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lix/src/libexpr/nixexpr.cc

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* "Fix expression" -> "Nix expression". * More refactoring.
2003-11-18 12:06:07 +00:00
#include "nixexpr.hh"
* Renamed `normalise.cc' -> `build.cc', `storeexprs.cc' -> `derivations.cc', etc. * Store the SHA-256 content hash of store paths in the database after they have been built/added. This is so that we can check whether the store has been messed with (a la `rpm --verify'). * When registering path validity, verify that the closure property holds.
2005-01-19 16:39:47 +00:00
#include "derivations.hh"
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
#include "eval.hh"
#include "symbol-table.hh"
* Use a proper namespace. * Optimise header file usage a bit. * Compile the parser as C++.
2006-09-04 21:06:23 +00:00
#include "util.hh"
* Don't use ATmake / ATmatch anymore, nor the ATMatcher class. Instead we generate data bindings (build and match functions) for the constructors specified in `constructors.def'. In particular this removes the conversions between AFuns and strings, and Nix expression evaluation now seems 3 to 4 times faster.
2004-10-26 22:54:26 +00:00
* GCC 4.3.0 (Fedora 9) compatibility fixes. Reported by Gour and Armijn Hemel.
2008-05-21 11:17:31 +00:00
#include <cstdlib>
* Don't use ATmake / ATmatch anymore, nor the ATMatcher class. Instead we generate data bindings (build and match functions) for the constructors specified in `constructors.def'. In particular this removes the conversions between AFuns and strings, and Nix expression evaluation now seems 3 to 4 times faster.
2004-10-26 22:54:26 +00:00
* Use a proper namespace. * Optimise header file usage a bit. * Compile the parser as C++.
2006-09-04 21:06:23 +00:00
namespace nix {
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
/* Displaying abstract syntax trees. */
Remove std::string alias (for real this time) Also use std::string_view in a few more places.
2022-02-25 15:00:00 +00:00
static void showString(std::ostream & str, std::string_view s)
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
{
str << '"';
Remove std::string alias (for real this time) Also use std::string_view in a few more places.
2022-02-25 15:00:00 +00:00
for (auto c : s)
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
if (c == '"' || c == '\\' || c == '$') str << "\\" << c;
else if (c == '\n') str << "\\n";
else if (c == '\r') str << "\\r";
else if (c == '\t') str << "\\t";
else str << c;
str << '"';
}
Remove std::string alias (for real this time) Also use std::string_view in a few more places.
2022-02-25 15:00:00 +00:00
static void showId(std::ostream & str, std::string_view s)
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
{
showId: Handle empty attribute names We should probably disallow these, but until then, we shouldn't barf with an assertion failure. Fixes #738.
2015-12-17 14:15:28 +00:00
if (s.empty())
str << "\"\"";
else if (s == "if") // FIXME: handle other keywords
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
str << '"' << s << '"';
else {
char c = s[0];
if (!((c >= 'a' && c <= 'z') || (c >= 'A' && c <= 'Z') || c == '_')) {
showString(str, s);
return;
}
for (auto c : s)
if (!((c >= 'a' && c <= 'z') ||
(c >= 'A' && c <= 'Z') ||
(c >= '0' && c <= '9') ||
c == '_' || c == '\'' || c == '-')) {
showString(str, s);
return;
}
str << s;
}
}
std::ostream & operator << (std::ostream & str, const Symbol & sym)
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
showId(str, sym.s);
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
return str;
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void Expr::show(const SymbolTable & symbols, std::ostream & str) const
* Indented strings.
2010-04-12 22:03:27 +00:00
{
abort();
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprInt::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
str << n;
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprFloat::show(const SymbolTable & symbols, std::ostream & str) const
First hit at providing support for floats in the language.
2016-01-04 23:40:40 +00:00
{
str << nf;
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprString::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
showString(str, s);
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprPath::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
str << s;
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprVar::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << symbols[name];
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprSelect::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "(";
e->show(symbols, str);
str << ")." << showAttrPath(symbols, attrPath);
if (def) {
str << " or (";
def->show(symbols, str);
str << ")";
}
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprOpHasAttr::show(const SymbolTable & symbols, std::ostream & str) const
* More missing constructs.
2010-04-12 21:21:24 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "((";
e->show(symbols, str);
str << ") ? " << showAttrPath(symbols, attrPath) << ")";
* More missing constructs.
2010-04-12 21:21:24 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprAttrs::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
if (recursive) str << "rec ";
str << "{ ";
ExprAttrs::show(): Show attrs in sorted order Issue #6160.
2022-02-25 08:21:04 +00:00
typedef const decltype(attrs)::value_type * Attr;
std::vector<Attr> sorted;
for (auto & i : attrs) sorted.push_back(&i);
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
std::sort(sorted.begin(), sorted.end(), [&](Attr a, Attr b) {
std::string_view sa = symbols[a->first], sb = symbols[b->first];
return sa < sb;
});
ExprAttrs::show(): Show attrs in sorted order Issue #6160.
2022-02-25 08:21:04 +00:00
for (auto & i : sorted) {
if (i->second.inherited)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "inherit " << symbols[i->first] << " " << "; ";
else {
str << symbols[i->first] << " = ";
i->second.e->show(symbols, str);
str << "; ";
}
}
for (auto & i : dynamicAttrs) {
str << "\"${";
i.nameExpr->show(symbols, str);
str << "}\" = ";
i.valueExpr->show(symbols, str);
str << "; ";
ExprAttrs::show(): Show attrs in sorted order Issue #6160.
