: `Query.register_special(<name>, <func>)`. The function should be formatted as such: 
          ```python
         # Python
        lambda value, *args, context: ...
         ```
         ```javascript
        // JavaScript
        (value, context, ...args) => { ... }
         ```
         Where `value` is the current query value, and `context` is the current context.
        
        #### <a name="context">Context</a>
        >Context is a way of putting temporary variables into the query search space.
        
        ##### How do I add something to `context`?
         1. Manually introduce values through `.single(..., context)` or `.many(..., context)`.
         2. Use the `$store_as()` special to place a value in the current context for later use
        
        ##### How do I access something in `context`?
         1. Any top-level field name is first looked for on the current item, then in `context`. Note, top-level means
         it is the main query in a `Query` string, or it follows an `@`, either as an argument or in a `Formatter` string.
         2. It is important to note that fields on the current item will shadow fields in the context, so make sure to use unique field names.
        
        ##### Ok, but give me an example.
        ```python
        # Python
        context = {
          "NOW": time.time()
        }
        
        Query("NOW.$subtract(@meta.timestamp).$divide(86400).$round.$suffix(' Days Ago')").single({ ... }, context)
        ```
        ```javascript
        // JavaScript
        const context = {
          NOW: Date.now() / 1000
        }
        
        new Query("NOW.$subtract(@meta.timestamp).$divide(86400).$round.$suffix(' Days Ago')").single({ ... }, context)
        ```
         
        #### <a name="specials">Specials</a>
        General
          * `$length -> int`
          * `$lookup(map: dict, fallback=null) -> any`: Lookup the current value in the provided map/dict 
          * `$inject(value: any) -> any`: Inject a value into the query
          * `$print -> any`: Print the current query value before continuing to pass that value along
          * `$store_as(name: string) -> any`: Store the current query value in the current context for later use in the query. This does not 
           change the underlying data being queried.
          * `$group_by(key="", count=false) -> Dict[any: any[] | int]`: Take an incoming list and group the values 
          by the specified key. Any valid JQL query can be used for the key, so `""` means the value itself. 
          The result by default will be keys to a list of values. However, if `count=true`, then the result will be keys 
          to the number of elements in that group.
          
        Maps/Objects
         * `$keys -> List[any]`
          * `$values -> List[any]`
          * `$items -> List[[any, any]]`
          * `$wildcard(next, just_value=true) -> List[any]`: On a given map or list, go through all values and see if `next` is
          a defined field. If it is, then return just the value of `next` on that item, if `just_value=true`, or the entire 
          item otherwise. This special allows a nested field to be extracted across multiple items where it it present. 
          For example: 
        ```python
        # Python
        data = {
          "a": {"tag": "run"},
          "b": {"tag": "to-do", "other": "task"},
          "meta": None
        }
        Query('$wildcard("tag")').single(data)  # => ["run", "to-do"]
        Query('$wildcard("tag", false)').single(data) # => [{"tag": "run"}, {"tag": "to-do", "other": "task"}]
        ```
        ```javascript
        // JavaScript
        let data = {
          "a": {"tag": "run"},
          "b": {"tag": "to-do", "other": "task"},
          "meta": null
        }
        new Query('$wildcard("tag")').single(data)  // => ["run", "to-do"]
        new Query('$wildcard("tag", false)').single(data) // => [{"tag": "run"}, {"tag": "to-do", "other": "task"}]
        ```
         * `$value_map(special, duplicate=true, ...args): Dict[any: any]`: Go through the values on the current item in the query, applying a special
         to each one in-place. If `duplicate=true`, then the original value will not be modified. Similar to:
         ```python
        # Python
        for key in value:
            value[key] = SPECIALS[special](value[key], *args)
         ```
         ```javascript
         // JavaScript
        Object.keys(value).forEach(key => {
            value[key] = SPECIALS[special](value[key], ...args);
        });
         ```
          
