With this article, we continue our journey through the realm of Solidity data types following today’s topics:

• contract types,
• fixed-size byte arrays,
• dynamically-sized byte arrays,
• address literals,
• rational, and
• integer literals.

It’s part of our long-standing tradition to make this (and other) articles a faithful companion or a supplement to the official Solidity documentation.

Download PDF Slide Deck at the end of this tutorial!

Contract Types

To quote the official Solidity documentation, “every contract defines its own type”.

This statement might seem a bit cryptic, and since we’re an efficient crowd, we’d surely like to know what it means.

We can all remember that some number of articles ago, we mentioned how Solidity has key elements of an object-oriented programming language (OOPL). We also emphasized how smart contracts in Solidity are very similar to classes in an OOPL.

Classes themselves are a mesh of custom data types, i.e. structs, and functions, which qualifies classes to be treated as types.

By extension, our contracts are also treated as types, and as every contract is unique in its own right, it defines its own type. Being a type, we can implicitly convert a specific contract to a contract it inherits from, i.e. if contract “Aa” inherits from contract A, it can also be converted to contract “A”.

Besides that, we can explicitly convert each contract to and from the address type. Even more, we can conditionally convert a contract to and from the address payable type (remember, that’s the same type as the address type, but predetermined to receive Ether).

The condition is that the contract type must have a receive or payable fallback function. If it does, we can make the conversion to address payable by using address(x).

However, if the contract type does not implement (a more professional way to say “have”) a receive or payable fallback function, then the conversion to address payable has to be even more explicit (no swearing!) by stating payable(address(x)).

A local variable obc of a contract type OurBeautifulContract is declared by OurBeautifulContract obc;.

Once we point our variable obc to an instantiated (newly created) contract, we’d be able to call functions on that contract.

In terms of its data representation, a contract is identical to the address type. This is important because the contract type is not directly supported by the ABI, but the address type, as its representative, is supported by the ABI.

In contrast to the types mentioned so far, contract types don’t support any operators.

The members of contract types are the external functions (the functions only available to other contracts) and state variables whose visibility is set to public.

When we need to access type information about the contract, like the OurBeautifulContract above, we’d call the type(OurBeautifulContract) function (docs).

Fixed-Size Byte Arrays

The value type bytesN holds a sequence of bytes, whose length, and accordingly N goes from 1 to up to 32, i.e., bytes1, …, bytes32.

The available operators for fixed-size operators are:

• Comparisons: <=, <, ==, !=, >=, > (evaluate to bool)
• Bit operators: &, |, ^ (bitwise exclusive or), ~ (bitwise negation)
• Shift operators: << (left shift), >> (right shift)
• Index access: If x is of type bytesN, then x[k] for 0 <= k < N returns the k-th byte (read-only). In other words, x[0] up to (inclusive) x[N-1] is available for index access; if N = 1, then only x is of type bytes1, and x[0] is the only element, i.e. byte accessible by the index.

The shifting operator always uses an unsigned integer type as a right operand, which represents the number of bits to shift by, and returns the type of the left operand.

Let’s take a look at a simple example to illustrate:

bytes2 lo = 0x1234; // (lo is the left operand)

uint8 ro = 5; // (ro is the right operand variable, must be u... type)

lo << ro // will evaluate to an lo type, bytes2

A fixed-size byte array has only one member, .length, that holds the fixed length of the byte array. This member is accessible as the read-only value.

Warning: Since the type bytes1 is a sequence of 1 byte in length, the type bytes1[] is a fixed-size byte array of 1-byte sequences. However, each element of the array is padded with 31 bytes, due to padding rules for elements stored in memory, stack, and call data, i.e., except in storage. Therefore, according to the official Solidity documentation, it’s better to use bytes type instead of bytes1[].

Note: Value types in storage are packed/compacted together and share a storage slot, taking only as much space per value type as really needed. In contrast, the stack, memory, and calldata pad value types and store in separate slots, meaning that each variable uses a whole slot of 32 bytes, even if the value type is shorter than 32 bytes, effectively wasting the memory space.