2022-02-25 08:21:04 +00:00
}
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
str << "}";
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprList::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
str << "[ ";
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
for (auto & i : elems) {
str << "(";
i->show(symbols, str);
str << ") ";
}
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
str << "]";
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprLambda::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
str << "(";
libexpr: remove matchAttrs boolean from ExprLambda The boolean is only used to determine if the formals are set to a non-null pointer in all our cases. We can get rid of that allocation and instead just compare the pointer value with NULL. Saving up to sizeof(bool) + platform specific alignment per ExprLambda instace. Probably not a lot of memory but perhaps a few kilobyte with nixpkgs? This also gets rid of a potential issue with dereferencing formals based on the value of the boolean that didn't have to be aligned with the formals pointer but was in all our cases.
2021-10-06 15:08:08 +00:00
if (hasFormals()) {
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
str << "{ ";
bool first = true;
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : formals->formals) {
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
if (first) first = false; else str << ", ";
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << symbols[i.name];
if (i.def) {
str << " ? ";
i.def->show(symbols, str);
}
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
if (formals->ellipsis) {
if (!first) str << ", ";
str << "...";
}
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
str << " }";
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (arg) str << " @ ";
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (arg) str << symbols[arg];
str << ": ";
body->show(symbols, str);
str << ")";
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprCall::show(const SymbolTable & symbols, std::ostream & str) const
Optimize primop calls We now parse function applications as a vector of arguments rather than as a chain of binary applications, e.g. 'substring 1 2 "foo"' is parsed as ExprCall { .fun = <substring>, .args = [ <1>, <2>, <"foo"> ] } rather than ExprApp (ExprApp (ExprApp <substring> <1>) <2>) <"foo"> This allows primops to be called immediately (if enough arguments are supplied) without having to allocate intermediate tPrimOpApp values. On $ nix-instantiate --dry-run '<nixpkgs/nixos/release-combined.nix>' -A nixos.tests.simple.x86_64-linux this gives a substantial performance improvement: user CPU time: median = 0.9209 mean = 0.9218 stddev = 0.0073 min = 0.9086 max = 0.9340 [rejected, p=0.00000, Δ=-0.21433±0.00677] elapsed time: median = 1.0585 mean = 1.0584 stddev = 0.0024 min = 1.0523 max = 1.0623 [rejected, p=0.00000, Δ=-0.20594±0.00236] because it reduces the number of tPrimOpApp allocations from 551990 to 42534 (i.e. only small minority of primop calls are partially applied) which in turn reduces time spent in the garbage collector.
2020-02-24 00:32:01 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << '(';
fun->show(symbols, str);
Optimize primop calls We now parse function applications as a vector of arguments rather than as a chain of binary applications, e.g. 'substring 1 2 "foo"' is parsed as ExprCall { .fun = <substring>, .args = [ <1>, <2>, <"foo"> ] } rather than ExprApp (ExprApp (ExprApp <substring> <1>) <2>) <"foo"> This allows primops to be called immediately (if enough arguments are supplied) without having to allocate intermediate tPrimOpApp values. On $ nix-instantiate --dry-run '<nixpkgs/nixos/release-combined.nix>' -A nixos.tests.simple.x86_64-linux this gives a substantial performance improvement: user CPU time: median = 0.9209 mean = 0.9218 stddev = 0.0073 min = 0.9086 max = 0.9340 [rejected, p=0.00000, Δ=-0.21433±0.00677] elapsed time: median = 1.0585 mean = 1.0584 stddev = 0.0024 min = 1.0523 max = 1.0623 [rejected, p=0.00000, Δ=-0.20594±0.00236] because it reduces the number of tPrimOpApp allocations from 551990 to 42534 (i.e. only small minority of primop calls are partially applied) which in turn reduces time spent in the garbage collector.
2020-02-24 00:32:01 +00:00
for (auto e : args) {
str << ' ';
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
e->show(symbols, str);
Optimize primop calls We now parse function applications as a vector of arguments rather than as a chain of binary applications, e.g. 'substring 1 2 "foo"' is parsed as ExprCall { .fun = <substring>, .args = [ <1>, <2>, <"foo"> ] } rather than ExprApp (ExprApp (ExprApp <substring> <1>) <2>) <"foo"> This allows primops to be called immediately (if enough arguments are supplied) without having to allocate intermediate tPrimOpApp values. On $ nix-instantiate --dry-run '<nixpkgs/nixos/release-combined.nix>' -A nixos.tests.simple.x86_64-linux this gives a substantial performance improvement: user CPU time: median = 0.9209 mean = 0.9218 stddev = 0.0073 min = 0.9086 max = 0.9340 [rejected, p=0.00000, Δ=-0.21433±0.00677] elapsed time: median = 1.0585 mean = 1.0584 stddev = 0.0024 min = 1.0523 max = 1.0623 [rejected, p=0.00000, Δ=-0.20594±0.00236] because it reduces the number of tPrimOpApp allocations from 551990 to 42534 (i.e. only small minority of primop calls are partially applied) which in turn reduces time spent in the garbage collector.
2020-02-24 00:32:01 +00:00
}
str << ')';
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprLet::show(const SymbolTable & symbols, std::ostream & str) const
* Evaluate lets directly (i.e. without desugaring to `rec { attrs...; <let-body> = e; }.<let-body>). This prevents the unnecessary allocation of an attribute set.