        Type Conversions
          * `$set -> set`
          * `$float -> float`
          * `$string -> str`
          * `$dict -> Dict[any: any]`: Take an incoming list of `(key, value)` pairs and make a map/dict/object out of them.
          * `$int -> int`
          * `$not -> bool`: Returns `not value` or `!value`
          * `$fallback(fallback) -> value or fallback`: If the value is `null`, then it will be replaced with `fallback`.
          * `$ternary(if_true, if_false, strict=false) -> any`: Return `if_true` if the value is `truish`, otherwise,
          return `if_false`. Pass `true` for `strict` if the value must be `true` and not just `truish`.
          
        Datetime 
          * `$parse_timestamp -> datetime or moment`: Take a Unix timestamp in seconds and return a corresponding datetime/moment object
          * `$strptime(fmt=null) -> datetime or moment`: Parse a datetime string and return a corresponding datetime/moment object.
          If `fmt=None`, then standard formats will be tried. Refer to [datetime](#https://docs.python.org/3/library/datetime.html#strftime-strptime-behavior) or 
          [moment](#https://momentjs.com/docs/#/parsing/string-format/) for formatting instructions
          * `$timestamp -> int`: Dump a datetime/moment object to a UTC timestamp as the number of seconds since the Unix Epoch
          * `$strftime(fmt="%Y-%m-%dT%H:%M:%SZ" or "YYYY-MM-DD[T]HH:mm:ss[Z]") -> string`: Format a datetime/moment object as a string using `fmt`. Refer to [datetime](#https://docs.python.org/3/library/datetime.html#strftime-strptime-behavior) or 
          [moment](#https://momentjs.com/docs/#/parsing/string-format/) for formatting instructions
          
        Math / Numbers
          * `$add(num) -> number`
          * `$subtract(num) -> number`
          * `$multiply(num) -> number`
          * `$divide(num) -> number`
          * `$pow(num) -> number`
          * `$abs(num) -> number`
          * `$distance(other) -> float`: Euler distance in N-dimensions
          * `$math(attr, ...args) -> any`: Returns `math[attr](value, ...args)`, which can be used for
          operations like `floor`, `cos`, `sin`, `min`, etc.
          * `$round(n=2) -> number`
          
        Strings
          * `$prefix(prefix) -> string`: Prefix the value with the specified string
          * `$suffix(suffix) -> string`: Concatenate a string to the end of the value
          * `$wrap(prefix, suffix) -> string`: Wrap a string with a prefix and suffix. Combines features of above two specials.
          * `$strip -> string`: Strip leading and trailing whitespace
          * `$replace(old, new) -> string`: Replace all occurrences of a string 
          * `$trim(length=50, suffix="...") -> string`: Trim the length of a string
          * `$split(on=" ") -> List[string]`: Split a string
          
        Lists
          * `$sum -> number`: Return the sum of the items in the value
          * `$join(sep=", ") -> string`: Join a list using the specified separator
          * `$join_arg(arg: any[], sep=", ")`: Similar to `$join` except this operates on an argument instead of the query value.
          Essentially a shortened form of `$inject(arg).$join(sep)`.
          * `$index(index) -> any`: Index a list. Negative indices are allowed.
          * `$range(start, end=null) -> List[any]`: Get a sublist. Defaults to `value.slice(start)`, 
          but an end value can be specified. Negative indices are allowed. 
          * `$remove_nulls -> List[any]`: Remove any values that are `None` if Python, or `null` and `undefined` if JavaScript
          * `$sort(key="", reverse=false) -> List[any]`: Sort an incoming list of values by a given key which can be any valid JQL query.
          By default, `key=""` means the top-level value will be sorted on.
          * `$map(special, ...args) -> List[any]`: Apply `special` to every element in the 
          value. Arguments can be passed through to the special being used.
          