Before Solidity v0.8.0, the keyword byte was an alias for bytes1.

Dynamically-Sized Byte Arrays

There are two dynamically-sized non-value types, namely bytes and string.

• bytes is a dynamically-sized byte array, while
• string is a dynamically-sized UTF-8-encoded string.

Address Literals

Address literals are hexadecimal literals that pass the address checksum test, e.g. 0xdCad3a6d3569DF655070DEd06cb7A1b2Ccd1D3AF.

Hexadecimal literals will produce an error if they are between 39 and 41 digits long and do not pass the checksum test.

However, we can remove the error by prepending zeros to integer types or appending zeros to bytesNN types.

The Ethereum Improvement Proposal EIP-55 defines the mixed-case address checksum.

Integer and Rational Literals

Integer Literals

Integer literals are created using a sequence of digits from a range 0-9, and each digit is interpreted (weighted) based on its position in the sequence.

Multiplied by an exponent of 10, e.g. 217 is interpreted as two hundred and seventeen, because, reading from right to left, we have 7 * 10⁰ + 1 * 10¹ + 2 * 10².

A reminder, 10⁰ = 1.

Octal literals don’t exist in Solidity and leading zeros are invalid.

Decimal Fractional Literals

Decimal fractional literals consist of a dot . (or, depending on the locale) and at least one number on either of the sides, e.g. 1., .1, and 1.3.

Info: “A locale consists of a number of categories for which country-dependent formatting or other specifications exist” (source).

Scientific Notation

Solidity also supports scientific notation in the form of 2e10, where 2 (left of “e”) is called mantissa (M) and the exponent (E) must be an integer. In a general form, we would write it as MeE and it is interpreted as M * 10**E, e.g. 2e10, -2e10, 2e-10, 2.5e1.

Readable Underscore Notation

We can also do a neat thing: separate the digits of a numeric literal for easier readability, such as in decimal 123_000, hexadecimal 0x2eff_abde, scientific decimal notation 1_2e345_678.

However, there are no leading, trailing, or multiple underscores; they can only be added between two digits.

Number Literal Expressions

Expressions containing number literals preserve their precision until they are converted to a non-literal type.

Such a conversion means an explicit conversion, or that the number literals are used with something else than a number literal expression, like boolean literals.

This behavior implies that computations don’t overflow and divisions don’t truncate in number literal expressions.

A very good example would be a number literal expression (2**800 + 1) – 2**800, which results in the constant 1 (of type uint8), although the intermediate results would not fit the capacity of the EVM word length of 32 bytes.

One more example shows that an integer 4 is produced by computing the expression .5 * 8, although the intermediary results are not integers.

More Operations

Warning: most operators produce a literal expression when applied to number literals, but there are also two exceptions:

• Ternary operator (... ? ... : ...),
• Array subscript (<array>[<index>]).

In other words, expressions like 255 + (true ? 1 : 0) or 255 + [1, 2, 3][0] are not equivalent to using the literal 256 (the result of these two expressions), as they are computed within the type uint8 and can lead to an overflow.

Number literal expressions can use the same operators as the integers, but both operands must compute yield an integer.

• If either of the operands is fractional, bit operations are inapplicable for use;
• If the exponent is a decimal fractional literal, the exponentiation operation is also inapplicable for use.

Shifts and exponentiation * operations with literal numbers in place of a left (base*) operand and integer types in place of the right (exponent*) operand are performed in the uint256 for non-negative literals or int256 for negative literals (a * symbol pertains to the exponentiation operations context).

Warning: Since Solidity v0.4.0 division on integer literals produces a rational number, e.g. 7 / 2 = 3.5.

Solidity has a number literal types for each rational number, e.g. integer literals and rational number literals belong to the same number literal type.