2010-04-13 13:42:25 +00:00
{
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
str << "(let ";
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrs->attrs)
if (i.second.inherited) {
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "inherit " << symbols[i.first] << "; ";
}
else {
str << symbols[i.first] << " = ";
i.second.e->show(symbols, str);
str << "; ";
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "in ";
body->show(symbols, str);
str << ")";
* Evaluate lets directly (i.e. without desugaring to `rec { attrs...; <let-body> = e; }.<let-body>). This prevents the unnecessary allocation of an attribute set.
2010-04-13 13:42:25 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprWith::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "(with ";
attrs->show(symbols, str);
str << "; ";
body->show(symbols, str);
str << ")";
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprIf::show(const SymbolTable & symbols, std::ostream & str) const
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "(if ";
cond->show(symbols, str);
str << " then ";
then->show(symbols, str);
str << " else ";
else_->show(symbols, str);
str << ")";
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprAssert::show(const SymbolTable & symbols, std::ostream & str) const
* More missing constructs.
2010-04-12 21:21:24 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "assert ";
cond->show(symbols, str);
str << "; ";
body->show(symbols, str);
* More missing constructs.
2010-04-12 21:21:24 +00:00
}
* Don't use ATerms for the abstract syntax trees anymore. Not finished yet.
2010-04-12 18:30:11 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprOpNot::show(const SymbolTable & symbols, std::ostream & str) const
* More missing constructs.
2010-04-12 21:21:24 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
str << "(! ";
e->show(symbols, str);
str << ")";
* More missing constructs.
2010-04-12 21:21:24 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprConcatStrings::show(const SymbolTable & symbols, std::ostream & str) const
* More missing constructs.
2010-04-12 21:21:24 +00:00
{
bool first = true;
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
str << "(";
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : *es) {
* More missing constructs.
2010-04-12 21:21:24 +00:00
if (first) first = false; else str << " + ";
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
i.second->show(symbols, str);
* More missing constructs.
2010-04-12 21:21:24 +00:00
}
Improve printing of ASTs
2014-10-20 06:44:32 +00:00
str << ")";
* More missing constructs.
2010-04-12 21:21:24 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprPos::show(const SymbolTable & symbols, std::ostream & str) const
Add a symbol __curPos that expands to the current source location I.e. an attribute set { file = <string>; line = <int>; column = <int>; }.
2013-11-18 19:14:54 +00:00
{
str << "__curPos";
}
* More missing constructs.
2010-04-12 21:21:24 +00:00
std::ostream & operator << (std::ostream & str, const Pos & pos)
* When something goes wrong in the evaluation of a Nix expression, print a nice backtrace of the stack, rather than vomiting a gigantic (and useless) aterm on the screen. Example: error: while evaluating file `.../pkgs/system/test.nix': while evaluating attribute `subversion' at `.../pkgs/system/all-packages-generic.nix', line 533: while evaluating function at `.../pkgs/applications/version-management/subversion/default.nix', line 1: assertion failed at `.../pkgs/applications/version-management/subversion/default.nix', line 13 Since the Nix expression language is lazy, the trace may be misleading. The purpose is to provide a hint as to the location of the problem.
2004-04-05 22:27:41 +00:00
{
forceString: Show position info
2014-04-04 19:14:11 +00:00
if (!pos)
* More missing constructs.
2010-04-12 21:21:24 +00:00
str << "undefined position";
else
comments and cleanup
2020-06-30 22:31:55 +00:00
{
position for stdin, string; (string) for trace; fix tests
2020-05-21 20:28:45 +00:00
auto f = format(ANSI_BOLD "%1%" ANSI_NORMAL ":%2%:%3%");
comments and cleanup
2020-06-30 22:31:55 +00:00
switch (pos.origin) {
position for stdin, string; (string) for trace; fix tests
2020-05-21 20:28:45 +00:00
case foFile:
Remove std::string alias (for real this time) Also use std::string_view in a few more places.
2022-02-25 15:00:00 +00:00
f % (const std::string &) pos.file;
position for stdin, string; (string) for trace; fix tests
2020-05-21 20:28:45 +00:00
break;
case foStdin:
case foString:
f % "(string)";
break;
default:
throw Error("unhandled Pos origin!");
}
str << (f % pos.line % pos.column).str();
}
* More missing constructs.
2010-04-12 21:21:24 +00:00
return str;
* When something goes wrong in the evaluation of a Nix expression, print a nice backtrace of the stack, rather than vomiting a gigantic (and useless) aterm on the screen. Example: error: while evaluating file `.../pkgs/system/test.nix': while evaluating attribute `subversion' at `.../pkgs/system/all-packages-generic.nix', line 533: while evaluating function at `.../pkgs/applications/version-management/subversion/default.nix', line 1: assertion failed at `.../pkgs/applications/version-management/subversion/default.nix', line 13 Since the Nix expression language is lazy, the trace may be misleading. The purpose is to provide a hint as to the location of the problem.
2004-04-05 22:27:41 +00:00
}
* Work around problems with the ATerm library. The ATerm library doesn't search the heap for pointers to ATerms when garbage collecting. As a result, C++ containers such as `map<ATerm, ATerm>' will cause pointer to be hidden from the garbage collector, causing crashes. Instead, we now use ATermTables.