         Attributes
          * `$call(func, ...args) -> any`: Call a function that is on the current value, implemented as `getattr(value, func)(*args)` and `value[func](...args)`
          * `$attr(attr) -> any`: Access an attribute of the given object, implemented as `getattr(value, attr)` and `value[attr]`
        
        
        ## <a name="filter">Filter</a>
        >`Filter` takes the power of `JQL` and combines it with 
        >filtering conditions to allow lists of items to be filtered down to just those of 
        >interest. The filters can be manually built, or the `Key` and `Condition` classes can 
        >be used to simplify your code.
        
        ### `new Filter(filters, [convert_ints=true (if Python)], empty_filters_response=true, missing_field_response=false)`
         * `filters`: `Condition | List[dict]` The filters to apply to any data. If `List[dict]`, then the
         filters should be formatted as shown below.
        ```
        [
            {"field": <field>, "operator": <op>, "value": <value>},
        
            OR
        
            {"or": <nested outer structure>},
            
            OR
        
            {"not": <nested outer structure>},
        
            ...
        ]
        <field>: any valid `JQL` query
        <op>: See list below
        <value>: Anything that makes sense for the operator
        ``` 
         * `convert_ints`: `bool` Corresponds with the argument with the same name in `Query`. Determines
         whether digit only fields are treated as integers or strings. Defaults to `true`.
         * `empty_filters_response`: `bool` Determines what gets returned when no filters are supplied.
         * `missing_field_response`: `bool` Determines the result of a filter where the field could not be found.
        
        #### `.single(item, context={})`
         * `context`: See [`Context`](#context) for more details
        >Take a single item and determine whether it satisfies the filters or not
        >
        >`Filter(filters).single(...) -> boolean`
        
        #### `.many(items, context={})`
         * `context`: See [`Context`](#context) for more details
        >Take a list of items, and returns only those which satisfy the filters. Note, `Filter.many()` introduces `INDEX` into
        the query namespace. Allowing items to be filtered by their 0-based index.
        >
        >`Filter(filters).many(...) -> [result, result, ...]`
        
        ### Notes
        ```
        {"or": [ 
            [ {filter1}, {filter2} ], 
            {filter3} 
        ]} === (filter1 AND filter2) OR filter3
        ``` 
        >Nesting in an `or` will cause those filters
        >to be `AND'd` and then everything in the toplevel of that `or` will be `OR'd`.
        
        Operators:
         * `>`
         * `<`
         * `>=`
         * `<=`
         * `==`
         * `!=`
         * `===`
         * `!==`
         * `in`: `<field> in <value>`
         * `!in`
         * `contains`: `<value> in <field>`
         * `!contains`
         * `interval`: `<field> in interval [value[0], value[1]]` (closed/inclusive interval)
         * `!interval`: `<field> not in interval [value[0], value[1]]` 
         * `startswith`
         * `endswith`
         * `present`
         * `!present`
        
        
        #### <a name="key">Key</a>
        >Intended to simplify having to write `{"field": <field>, "operator": <operator>, "value": value}` 
        >a lot. The basic usage is: `Key(<field>).<op>(<value>)`, or for the first six 
        >operators, the actual Python operators can be used, so `Key(<field>) <op> <value>`.
        >For example: `Key("meta.id").eq(12)` is the same as `Key("meta.id") == 12`,
        >which is the same as `{"field": "meta.id", "operator": "==", "value": 12}`.
        