All number literal expressions (expressions with only number literals and operators) also belong to number literal types, e.g. 1 + 2 and 2 + 1 belong to the same number literal type.

Note: When number literal types are used with non-literal expressions, they are converted into a non-literal type, e.g.  uint128 a = 1; uint128 b = 2.5 + a + 0.5;

Here, 1 is converted into a non-literal type uint128, i.e. variable a, but a common type for both 2.5 and uint128 doesn’t exist and the compiler will reject the code.

Conclusion

In this article, we added even more data types in Solidity under our proverbial belt!

• First, we introduced and learned about the contract type.
• Second, we fixed our understanding of the fixed-size byte array type.
• Third, the situation got dynamic by studying the dynamically-sized byte array type.
• Fourth, we addressed the… what was it called… Aha – address literals!
• Fifth, we came to the most rational decision and discovered what rational and integer literals are and, of course, how can they be put to good use.

Slide Deck Data Types

You can scroll through the data types discussed in this tutorial here:

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Question: Given a Boolean value True or False. How to convert it to a string "True" or "False" in Python?

Note that this tutorial doesn’t concern “concatenating a Boolean to a string”. If you want to do this, check out our in-depth article on the Finxter blog.

Simple Bool to String Conversion

To convert a given Boolean value to a string in Python, use the str(boolean) function and pass the Boolean value into it. This converts Boolean True to string "True" and Boolean False to string "False".

Here’s a minimal example:

>>> str(True) 'True'

>>> str(False) 'False'

Python Boolean Type is Integer

Booleans are represented by integers in Python, i.e., bool is a subclass of int. Boolean value True is represented with integer 1. And Boolean value False is represented with integer 0.

Here’s a minimal example:

>>> True == 1

True

>>> False == 0

True

Convert True to ‘1’ and False to ‘0’

To convert a Boolean value to a string '1' or '0', use the expression str(int(boolean)). For instance, str(int(True)) returns '1' and str(int(False)) returns '0'. This is because of Python’s use of integers to represent Boolean values.

Here’s a minimal example:

>>> str(int(True)) '1'

>>> str(int(False)) '0'

Convert List of Boolean to List of Strings

To convert a Boolean to a string list, use the list comprehension expression [str(x) for x in my_bools] assuming the Boolean list is stored in variable my_bools. This converts each Boolean x to a string using the built-in str() function and repeats it for all x in the Boolean list.

Here’s a simple example:

my_bools = [True, True, False, False, True]

my_strings = [str(x) for x in my_bools]

print(my_strings)

# ['True', 'True', 'False', 'False', 'True']

Convert String Back to Boolean

What if you want to convert the string representation 'True' and 'False' (or: '1' and '0') back to the Boolean representation True and False?

Recommended Tutorial: String to Boolean Conversion

Here’s the short summary:

You can convert a string value s to a Boolean value using the Python function bool(s).

For example, bool('True') and bool('1') return True.

However, bool('False') and bool('0') return False as well which may come unexpected to you.

This is because all Python objects are “truthy”, i.e., they have an associated Boolean value. As a rule of thumb: empty values return Boolean True and non-empty values return Boolean False. So, only bool('') on the empty string '' returns False. All other strings return True!

You can see this in the following example:

>>> bool('True')

True

>>> bool('1')

True

>>> bool('2')

True

>>> bool('False')

True

>>> bool('0')

True

>>> bool('')

False

Okay, what to do about it?

Easy – first pass the string into the eval() function and then pass the result into the bool() function. In other words, the expression bool(eval(my_string)) converts a string to a Boolean mapping 'True' and '1' to Boolean True and 'False' and '0' to Boolean False.

Finally – this behavior is as expected by many coders just starting out.

Here’s an example:

>>> bool(eval('False'))

False

>>> bool(eval('0'))

False

>>> bool(eval('True'))

True

>>> bool(eval('1'))

True

Feel free to go over our detailed guide on the function:

Recommended Tutorial: Python eval() deep dive