2003-11-03 20:30:40 +00:00
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
std::string showAttrPath(const SymbolTable & symbols, const AttrPath & attrPath)
* In the ‘?’ operator, allow attribute paths. For instance, you can write ‘attrs ? a.b’ to test whether ‘attrs’ has an attribute ‘a’ containing an attribute ‘b’. This is more convenient than ‘attrs ? a && attrs.a ? b’. Slight change in the semantics: it's no longer an error if the left-hand side of ‘?’ is not an attribute set. In that case it just returns false. So, ‘null ? foo’ no longer throws an error.
2011-07-06 10:58:17 +00:00
{
Don't use any syntactic sugar for dynamic attrs This doesn't change any functionality but moves some behavior out of the parser and into the evaluator in order to simplify the code. Signed-off-by: Shea Levy <shea@shealevy.com>
2013-12-31 23:56:26 +00:00
std::ostringstream out;
bool first = true;
Improve error message
2015-03-06 13:24:08 +00:00
for (auto & i : attrPath) {
if (!first) out << '.'; else first = false;
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (i.symbol)
out << symbols[i.symbol];
else {
out << "\"${";
i.expr->show(symbols, out);
out << "}\"";
}
* In the ‘?’ operator, allow attribute paths. For instance, you can write ‘attrs ? a.b’ to test whether ‘attrs’ has an attribute ‘a’ containing an attribute ‘b’. This is more convenient than ‘attrs ? a && attrs.a ? b’. Slight change in the semantics: it's no longer an error if the left-hand side of ‘?’ is not an attribute set. In that case it just returns false. So, ‘null ? foo’ no longer throws an error.
2011-07-06 10:58:17 +00:00
}
Don't use any syntactic sugar for dynamic attrs This doesn't change any functionality but moves some behavior out of the parser and into the evaluator in order to simplify the code. Signed-off-by: Shea Levy <shea@shealevy.com>
2013-12-31 23:56:26 +00:00
return out.str();
* In the ‘?’ operator, allow attribute paths. For instance, you can write ‘attrs ? a.b’ to test whether ‘attrs’ has an attribute ‘a’ containing an attribute ‘b’. This is more convenient than ‘attrs ? a && attrs.a ? b’. Slight change in the semantics: it's no longer an error if the left-hand side of ‘?’ is not an attribute set. In that case it just returns false. So, ‘null ? foo’ no longer throws an error.
2011-07-06 10:58:17 +00:00
}
* Store attribute positions in the AST and report duplicate attribute errors with position info. * For all positions, use the position of the first character of the first token, rather than the last character of the first token plus one.
2010-05-06 16:46:48 +00:00
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
/* Computing levels/displacements for variables. */
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void Expr::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
abort();
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprInt::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprFloat::bindVars(const EvalState & es, const StaticEnv & env)
First hit at providing support for floats in the language.
2016-01-04 23:40:40 +00:00
{
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprString::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprPath::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprVar::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
/* Check whether the variable appears in the environment. If so,
set its level and displacement. */
const StaticEnv * curEnv;
Add level / displacement types
2020-02-24 13:33:01 +00:00
Level level;
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
int withLevel = -1;
for (curEnv = &env, level = 0; curEnv; curEnv = curEnv->up, level++) {
if (curEnv->isWith) {
if (withLevel == -1) withLevel = level;
} else {
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
auto i = curEnv->find(name);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
if (i != curEnv->vars.end()) {
fromWith = false;
this->level = level;
displ = i->second;
return;
}
* Refactoring: combine functions that take an attribute set and functions that take a single argument (plain lambdas) into one AST node (Function) that contains a Pattern node describing the arguments. Current patterns are single lazy arguments (VarPat) and matching against an attribute set (AttrsPat). This refactoring allows other kinds of patterns to be added easily, such as Haskell-style @-patterns, or list pattern matching.
2008-08-14 10:04:22 +00:00
}
}
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
/* Otherwise, the variable must be obtained from the nearest
enclosing `with'. If there is no `with', then we can issue an
"undefined variable" error now. */
Remove trailing whitespace
2020-06-15 12:12:39 +00:00
if (withLevel == -1)
Get rid of explicit ErrorInfo constructors
2020-06-15 12:06:58 +00:00
throw UndefinedVarError({
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
.msg = hintfmt("undefined variable '%1%'", es.symbols[name]),
.errPos = es.positions[pos]
Get rid of explicit ErrorInfo constructors
2020-06-15 12:06:58 +00:00
});
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
fromWith = true;
this->level = withLevel;
* Refactoring: combine functions that take an attribute set and functions that take a single argument (plain lambdas) into one AST node (Function) that contains a Pattern node describing the arguments. Current patterns are single lazy arguments (VarPat) and matching against an attribute set (AttrsPat). This refactoring allows other kinds of patterns to be added easily, such as Haskell-style @-patterns, or list pattern matching.
2008-08-14 10:04:22 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprSelect::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
e->bindVars(es, env);
if (def) def->bindVars(es, env);
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrPath)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (!i.symbol)
i.expr->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
* Refactoring: combine functions that take an attribute set and functions that take a single argument (plain lambdas) into one AST node (Function) that contains a Pattern node describing the arguments. Current patterns are single lazy arguments (VarPat) and matching against an attribute set (AttrsPat). This refactoring allows other kinds of patterns to be added easily, such as Haskell-style @-patterns, or list pattern matching.
2008-08-14 10:04:22 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprOpHasAttr::bindVars(const EvalState & es, const StaticEnv & env)
* Verify that all variables in a Nix expression are defined.