        >The table below describes all of the functions which map to the underlying conditions, but, in
        >addition, there is the `.operator(op: str)` function which can be use to build a filter.
        >For example: `Key(<field>).operator(<op>).value(<value>)` is the same as 
        >`{"field": <field>, "operator": <op>, "value": <value>}`
        
        Operators: 
        
        | underlying operator | `Key` function | `Python` operator |
        | ------------------- | -------- | -------- |
        | `>` | `gt` | `>` | 
        | `<` | `lt` | `<` | 
        | `<=` | `lte` | `<=` | 
        | `>=` | `gte` | `>=` | 
        | `==` | `eq` | `==` | 
        | `!=` | `ne` | `!=` | 
        | `===` | `seq` | N/A |
        | `!==` | `sne` | N/A
        | `in` | `in_` | N/A | 
        | `!in` | `nin` | N/A | 
        | `contains` | `contains` | N/A | 
        | `!contains` | `not_contains` | N/A | 
        | `interval` | `interval` | N/A |
        | `!interval` | `not_interval` | N/A |
        | `startswith` | `startswith` | N/A | 
        | `endswith` | `endswith` | N/A | 
        | `present` | `present` | N/A | 
        | `!present` | `not_present` | N/A | 
        
        #### <a name="condition">Condition</a>
        >Intended to be used in combination with `Key` to make creating filters
        >easier than manually creating the `JSON`. There are three conditions supported:
        >`and`, `or`, and `not`. They can be manually accessed via `and_(...conditions)`, `or_(...conditions)`, and `not_()`.
        >
        >The conditions can also be accessed through the overloaded operators `&`, `|`, and `~`, respectively, if in Python. **Caution: `&` and `|` bind tighter than the comparisons operators and `~` binds the tightest**
        >
        >`Key("first_name") == "John" | Key("first_name") == "Bill"` is actually
        `(Key("first_name") == ("John" | Key("first_name"))) == "Bill"`, not
        `(Key("first_name") == "John") | (Key("first_name") == "Bill")`
        
        Examples
        ```python
        # Python
        Key("state").eq("Texas") | Key("city").eq("New York")
        
        (Key("gender") == "male") & (Key("age") >= 18) & (Key("selective_service") == False)
        
        Key('creation_time.$parse_timestamp.$attr("year")').lt(2005).or_(
            Key('creation_time.$parse_timestamp.$attr("year")').gt(2015)
        ).and_(
            Key("product_id") == 15
        )
        # (year < 2005 OR year > 2015) AND product_id == 15
        ```
        
        ```javascript
        // JavaScript
        Key('creation_time.$parse_timestamp.$call("year")').lt(2005).or_(
            Key('creation_time.$parse_timestamp.$call("year")').gt(2015)
        ).and_(
            Key("product_id").seq(15)
        );
        ```
        
        ## <a name="formatter">Formatter</a>
        > `Formatter` allows fields to be queried from an object and then formatted
        >into a string. Any queries in a format string should be prefixed with `@` and any valid `JQL` query can be used. For example, 
        >`new Formatter('Name: @name}').single({"name": "John Smith"})` results in
        >`Name: John Smith`.
        
        ### `Formatter(spec, fallback="<missing>", [convert_ints=true (if Python)])`
         * `spec`: `str` The format string
         * `fallback`: `str` The value that will be used in the formatted string if a query could not be performed. For example, if the field `missing` does exist, then the query `"Age: @missing"` will result in `"Age: <missing>"`
         * `convert_ints`: `bool` Whether digit-only fields get treated as integers or strings
         
        #### `.single(item, context={})`
         * `context`: See [`Context`](#context) for more details
        > Return a formatted string or the fallback value if the query fails
        
        #### `.many(items, context={})`
         * `context`: See [`Context`](#context) for more details
        > Return a list of formatted strings or the fallback value.
        
        ### Notes
        >The differences between `Query` and `Formatter` are:
         * `Query` can return a value of any type, `Formatter` just returns strings
         * `Formatter` supports multiple queries, end-to-end, `Query` does not
         * All queries must be prefixed with `@` with `Formatter`, not just when used as an argument like with `Query`
         * Both support all the features of `JQL`
         * `Query` actually can theoretically do everything `Formatter` does by using `$prefix`, `$suffix`, and `$string`. 
         For example, `'@name @age'` -> `'name.$suffix(" ").$suffix(@age)'`. However, the latter is much longer than the former
         