2004-02-03 14:45:34 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
e->bindVars(es, env);
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrPath)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (!i.symbol)
i.expr->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprAttrs::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
Fix potential segfault The newEnv variable was accessed (via the dynamicEnv) pointer after it had gone out of scope. Fixes #234.
2014-04-01 15:04:38 +00:00
const StaticEnv * dynamicEnv = &env;
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
StaticEnv newEnv(false, &env, recursive ? attrs.size() : 0);
Fix potential segfault The newEnv variable was accessed (via the dynamicEnv) pointer after it had gone out of scope. Fixes #234.
2014-04-01 15:04:38 +00:00
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
if (recursive) {
Dynamic attrs This adds new syntax for attribute names: * attrs."${name}" => getAttr name attrs * attrs ? "${name}" => isAttrs attrs && hasAttr attrs name * attrs."${name}" or def => if attrs ? "${name}" then attrs."${name}" else def * { "${name}" = value; } => listToAttrs [{ inherit name value; }] Of course, it's a bit more complicated than that. The attribute chains can be arbitrarily long and contain combinations of static and dynamic parts (e.g. attrs."${foo}".bar."${baz}" or qux), which is relatively straightforward for the getAttrs/hasAttrs cases but is more complex for the listToAttrs case due to rules about duplicate attribute definitions. For attribute sets with dynamic attribute names, duplicate static attributes are detected at parse time while duplicate dynamic attributes are detected when the attribute set is forced. So, for example, { a = null; a.b = null; "${"c"}" = true; } will be a parse-time error, while { a = {}; "${"a"}".b = null; c = true; } will be an eval-time error (technically that case could theoretically be detected at parse time, but the general case would require full evaluation). Moreover, duplicate dynamic attributes are not allowed even in cases where they would be with static attributes ({ a.b.d = true; a.b.c = false; } is legal, but { a."${"b"}".d = true; a."${"b"}".c = false; } is not). This restriction might be relaxed in the future in cases where the static variant would not be an error, but it is not obvious that that is desirable. Finally, recursive attribute sets with dynamic attributes have the static attributes in scope but not the dynamic ones. So rec { a = true; "${"b"}" = a; } is equivalent to { a = true; b = true; } but rec { "${"a"}" = true; b = a; } would be an error or use a from the surrounding scope if it exists. Note that the getAttr, getAttr or default, and hasAttr are all implemented purely in the parser as syntactic sugar, while attribute sets with dynamic attribute names required changes to the AST to be implemented cleanly. This is an alternative solution to and closes #167 Signed-off-by: Shea Levy <shea@shealevy.com>
2013-09-21 03:25:30 +00:00
dynamicEnv = &newEnv;
Fix whitespace
2013-09-02 14:29:15 +00:00
Add level / displacement types
2020-02-24 13:33:01 +00:00
Displacement displ = 0;
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrs)
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
newEnv.vars.emplace_back(i.first, i.second.displ = displ++);
// No need to sort newEnv since attrs is in sorted order.
Fix whitespace
2013-09-02 14:29:15 +00:00
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrs)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
i.second.e->bindVars(es, i.second.inherited ? env : newEnv);
* New language feature: with expressions. The expression `with E1; E2' evaluates to E2 with all bindings in the attribute set E1 substituted. E.g., with {x = 123;}; x evaluates to 123. That is, the attribute set E1 is in scope in E2. This is particularly useful when importing files containing lots definitions. E.g., instead of let { inherit (import ./foo.nix) a b c d e f; body = ... a ... f ...; } we can now say with import ./foo.nix; ... a ... f ... I.e., we don't have to say what variables should be brought into scope.
2004-10-25 16:54:56 +00:00
}
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
* Keep attribute sets in sorted order to speed up attribute lookups. * Simplify the representation of attributes in the AST. * Change the behaviour of listToAttrs() in case of duplicate names.
2010-10-24 19:52:33 +00:00
else
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrs)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
i.second.e->bindVars(es, env);
Dynamic attrs This adds new syntax for attribute names: * attrs."${name}" => getAttr name attrs * attrs ? "${name}" => isAttrs attrs && hasAttr attrs name * attrs."${name}" or def => if attrs ? "${name}" then attrs."${name}" else def * { "${name}" = value; } => listToAttrs [{ inherit name value; }] Of course, it's a bit more complicated than that. The attribute chains can be arbitrarily long and contain combinations of static and dynamic parts (e.g. attrs."${foo}".bar."${baz}" or qux), which is relatively straightforward for the getAttrs/hasAttrs cases but is more complex for the listToAttrs case due to rules about duplicate attribute definitions. For attribute sets with dynamic attribute names, duplicate static attributes are detected at parse time while duplicate dynamic attributes are detected when the attribute set is forced. So, for example, { a = null; a.b = null; "${"c"}" = true; } will be a parse-time error, while { a = {}; "${"a"}".b = null; c = true; } will be an eval-time error (technically that case could theoretically be detected at parse time, but the general case would require full evaluation). Moreover, duplicate dynamic attributes are not allowed even in cases where they would be with static attributes ({ a.b.d = true; a.b.c = false; } is legal, but { a."${"b"}".d = true; a."${"b"}".c = false; } is not). This restriction might be relaxed in the future in cases where the static variant would not be an error, but it is not obvious that that is desirable. Finally, recursive attribute sets with dynamic attributes have the static attributes in scope but not the dynamic ones. So rec { a = true; "${"b"}" = a; } is equivalent to { a = true; b = true; } but rec { "${"a"}" = true; b = a; } would be an error or use a from the surrounding scope if it exists. Note that the getAttr, getAttr or default, and hasAttr are all implemented purely in the parser as syntactic sugar, while attribute sets with dynamic attribute names required changes to the AST to be implemented cleanly. This is an alternative solution to and closes #167 Signed-off-by: Shea Levy <shea@shealevy.com>
2013-09-21 03:25:30 +00:00
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : dynamicAttrs) {
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
i.nameExpr->bindVars(es, *dynamicEnv);
i.valueExpr->bindVars(es, *dynamicEnv);
Dynamic attrs This adds new syntax for attribute names: * attrs."${name}" => getAttr name attrs * attrs ? "${name}" => isAttrs attrs && hasAttr attrs name * attrs."${name}" or def => if attrs ? "${name}" then attrs."${name}" else def * { "${name}" = value; } => listToAttrs [{ inherit name value; }] Of course, it's a bit more complicated than that. The attribute chains can be arbitrarily long and contain combinations of static and dynamic parts (e.g. attrs."${foo}".bar."${baz}" or qux), which is relatively straightforward for the getAttrs/hasAttrs cases but is more complex for the listToAttrs case due to rules about duplicate attribute definitions. For attribute sets with dynamic attribute names, duplicate static attributes are detected at parse time while duplicate dynamic attributes are detected when the attribute set is forced. So, for example, { a = null; a.b = null; "${"c"}" = true; } will be a parse-time error, while { a = {}; "${"a"}".b = null; c = true; } will be an eval-time error (technically that case could theoretically be detected at parse time, but the general case would require full evaluation). Moreover, duplicate dynamic attributes are not allowed even in cases where they would be with static attributes ({ a.b.d = true; a.b.c = false; } is legal, but { a."${"b"}".d = true; a."${"b"}".c = false; } is not). This restriction might be relaxed in the future in cases where the static variant would not be an error, but it is not obvious that that is desirable. Finally, recursive attribute sets with dynamic attributes have the static attributes in scope but not the dynamic ones. So rec { a = true; "${"b"}" = a; } is equivalent to { a = true; b = true; } but rec { "${"a"}" = true; b = a; } would be an error or use a from the surrounding scope if it exists. Note that the getAttr, getAttr or default, and hasAttr are all implemented purely in the parser as syntactic sugar, while attribute sets with dynamic attribute names required changes to the AST to be implemented cleanly. This is an alternative solution to and closes #167 Signed-off-by: Shea Levy <shea@shealevy.com>
2013-09-21 03:25:30 +00:00
}
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprList::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : elems)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
i->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprLambda::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
StaticEnv newEnv(
false, &env,
(hasFormals() ? formals->formals.size() : 0) +
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
(!arg ? 0 : 1));
Fix whitespace
2013-09-02 14:29:15 +00:00
Add level / displacement types
2020-02-24 13:33:01 +00:00
Displacement displ = 0;
Fix whitespace
2013-09-02 14:29:15 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (arg) newEnv.vars.emplace_back(arg, displ++);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
libexpr: remove matchAttrs boolean from ExprLambda The boolean is only used to determine if the formals are set to a non-null pointer in all our cases. We can get rid of that allocation and instead just compare the pointer value with NULL. Saving up to sizeof(bool) + platform specific alignment per ExprLambda instace. Probably not a lot of memory but perhaps a few kilobyte with nixpkgs? This also gets rid of a potential issue with dereferencing formals based on the value of the boolean that didn't have to be aligned with the formals pointer but was in all our cases.
2021-10-06 15:08:08 +00:00
if (hasFormals()) {
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : formals->formals)
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
newEnv.vars.emplace_back(i.name, displ++);
newEnv.sort();
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : formals->formals)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
if (i.def) i.def->bindVars(es, newEnv);
* Verify that all variables in a Nix expression are defined.
2004-02-03 14:45:34 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
body->bindVars(es, newEnv);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprCall::bindVars(const EvalState & es, const StaticEnv & env)
Optimize primop calls We now parse function applications as a vector of arguments rather than as a chain of binary applications, e.g. 'substring 1 2 "foo"' is parsed as ExprCall { .fun = <substring>, .args = [ <1>, <2>, <"foo"> ] } rather than ExprApp (ExprApp (ExprApp <substring> <1>) <2>) <"foo"> This allows primops to be called immediately (if enough arguments are supplied) without having to allocate intermediate tPrimOpApp values. On $ nix-instantiate --dry-run '<nixpkgs/nixos/release-combined.nix>' -A nixos.tests.simple.x86_64-linux this gives a substantial performance improvement: user CPU time: median = 0.9209 mean = 0.9218 stddev = 0.0073 min = 0.9086 max = 0.9340 [rejected, p=0.00000, Δ=-0.21433±0.00677] elapsed time: median = 1.0585 mean = 1.0584 stddev = 0.0024 min = 1.0523 max = 1.0623 [rejected, p=0.00000, Δ=-0.20594±0.00236] because it reduces the number of tPrimOpApp allocations from 551990 to 42534 (i.e. only small minority of primop calls are partially applied) which in turn reduces time spent in the garbage collector.