        Example (flattening operations):
        
        ```python
        # Python
        errors = {
            "errors": {
                "Process Error": "Could not communicate with the subprocess",
                "Connection Error": "Could not connect with the database instance"
            }
        }
        
        Formatter('Errors: \n@errors.$items.$map("join", ": \\n\\t").$join("\\n")').single(errors)
        # Errors:
        # Process Error: 
        #   Could not communicate with the subprocess
        # Connection Error: 
        #   Could not connect with the database instance
        ```
        
        ```javascript
        // JavaScript
        const errors = {
            errors: {
                "Process Error": "Could not communicate with the subprocess",
                "Connection Error": "Could not connect with the database instance"
            }
        };
        
        new Formatter('Erros: @errors.$items.$map("join", ": \\n\\t").$join("\\n")}').single(errors);
        // Errors: 
        // Process Error: 
        //   Could not communicate with the subprocess
        // Connection Error: 
        //   Could not connect with the database instance
        ```
        >The above example shows a powerful usage of flattening `errors` into its items,
        >then joining each item; splitting the error name and message between lines, then
        >joining all the errors together.
        
        Example (nested replacement):
        
        ```python
        # Python
        item = {
            "x1": 1,
            "y1": 1,
            "x2": 12,
            "y2": 54
        }
        
        Formatter(
            "Midpoint: [@x2.$subtract(@x1).$divide(2), @y2.$subtract(@y1).$divide(2)]"
        )
        # Midpoint: [5.5, 26.5]
        ```
        
        ```javascript
        // JavaScript
        const item = {
            x1: 1,
            y1: 1,
            x2: 12,
            y2: 54
        };
        
        new Formatter(
            "Midpoint: [@x2.$subtract(@x1).$divide(2), @y2.$subtract(@y1).$divide(2)]"
        ).single(item);
        // Midpoint: [5.5, 26.5]
        ```
        
        
        ## <a name="performance">Performance</a>
        >There are several ways to increase the performance of querying, filtering, and formatting. The performance gains can be had
        >by limiting the amount of times a query string has to be parsed. This means that using a `Query`,
        >`Filter`, or `Formatter` object multiple times will be faster then creating a new object every time. 
        
        Examples:
        ```python
        # Python
        # slower
        for item in items:
            f = Query("timestamp.$parse_timestamp").single(item)
            # do other stuff
        
        # faster
        query = Query("timestamp.$parse_timestamp")
        for item in items:
            f = query.single(item)
            # do other stuff
        ```
        
        ```javascript
        // JavaScript
        // slower
        items.forEach(item => {
          let f = new Query("timestamp.$parse_timestamp").single(item);
          // do other stuff
        });
        
        // faster
        const query = new Query("timestamp.$parse_timestamp");
        items.forEach(item => {
          let f = query.single(item);
          // do other stuff
        });
        ```
        
        >Across 10,000 runs:
        * Python
           * reusing `Query` can improve performance by 302x
           * reusing `Filter` can improve performance by 132x
           * reusing `Formatter` can improve performance by 377x.
        * JavaScript
           * reusing `Query` can improve performance by 192
           * reusing `Filter` can improve performance by 120x
           * reusing `Formatter` can improve performance by 210x.
        