2020-02-24 00:32:01 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
fun->bindVars(es, env);
Optimize primop calls We now parse function applications as a vector of arguments rather than as a chain of binary applications, e.g. 'substring 1 2 "foo"' is parsed as ExprCall { .fun = <substring>, .args = [ <1>, <2>, <"foo"> ] } rather than ExprApp (ExprApp (ExprApp <substring> <1>) <2>) <"foo"> This allows primops to be called immediately (if enough arguments are supplied) without having to allocate intermediate tPrimOpApp values. On $ nix-instantiate --dry-run '<nixpkgs/nixos/release-combined.nix>' -A nixos.tests.simple.x86_64-linux this gives a substantial performance improvement: user CPU time: median = 0.9209 mean = 0.9218 stddev = 0.0073 min = 0.9086 max = 0.9340 [rejected, p=0.00000, Δ=-0.21433±0.00677] elapsed time: median = 1.0585 mean = 1.0584 stddev = 0.0024 min = 1.0523 max = 1.0623 [rejected, p=0.00000, Δ=-0.20594±0.00236] because it reduces the number of tPrimOpApp allocations from 551990 to 42534 (i.e. only small minority of primop calls are partially applied) which in turn reduces time spent in the garbage collector.
2020-02-24 00:32:01 +00:00
for (auto e : args)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
e->bindVars(es, env);
Optimize primop calls We now parse function applications as a vector of arguments rather than as a chain of binary applications, e.g. 'substring 1 2 "foo"' is parsed as ExprCall { .fun = <substring>, .args = [ <1>, <2>, <"foo"> ] } rather than ExprApp (ExprApp (ExprApp <substring> <1>) <2>) <"foo"> This allows primops to be called immediately (if enough arguments are supplied) without having to allocate intermediate tPrimOpApp values. On $ nix-instantiate --dry-run '<nixpkgs/nixos/release-combined.nix>' -A nixos.tests.simple.x86_64-linux this gives a substantial performance improvement: user CPU time: median = 0.9209 mean = 0.9218 stddev = 0.0073 min = 0.9086 max = 0.9340 [rejected, p=0.00000, Δ=-0.21433±0.00677] elapsed time: median = 1.0585 mean = 1.0584 stddev = 0.0024 min = 1.0523 max = 1.0623 [rejected, p=0.00000, Δ=-0.20594±0.00236] because it reduces the number of tPrimOpApp allocations from 551990 to 42534 (i.e. only small minority of primop calls are partially applied) which in turn reduces time spent in the garbage collector.
2020-02-24 00:32:01 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprLet::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
StaticEnv newEnv(false, &env, attrs->attrs.size());
Fix whitespace
2013-09-02 14:29:15 +00:00
Add level / displacement types
2020-02-24 13:33:01 +00:00
Displacement displ = 0;
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrs->attrs)
StaticEnv: Use std::vector instead of std::map
2020-02-21 17:31:16 +00:00
newEnv.vars.emplace_back(i.first, i.second.displ = displ++);
// No need to sort newEnv since attrs->attrs is in sorted order.
Fix whitespace
2013-09-02 14:29:15 +00:00
OCD: foreach -> C++11 ranged for
2015-07-17 17:24:28 +00:00
for (auto & i : attrs->attrs)
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
i.second.e->bindVars(es, i.second.inherited ? env : newEnv);
Fix whitespace
2013-09-02 14:29:15 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
body->bindVars(es, newEnv);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprWith::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
* Implemented withs.
2010-04-14 15:01:04 +00:00
/* Does this `with' have an enclosing `with'? If so, record its
* Simplify the implementation of `with'. This gives a 7% speedup in evaluating the NixOS system configuration.
2010-04-22 15:08:09 +00:00
level so that `lookupVar' can look up variables in the previous
`with' if this one doesn't contain the desired attribute. */
* Implemented withs.
2010-04-14 15:01:04 +00:00
const StaticEnv * curEnv;
Add level / displacement types
2020-02-24 13:33:01 +00:00
Level level;
* Simplify the implementation of `with'. This gives a 7% speedup in evaluating the NixOS system configuration.
2010-04-22 15:08:09 +00:00
prevWith = 0;
for (curEnv = &env, level = 1; curEnv; curEnv = curEnv->up, level++)
* Implemented withs.
2010-04-14 15:01:04 +00:00
if (curEnv->isWith) {
prevWith = level;
break;
}
Fix whitespace
2013-09-02 14:29:15 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
attrs->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
StaticEnv newEnv(true, &env);
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
body->bindVars(es, newEnv);
* Memoise checkVarDefs since internally produced terms (i.e., not the result of parsing) can have very heavy sharing, causing exponential complexity if we naively recurse into them. ATerms are graphs, not trees!
2005-11-04 15:17:05 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprIf::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
cond->bindVars(es, env);
then->bindVars(es, env);
else_->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprAssert::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
cond->bindVars(es, env);
body->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprOpNot::bindVars(const EvalState & es, const StaticEnv & env)
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
e->bindVars(es, env);
* After parsing, compute level/displacement pairs for each variable use site, allowing environments to be stores as vectors of values rather than maps. This should speed up evaluation and reduce the number of allocations.
2010-04-14 14:42:32 +00:00
}
* Memoise checkVarDefs since internally produced terms (i.e., not the result of parsing) can have very heavy sharing, causing exponential complexity if we naively recurse into them. ATerms are graphs, not trees!
2005-11-04 15:17:05 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprConcatStrings::bindVars(const EvalState & es, const StaticEnv & env)
* Memoise checkVarDefs since internally produced terms (i.e., not the result of parsing) can have very heavy sharing, causing exponential complexity if we naively recurse into them. ATerms are graphs, not trees!