        ## Changelog
         * `1.1.3`
           * Changed the behavior of `new Query("")`, from returning the fallback value, to returning the source data element itself.
          For example, `new Query("").single(data) === data`.
           * Added `SpecialNotFoundError`, which is raised when an invalid special is queried. Can be imported as 
          `import { SpecialNotFoundError } from "@blending_jake/jtools";`
           * Added new specials
             * `$store_as(name)` Store the current query value in the current context for later use in the query. This does not 
           change the underlying data being queried.
             * `$group_by(key="", count=false)` Take an incoming list and group the values by the specified key.
           Any valid JQL query can be used for the key, so `""` means the value itself. The result by default will be
           keys to a list of values. However, if `count=true`, then the result will be keys to the number of elements with each 
           key.
             * `$sort(key="", reverse=false)` Sort an incoming list of values by a given key which can be any valid JQL query.
           By default, `key=""` means the top-level value will be sorted on.
             * `$dict` Take an incoming list of `(key, value)` pairs and make a dict out of them.
             * `$join_arg(arg, sep=', ')` Similar to `$join` except this operates on an argument instead of the query value.
           Essentially a shortened form of `$inject(arg).$join(sep)`.
           * Changed the underlying special function definition to now include the keyword argument `context`. This argument is 
          implemented to only be accessed by name to avoid collision if the user provides too many arguments in their query. 
          The purpose of the context is to support specials adding values temporarily to the data
          namespace of the query, like `$store_as` does.
        
         * `1.1.2`
           * Version `1.1.1` was skipped to keep on track with `JTools-Py`
           * Catch and handle `Extraneous Input Error`
           * Change `JQL` so that field and special names must only contain `[-a-zA-Z0-9_]`. `$index` can be used to get fields
           with prohibited characters. The change was to support more formatting use-cases, like `Age: @age, DOB: @dob`, which 
           previously would have failed because the `,` would have been considered part of the field name.
           * Change `Formatter` so that `fallback` is just a string that is substituted for invalid queries, instead of being
           the entire return value. Previously, `"Age: @missing"` would result in `None`, now it results in `"Age: <missing>"`.
           This change allows for better debugging as it becomes clear exactly which queries are failing.
           * Add function docstrings
        
         * `1.1.0`
           * Rename `Getter` to `Query` to more accurately describe what the class does
           * Migrate queries to use `JQL`
             * The migration opens the door to nested queries in `Query`, allowing queries, prefixed with `@` to be used
             as arguments to specials, or even as values in the supported argument data structures
             * Special arguments are no longer parsed as `JSON`, allowing features like sets, query nesting, and support
             for single and double quoted strings.
             * Formatter no longer uses `{{}}` to surround queries. Instead, all queries must be prefixed with `@`, so
             `"{{name}} {{age}}"` -> `"@name @age"`. `@@` must be used to get a literal `@` in a formatted string:
             `"bob@@gmail.com"` -> `"bob@gmail.com"`
             * Formatter got about a 2x performance boost
           * Added `$wrap(prefix, suffix)` to combine `$prefix` and `$suffix`
           * Added `$remove_nulls`
           * Added `$lookup(map, fallback=None)`
           * Added `$wildcard(next, just_value=True)`, which allows level of nesting to be "skipped", such that a list
           of sub-values where `next` is present
           * Added a `fallback` argument to `$index`
           * Added `$print` to display the current value in the query
           * Added `$inject` to allow any valid argument value to be injected into the query to be
          accessed and transformed by subsequent fields and specials
        
         * `1.0.6`
           * Migrate to TypeScript, so a declaration file is now included in the distribution
           * Add this `README`
           * Add `===` and `!==` filters for strict equality checking. The methods `seq` and `sne` have
           been added to `Key` to correspond with the new filters.
           * Rename `null` -> `!present` and `!null` -> `present`. Corresponding methods have been renamed
           to `not_present` and `present`. This filter will catch values that are `null` or `undefined`.
           * Make membership filters (`in`, `contains`, `!in` and `!contains`) work properly with 
           strings, arrays, associative arrays, and sets.
           * Remove `$datetime`. See below for replacement.
           * Add `$call` and `$attr` for calling a function and accessing an attribute. Can be used to replace
           `$datetime` functionality.
           * Remove `Formatter.format` and add `Formatter.single` and `Formatter.many` to be consistent across
           other classes and support formatting arrays of items.
           * Add more tests to increase coverage and do basic performance testing
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Database
Classifier: Topic :: Utilities
Requires-Python: >=3.5
Description-Content-Type: text/markdown