2005-11-04 15:17:05 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
for (auto & i : *this->es)
i.second->bindVars(es, env);
* Verify that all variables in a Nix expression are defined.
2004-02-03 14:45:34 +00:00
}
* Big cleanup of the semantics of paths, strings, contexts, string concatenation and string coercion. This was a big mess (see e.g. NIX-67). Contexts are now folded into strings, so that they don't cause evaluation errors when they're not expected. The semantics of paths has been clarified (see nixexpr-ast.def). toString() and coerceToString() have been merged. Semantic change: paths are now copied to the store when they're in a concatenation (and in most other situations - that's the formalisation of the meaning of a path). So "foo " + ./bla evaluates to "foo /nix/store/hash...-bla", not "foo /path/to/current-dir/bla". This prevents accidental impurities, and is more consistent with the treatment of derivation outputs, e.g., `"foo " + bla' where `bla' is a derivation. (Here `bla' would be replaced by the output path of `bla'.)
2006-10-16 15:55:34 +00:00
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprPos::bindVars(const EvalState & es, const StaticEnv & env)
Add a symbol __curPos that expands to the current source location I.e. an attribute set { file = <string>; line = <int>; column = <int>; }.
2013-11-18 19:14:54 +00:00
{
}
* Big cleanup of the semantics of paths, strings, contexts, string concatenation and string coercion. This was a big mess (see e.g. NIX-67). Contexts are now folded into strings, so that they don't cause evaluation errors when they're not expected. The semantics of paths has been clarified (see nixexpr-ast.def). toString() and coerceToString() have been merged. Semantic change: paths are now copied to the store when they're in a concatenation (and in most other situations - that's the formalisation of the meaning of a path). So "foo " + ./bla evaluates to "foo /nix/store/hash...-bla", not "foo /path/to/current-dir/bla". This prevents accidental impurities, and is more consistent with the treatment of derivation outputs, e.g., `"foo " + bla' where `bla' is a derivation. (Here `bla' would be replaced by the output path of `bla'.)
2006-10-16 15:55:34 +00:00
Show function names in error messages Functions in Nix are anonymous, but if they're assigned to a variable/attribute, we can use the variable/attribute name in error messages, e.g. while evaluating `concatMapStrings' at `/nix/var/nix/profiles/per-user/root/channels/nixos/nixpkgs/pkgs/lib/strings.nix:18:25': ...
2013-05-16 17:08:02 +00:00
/* Storing function names. */
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void Expr::setName(SymbolIdx name)
Show function names in error messages Functions in Nix are anonymous, but if they're assigned to a variable/attribute, we can use the variable/attribute name in error messages, e.g. while evaluating `concatMapStrings' at `/nix/var/nix/profiles/per-user/root/channels/nixos/nixpkgs/pkgs/lib/strings.nix:18:25': ...
2013-05-16 17:08:02 +00:00
{
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
void ExprLambda::setName(SymbolIdx name)
Show function names in error messages Functions in Nix are anonymous, but if they're assigned to a variable/attribute, we can use the variable/attribute name in error messages, e.g. while evaluating `concatMapStrings' at `/nix/var/nix/profiles/per-user/root/channels/nixos/nixpkgs/pkgs/lib/strings.nix:18:25': ...
2013-05-16 17:08:02 +00:00
{
this->name = name;
body->setName(name);
}
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
std::string ExprLambda::showNamePos(const EvalState & state) const
Show function names in error messages Functions in Nix are anonymous, but if they're assigned to a variable/attribute, we can use the variable/attribute name in error messages, e.g. while evaluating `concatMapStrings' at `/nix/var/nix/profiles/per-user/root/channels/nixos/nixpkgs/pkgs/lib/strings.nix:18:25': ...
2013-05-16 17:08:02 +00:00
{
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
std::string id(name
? concatStrings("'", state.symbols[name], "'")
: "anonymous function");
return fmt("%1% at %2%", id, state.positions[pos]);
Show function names in error messages Functions in Nix are anonymous, but if they're assigned to a variable/attribute, we can use the variable/attribute name in error messages, e.g. while evaluating `concatMapStrings' at `/nix/var/nix/profiles/per-user/root/channels/nixos/nixpkgs/pkgs/lib/strings.nix:18:25': ...
2013-05-16 17:08:02 +00:00
}
printStats(): Print the size of the symbol table in bytes
2013-10-08 13:34:57 +00:00
/* Symbol table. */
size_t SymbolTable::totalSize() const
{
size_t n = 0;
store Symbols in a table as well, like positions this slightly increases the amount of memory used for any given symbol, but this increase is more than made up for if the symbol is referenced more than once in the EvalState that holds it. on average every symbol should be referenced at least twice (once to introduce a binding, once to use it), so we expect no increase in memory on average. symbol tables are limited to 2³² entries like position tables, and similar arguments apply to why overflow is not likely: 2³² symbols would require as many string instances (at 24 bytes each) and map entries (at 24 bytes or more each, assuming that the map holds on average at most one item per bucket as the docs say). a full symbol table would require at least 192GB of memory just for symbols, which is well out of reach. (an ofborg eval of nixpks today creates less than a million symbols!)
2022-03-05 13:40:24 +00:00
dump([&] (const Symbol & s) { n += std::string_view(s).size(); });
printStats(): Print the size of the symbol table in bytes
2013-10-08 13:34:57 +00:00
return n;
}
* Use a proper namespace. * Optimise header file usage a bit. * Compile the parser as C++.
2006-09-04 21:06:23 +00:00
}
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